Syllabus for PSYC 301: Elementary Statistics for Psychology (Spring, 2022)

1 Overview

1.1 Main Class meetings

Table 1.1: Main-Class Information for PSYC 301
Sections Days Time Location Credit Hours
Dr. Patrick Bolger
902-905 MWF 1:50-2:40 pm PSYC 108 4
Dr. Yumiko Mochinushi
912-915 TTh 3:55-5:10 pm PSYC 106 4


1.2 Lab Meetings

Table 1.2: Section Information for PSYC 301
Section TA(s) Hours
Sections 902-905, Tuesdays in Milner 202
902 Tiffany Truong 10:00 am - 12:00 pm
903 Emily Johnson 12:00 pm - 2:00 pm
904 Ty Gadberry 2:00 pm - 4:00 pm
905 Ran Wang 4:00 pm - 6:00 pm
Sections 912-915, Wednesdays in Milner 202
912 Sungjoon Park 10:00 am - 12:00 pm
913 Cecily Oleksiak 12:00 pm - 2:00 pm
914 Caroline Gonynor 2:00 pm - 4:00 pm
915 Mia Kreitlow & Devin Guthrie 4:00 pm - 6:00 pm


1.3 Contact Information

Table 1.3: People in Sections 902-905
Name Role Section(s) E-Mail Office Location Student Hours Student Hours Format
Main Instructor
Patrick Bolger, PhD Main Instructor 902-905 Psychology 220\(^{\dagger}\) Mondays & Wednesdays, 9-10 am online only via Zoom
Lab TA for Section 902, Tuesdays, 10am-12pm, Milner 202
Tiffany Truong TA 902 Milner 127\(^{\dagger}\) By appointment only online only via Zoom
Lab TA for Section 903, Tuesdays, 12-2pm, Milner 202
Emily Johnson TA 903 Psychology 330 Thursdays, 2:15 to 3:15, and by appointment if needed face-to-face only
Lab TA for Section 904, Tuesdays, 2-4pm, Milner 202
Ty Gadberry TA 904 ILSB 3149\(^{\dagger}\) By appointment only online only via Zoom
Lab TA for Section 905, Tuesdays, 4-6pm, Milner 202
Ran Wang TA 905 Psychology 332\(^{\dagger}\) Mondays, 1-2 pm online only via Zoom
Undergraduate Teaching Scholar (all sections)
Elizabeth Landin UGTS\(^{\ddagger}\) 902-905 n/a n/a n/a

\(\dagger\) Strikethrough font means that the office location is for documentation purposes only. Student hours are online only.

\(\ddagger\) Undergraduate Teaching Scholar


Table 1.4: People in Sections 912-915
Name Role Section(s) E-Mail Office Location Student Hours Student Hours Format
Main Instructor
Yumiko Mochinushi, PhD Main Instructor 912-915 Milner 226\(^{\dagger}\) Mondays 2-5 pm or by appointment online only via Zoom
Lab TA for Section 912, Wednesdays, 10am-12pm, Milner 202
Sungjoon Park TA 912 n/a\(^{\dagger}\) Wednesdays, 1-3 pm online only via Zoom
Lab TA for Section 913, Wednesdays, 12-2pm, Milner 202
Cecily Oleksiak TA 913 ILSB 3201 Tuesdays & Fridays 12-1 pm ALSO online via Zoom
Lab TA for Section 914, Wednesdays, 2-4pm, Milner 202
Caroline Gonynor TA 914 n/a\(^{\dagger}\) Tuesdays, 2-4 pm online only via Zoom
Lab TAs for Section 915, Wednesdays, 4-6pm, Milner 202
Mia Kreitlow TA 915 n/a\(^{\dagger}\) Mondays, 10-11 am online only via Zoom
Devin Guthrie TA 915 n/a\(^{\dagger}\) Wednesdays, 3-4 pm online only via Zoom
Undergraduate Teaching Scholars (all sections)
Brandon Watanabe UGTS\(^{\ddagger}\) 912-915 n/a n/a n/a
Yutika Raina UGTS\(^{\ddagger}\) 912-915 n/a n/a n/a

\(\dagger\) Strikethrough font means that the office location is for documentation purposes only. Student hours are online only.

\(\ddagger\) Undergraduate Teaching Scholar


2 Details

2.1 Class

2.1.1 Description

Statistics is the art of stating in precise terms that which one does not know. – William Kruskal

Statistics is a body of methods for making wise decisions in the face of uncertainty. – Wallis & Roberts (1956)

Statistics is the math of estimation, prediction, and uncertainty. The course will teach you to use a broad set of statistical methods to analyze data and interpret hypothesis tests. We will emphasize statistical reasoning and its interpretation rather than memorization of formulas. You will be trained to be critical consumers of research findings described in both the scientific literature and popular media. You will not have to perform calculations during exams; they are done as homework assignments. But these require nothing more than basic algebra. The emphasis of this class is on understanding the logic of the statistical methods. If you can use a simple four-function calculator, you can do statistics.

This class also includes a lab component where you will learn how to use statistical software, specifically the free, open software platform jamovi, and write up results of your own research, which you conduct in group projects.


2.1.2 Meetings

Meetings for the main class are remote and synchronous.


2.1.3 Special Designation

Writing Intensive (W)

This course is a university designated “W” course. Although statistics may not seem like the most obvious class to be writing-intensive, effective communication about statistical analyses and the interpretation of results is a crucial part of psychological science. Writing well is a set of skills that can be developed with deliberate practice. You will have the chance to develop such skills in this course.

Accordingly, since it is a 4-unit W course, at least 25% of your grade must be based on writing. In this class, there are both rough and final drafts. Together, they comprise 34% of your total grade, or 339 points out of 1000.

Additionally, as per the rules of the Department of Psychological and Brain Sciences, you must pass the writing portion of the course with at least 60% of the points on the writing assignments (59.5% in this class rounds up to 60%). For this class, this means that your total summed score across all FINAL drafts of papers must reach at least 130 out of 219 points.

Failure to obtain 130 points for the four final drafts will result in a failure to pass PSYC 301 altogether, irrespective of your cumulative score out of 1000 for the entire class (main class + lab).

Two additional rules:

  • You must turn in eight writing products total in order to pass the class. These comprise the rough and final drafts for all four writing assignments.
  • The final draft of each writing assignment must also show changes based on the feedback on the respective rough draft.

Failure to turn in all eight of these products with significant changes between each rough-final draft pair will result in failure of the entire PSYC 301 course.


2.1.4 Prerequisites

Grade of C or better in PSYC 107; MATH 140 or MATH 150 with a grade of C or better, MATH 168, MATH 142, MATH 166, MATH 151, MATH 171, MATH 131, or MATH 147; major in psychology.


2.1.5 Course Catalog Description

If you are interested for some reason, the description from the Undergraduate Course Catalog is quoted below.

PSYC 301 Elementary Statistics for Psychology
Credits 4. 3 Lecture Hours. 2 Lab Hours.
Practical knowledge of statistics up through analysis of variance. Practice sessions devoted to numerical problems. Will not satisfy mathematics requirement in College of Liberal Arts curricula.


2.2 Lab

2.2.1 Description

This lab is designed to complement the lecture portion of PSYC 301. In the main class, you will learn the logic behind various statistical tests, how they are computed, and how to interpret them.

In the lab, you will apply this knowledge and learn both to run statistical tests (using software) and to write about the results for professional reports. This is similar to what psychological researchers do every day (in part, anyway).

The central focus of the lab is the Research Project, which is carried out in small groups, and comprises the following components, not all in chronological order:

  • Designing a survey
  • Collecting data
  • Organizing the data for analysis
  • Analyses
    • a t-test
    • a oneway ANOVA
    • a correlation
    • a simple regression
  • Writing
    • Rough drafts
    • Final drafts

Again, these will be carried out in groups of about 4-5 students. We normally organize students into groups based on mutual research interests. However, in the Covid era, we need to do this by masking preferences. Students who prefer to wear masks will be put into groups together, as much as is possible. The same is true for students who prefer not to wear masks.

With these groups, you will also engage in further activities that will help you achieve a deeper understanding of the topics covered in lecture.

Video watchings, support tasks, writing assignments, and research-group lab tasks are worth just under 54% of your total grade(or 544/1000).

Thus, actively participating in lab is important for success in this course.

There is much more information about these assignments and tasks under the heading Tasks (section 4), as well as Grades (section 5).


2.2.2 Meetings

Meetings for the all the labs are weekly and face-to-face. If students need to quarantine, we have Zoom on all the computers in Milner 202 so that groups can still meet. All labs will have a Zoom option, and they will be recorded for asynchronous viewing.


3 Outcomes

3.1 Class

At the end of the main class in PSYC 301, the successful student should be able to critically evaluate quantitative information in psychological research, the main sub-skills of which are listed below (success measured on exams and homework problems):

  • Understand how constructs, operationalization, and variables relate to each other in scientific measurement
  • Understand what Null Hypothesis Significance Testing (NHST) is, along with Type I and Type II errors, and the controversy surrounding the NHST approach
  • Understand the various sources of the replication crisis, and what future researchers need to do to change this state of affairs
  • Understand how probability and descriptive statistics work together to make larger inferences, with special emphasis on the following:
    • Understanding what p-values are and are NOT
    • Understanding what confidence intervals are and are NOT
  • Interpret inferential statistics to evaluate the following:
    • Whether there are differences between two or more groups
    • Whether there are linear associations between two or more variables
  • Compute and evaluate simple effect sizes
  • Understand how the parametric statistics covered in this class are not disparate techniques, but rather form a unified family of techniques

3.2 Lab

At the end of the lab PSYC 301, the successful student should be able to do all the of the following:

  • Design and collect data that can be analyzed statistically, as measured by the quality of the Google Forms survey (Support Task #2)
  • Import data into jamovi for statistical analysis, as measured by success in getting the data from Google Drive into jamovi (Support Task #3)
  • Analyze data for diagnostic, inferential, and visual analysis in jamovi, as measured by support tasks #4-8
  • Write a primary-research manuscript in the IMRaD format required by the American Psychological Association (APA), as measured by the writing assignments
  • Work together effectively in small groups


3.3 University

Texas A&M University has identified student learning outcomes that describe our institutional commitment to your educational goals. These include the ability to demonstrate critical thinking, effective communication, and social, cultural, and global competence. Please see https://catalog.tamu.edu/undergraduate/general-information/student-learning-outcomes/.


3.3.1 Knowledge Required for the Degree

As the field of Psychology in the modern era requires significant quantitative skills, you will learn to use statistical techniques to summarize sample data (descriptive statistics) and how to use that sample data make inferences about population parameters (inferential statistics). You will learn how to distinguish claims of statistical significance (null-hypothesis significance testing, confidence intervals, etc.) from claims about substantive or practical significance (effect size).


3.3.2 Critical Thinking

You will learn how to critically evaluate statistical results and quantitative information reported in psychological research.


3.3.3 Communication

You will learn how to communicate statistical results to other researchers in Psychology. You will learn how to interpret statistical information presented in scientific reports.


3.3.4 Personal and Social Responsibility

You will consider how data should be collected, presented, and interpreted in an ethical manner. You will learn about the importance of transparency in conducting and reporting statistical analyses.


3.3.5 Collaboration

You will work in teams to design a study and collect data. Almost all research projects in the field of Psychology are collaborative in the modern era.


4 Tasks

4.1 Tasks in main class

4.1.1 Readings

The readings for the main class are done through Perusall. Perusall is a social-reading platform that allows you to see your classmates’ comments. These are kept anonymous in this class.

Each of these 14 readings over the course of the semester is worth 4 points, or 56 points total. This amounts to 6% of the total final grade.

The assignments are graded automatically by Perusall using a highly complex algorithm. This algorithm is designed to detect legitimate engagement with the material. In short, as long as you are reading the material deeply, and providing thoughtful comments and replies to comments, Perusall will reward you with high scores.

Except for the first reading assignment (which is due on the Friday of the first week), these assignments are always due before class begins on the first instructional day during the week in which the Perusall assignment is considered due. That is, if you have a MWF class, it’ll be due before class begins on Monday, and if you have a TTh class, it will be due before class begins on Tuesday.

4.1.2 Exams

4.1.2.1 Overview

There will be four exams (the 4th being the cumulative final exam), each worth 75 points (summing to 300 points, or 30% of your total grade).

Exams will include multiple-choice questions only. Exams 1-3 (but not the final) will be explicitly focused on the topics covered in just that section of the course. But note again that the final exam is cumulative.

These exams will all be online through the Respondus Lockdown Browser. The Lockdown Browser is a special browser that shuts down all your other applications on that computer while you take exams.

In the Respondus Lockdown Browser, you’ll need to do the following before any exam:

  • verify your student ID
    • If you do not have your Student ID handy, you should log in to the Howdy Portal and click on the My Profile tile. In the top right corner, you will see you Aggie Card photo along with your full name and UIN. You may choose to take a screenshot of this display with your smart phone or print it out in order to present for exams.
  • perform an environment check to show that your environment doesn’t have notes
  • record the exam with your webcam

A simple calculator will be available on screen. Otherwise, you should be looking at the screen.


4.1.2.2 Exam re-takes

The good news is that the exams in this class are now more of a formative nature instead of summative nature. This means that the tests are more focused on helping you learn rather than assessing your knowledge, per se.

The translation for you is that in this course, you can re-take each exam up to 3 times within the exam date-interval. Note however that there is a 12-hour waiting period between each attempt, starting at the END of each attempt.

IMPORTANT: Note that this means that if you finish your first attempt exactly 24 hours before the deadline, you will only get 2 attempts total; you will miss the third because you didn’t allow a 1 hour, 15 minute cushion for the second attempt, leaving you with less than 12 hours between the second and third attempts. The same is true if you finish your first attempt 12 hours before the deadline, you will only get one attempt total.

We will accept your highest score of the 1-to-3 attempts on each exam that you take/re-take.

However, there are some ground rules to this process. Details are provided below:

4.1.2.3 Key Exam Dates

  • Exam 1
    • The attempt window begins on Friday, 11 February at 5:00 pm
    • The attempt window ends on Wednesday, 16 February at 11:59 pm
  • Exam 2
    • The attempt window begins on Friday, 4 March at 5:00 pm
    • The attempt window ends on Wednesday, 9 March at 11:59 pm
  • Exam 3
    • The attempt window begins on Friday, 8 April at 5:00 pm
    • The attempt window ends on Wednesday, 13 April at 11:59 pm
  • Final Exam
    • The attempt window begins on Thursday, 5 May at 8:00 am
    • The attempt window ends on Tuesday, 10 May at 4:30 pm

4.1.2.4 Exam guidelines

There are more exam guidelines, but since the exams will be online, we have included these guidelines in section 7.4.1.2 below. This is because the guidelines are tightly related to how to use the Respondus Lockdown Browser.


4.1.3 Homework Problems

The homework problems assigned in the main class involve calculations. In the table below, you can see when will appear online, and when they are due. These are all Fridays, and the time that they are due is always 11:59 pm. These are also listed on the course schedule (section 6.1). Note that they can be quite involved, and will probably take you between 1/2 hour and an hour to complete (especially the more difficult ones).

If you are not satisfied with your score on any given attempt, you just make a request in the associated Request to re-do HW… (a Google Form that you fill out). The undergraduate Teaching Scholar for the class will update the assignment so that you can re-take it the following day. But note that on any re-take, you will get a different data set.

You can re-attempt any given homework up to once per day throughout the time window when that particular homework assignment is available.

There are thirteen of them. See below.

Table 4.1: Homework Problems by Date
Number Problem Name Available Due Difficulty Points
1 Central Tendency 28 Jan 4 Feb Easier 5
2 Variation 4 Feb 18 Feb Easier 5
3 z-scores 4 Feb 18 Feb Easier 5
4 Boxplots 11 Feb 25 Feb Easier 5
5 Standard Error & Confidence Intervals 18 Feb 11 Mar Harder 8
6 Area Under Curve 18 Feb 11 Mar Hardest 12
7 Chi-Square 4 Mar 25 Mar Harder 8
8 Independent-samples t-test 11 Mar 1 Apr Harder 8
9 ANOVA table 25 Mar 8 Apr Harder 8
10 ANOVA Sums of Squares 25 Mar 8 Feb Hardest 12
11 Correlation 1 Apr 15 Apr Harder 8
12 Simple Regression 8 Apr 22 Apr Harder 8
13 paired-samples t-test 15 Apr 29 Apr Harder 8
Note:
All homework together sum to 100 points

4.1.4 Extra credit

There is only one kind of extra credit in this course. In addition to the four reviews you are required to do, you are also allowed (but not required) to do up to 4 extra peer reviews during the peer-review period in Peerceptiv. Your extra credit, however, is not reflected in a separate grade column in Canvas Rather, it is reflected directly in your grade for the particular assignment in Peerceptiv. That is, Peerceptiv takes care of your extra-credit points, not us.

Otherwise, there is no extra credit in this course (though the formative exams and homework problems might be considered an indirect way of doing this).

So please do not ask us at the end of the semester about extra-credit opportunities. The answer is always “No.”

4.2 Tasks in Lab

Briefly, what you learn as theory in the main class, you carry out in the lab portion of the course.

There are 544 points possible in the lab, the majority of which is carried by the research project (435points), and a minority by weekly tasks carried out in lab (65 points).


4.2.1 Attendance

(65 points [5 points \(\times\) 13 physical attendances], or 6% of the total grade)

Lab attendance is important for mastering material.

Each lab session will also be available in Zoom, and live attendance in Zoom is acceptable. Although each lab will be recorded as well for later viewing, just watching the lab asynchronously will not be considered as having attended.

4.2.2 Watching how-to videos

There are how-to videos that you need to watch as homework for the lab. Like the reading assignments in the main class, you watch these videos through Perusall. Again, Perusall is a social-reading (in this case -watching) platform that allows you to see your classmates’ comments. These are kept anonymous in this class.

Each of these 11 “watchings” over the course of the semester is worth 4 points, or 44 points total. This amounts to 4% of the total final grade.

Again, each assignment is graded automatically by Perusall using a highly complex algorithm. This algorithm is designed to detect legitimate engagement with the material. In short, as long as you are watching the videos carefully, and providing thoughtful comments and replies to comments, Perusall will reward you with high scores.

They are always due at 9 am on the day of your lab (irrespective of when your lab actually starts) during the week in which the Perusall assignment is considered due.

4.2.3 Research Project

You will be carrying out a small research project in groups of about four students. This project is broken down into various parts.

  • There will be 8 Support Tasks that you turn in as a group, each worth 12 for a total of 96 points. The support tasks revolve around research design, data collection, preparation, and analysis.
  • You will also write somewhat simplified version of an APA primary-research manuscript. This will come in the form of four writing assignments, each of which in turn comprises a rough and a final draft.
    • The 4 rough drafts are each worth 30 points (120 total), and are peer-reviewed (by your classmates) through Peerceptiv.
    • The final drafts have varying point values. See below.


4.2.3.1 Support Tasks

There are a total of 8 Support Tasks Each is worth 12 points, or 96 points total. This amounts to 10% of the total final grade.

The support tasks are done individually by student, even though many of them involve shared data sets (i.e., the data set generated by the research group you’ll be in).

For each support task (with the exception of the first), there will be some extra questions you will need to answer.

Support Task #1 is unique, and involves providing examples of what you think might be good research questions and variables for a group project, given what you learned in the first week (in the main class).

For the other support tasks, your answers will be provided through Gradescope. In each of these cases, you either provide a link or upload a .omv file, and then answer some questions related to what you linked or uploaded.

At no point should you be tempted to copy your group-mates’ answers. You can talk to each other about the answers to the questions, but those answers must be in your own words.

The support tasks are listed in order below.


4.2.3.1.1 Brainstorm (1 task)

Students will brainstorm on possible topics through a survey provided by the main instructor. When this survey is completed, the instructor will assign 12 points to those who completed the survey on time. This is due at the latest on Saturday, 22 January at 5 pm.


4.2.3.1.2 Design (1 task)

Students will design their study in Google Forms in a Google Drive folder (specific folders shared out of the head instructor’s Google Drive account).\(^{\dagger\dagger}\) When the study is approved by the TA (due Friday, 4 February at 11:59 pm), each group member will then fill out a survey, which is due on Friday, 4 February at 11:59 pm. Based on the answers to the survey, the group members get up to 12 points each.

\(\dagger\dagger\) This will be your group’s survey for the semester. It will be housed in a Google Drive folder that has been assigned to you in the head instructor’s Google Drive. This is the only location considered official for your survey. Do not create any other Google Drives or use any other cloud-storage tools to put your survey.


4.2.3.1.3 Data (1 task)

The groups will collect data. When that data collection is complete and the data have been saved into a jamovi file (.omv), uploaded into the same Google Drive folder,\(^{\dagger\dagger}\) and approved by the TA, each member of the group will also answer a survey. They will get up to 12 points for their answers. This support task is due Friday, 18 February at 11:59 pm.

\(\dagger\dagger\) This will be your group’s official data for the semester. It will be housed in a Google Drive folder that has been assigned to you in the head instructor’s Google Drive. This is the only location considered official for your data. Do not create any other Google Drives or use any other cloud-storage tools to put this data. That said, the support tasks below (Outputs) should be carried out on a copy of the data you download from this Google Drive folder.


4.2.3.1.4 Outputs (5 tasks)

There are four writing assignments total, but the last three of these require several data-analysis steps. Writing Assignment #2 requires one data analysis, and the last two writing assignments each require two data analyses. This sums to five outputs, and five support tasks, accordingly.

For each of these last five support tasks, you will upload your analysis to the assignment in Gradescope, and then answer the questions that are in the survey (in the same Gradescope assignment). Students can get up to 12 points based on their answers, and the appropriateness of the respective analysis.

Due dates:

  • Support task 4 is due Friday, 25 February at 11:59 pm
  • Support task 5 is due Friday, 11 March at 11:59 pm
  • Support task 6 is due Friday, 25 March at 11:59 pm
  • Support task 7 is due Friday, 8 April at 11:59 pm
  • Support task 8 is due Friday, 8 April at 11:59 pm


4.2.3.2 Writing Assignments

There are four writing assignments (divided into 4 rough and 4 final drafts) totaling 339 points out of 1000, or 34% of the class total.

The four writing assignments correspond roughly to the sections typically found in a published original-research paper in Psychology (IMRaD -> Introduction, Method, Results, and Discussion) . They should also be formatted according to the manuscript-formatting guidelines of the American Psychological Association. More details about this are in the lab manual (Bolger, 2020).

Recall that this is a W course. As such, you are required to submit both rough drafts (section 4.2.3.2.1) and final drafts (section 4.2.3.2.2) of writing assignments. See the respective sections below for more details on these assignment types.

4.2.3.2.1 Rough Drafts

Read this section carefully. It is the most complex part of this course.

There are 4 rough drafts at 30 points each, which is 120 points total, or 12% of the class total.

Each of the 4 rough drafts serves as a draft for your peers to review online. As one of these peer review-ers, you will review four other papers. Subsequently, as a review-ee, you will use the feedback from others to revise your own final draft.


You might also get direct feedback from your TA. TAs will randomly spot-review about 20-25% of the papers assigned to them.

These rough drafts are due on the following dates and times:

  • Assignment #1 (rough draft): by 9:00 am, the day of your lab, 8 or 9 February
  • Assignment #2 (rough draft): by 9:00 am, the day of your lab, 1 or 2 March
  • Assignment #3 (rough draft): by 9:00 am, the day of your lab, 29 or 30 March
  • Assignment #4 (rough draft): by 9:00 am, the day of your lab, 19 or 20 April

Rough drafts must be turned in via Peerceptiv within Canvas. A special link is provided in Canvas. Note that you must access Peerceptiv assignments from within Canvas using that special link. Do not go to the Peerceptiv website to log in; this leads to problems.

Turning in your rough draft late leads to accruing penalties in two ways:

  1. Submitting your rough draft at any time between 9 am on the day of your lab and 9 am of the subsequent day is a submission during the “grace period”. It will result in an automatic 50% off your peer-review grade (or 15 out of 30 points). If you upload your draft on time (or at least by the end of the grace period), the grading of the rough draft is done automatically through Peerceptiv as other students receive your draft and evaluate it.

  2. If you miss the grace period, then Peerceptiv will no longer allow you to upload your paper.\(^{\dagger\dagger}\) In this case, you will need to submit your draft to an alternative assignment that will be assigned to you after the grace period. This can happen in one of two ways:

  • Legitimate excuse: If you missed the deadline and the grace period because of a legitimate reason as spelled out in Student Rule #7, then you will upload your paper to an assignment labeled late EXCUSED rough draft of writing assignment #X. This will be worth 30 points.
  • Non-legitimate excuse: If it is not legitimate under Student Rule #7, then you will upload your paper to an assignment labeled late UN-excused rough draft of writing assignment #X. This will be worth 15 points (the penalty applied for a submission within the grace period). But see the bullet point below.
  • Incremental penalties for late rough drafts: You will receive additional cumulative 10% deductions off your FINAL draft for every 24-hour period (9 am one day to 9 am the next day) that the ROUGH draft is late after the grace period. This penalty accrues on your final draft (and not your rough draft) since (understandably) Peerceptiv will not allow you to upload a document after the grace period. The 10% penalty on your final draft accrues each day for 10 days after the grace period, at which point you can no longer get any points for the final draft (i.e., the penalties will have accrued to 100%).

\(\dagger\dagger\) Peerceptiv does this because your paper probably will not get reviewed by a peer at all after the grace period. This is because everyone else will be finishing up with their reviews.


4.2.3.2.2 Final Drafts

(varying points each [see bullet points below]; 219 points total)

  • Final Draft of Writing Assignment #1: 44/219 points (or 20%)
  • Final Draft of Writing Assignment #2: 55/219 points (or 25%)
  • Final Draft of Writing Assignment #3: 45/219 points (or 21%)
  • Final Draft of Writing Assignment #4: 75/219 points (or 34%)


You will apply the feedback from your rough draft to your final (improved) draft. This is due at 9 am on the day that your lab meets, usually two weeks after the peer review.

Specifically:
- Assignment #1 (final draft): by 11:59 pm, Friday, 25 February
- Assignment #2 (final draft): by 11:59 pm, Friday, 25 March
- Assignment #3 (final draft): by 11:59 pm, Friday 15 April
- Assignment #4 (final draft): Tuesday, 3 May by 11:59 pm

Final drafts will be turned in via a standard assignment in Canvas. In the background, it will be checked by Turnitin. Note that there is no need to access anything from the Turnitin website itself, except for help files, if you need them.

Turning in your final draft late accrues penalties daily. Specifically, 10% will be deducted from the grade of your final version for each 24-hour period the assignment is late after the initial deadline. These penalties will accrue for up to 10 days after the initial deadline, after which is will certainly be worth zero points (a 100% would have accrued).

Note however, that if you have penalties carrying over from a rough draft turned in after the grace period (see above), fewer days will elapse before you reach a zero-point maximum on your final draft.


4.2.3.3 Important requirements


4.2.3.3.1 The 60% requirement

NOTE THAT IRRESPECTIVE OF YOUR GRADE FOR THE OVERALL CLASS, YOUR SCORE SUMMED ACROSS THE FINAL DRAFTS MUST REACH AT LEAST 130 OUT OF 219 POINTS IN ORDER TO PASS PSYC 301 (60% of 219).

Note that the points for the rough drafts do not count towards this particular W course requirement, but do indeed contribute substantially to your overall grade.

This is also covered under Grades below (specifically, section 5.2.2).


4.2.3.3.2 Absolute two-draft requirement

You must turn in two drafts per assignment, amounting to a total of 8 drafts. This entails that you cannot submit a final draft without already having submitted a rough draft and received feedback on it. For example, if you think you just want to skip the rough draft, and just submit what you think is your “final draft” on the day that the final draft is due, you will find that your submission is worth 0 points towards the final draft. Instead, you will receive whatever amount of credit you can still muster on your rough draft, plus any penalties on your final draft. This is followed by a minimum of 1 day, after which point, you can submit your final draft (with substantial changes based on instructor feedback). For that one day, you will not lose points, but the 10%-deduction clock begins after the 24-hour period has expired.

This is also covered under Grades below (specifically, section 5.2.3).


4.2.3.3.3 Substantial revision requirement

Each final draft must reflect substantial changes from the respective rough draft, and these changes must both be commensurate with and accommodate the feedback on that rough draft. If we find that your have turned in a final draft that has not taken the feedback seriously, your TA reserves the right to return it to you to revise again. In this case, the late-submission clock re-sets itself to the day we notice the failure to make substantial changes. It continues to “tick” daily after that point, however.

These are not covered further in Grades below (section 5) since we will just reject and return the draft to you for further revision in this case.


4.2.3.3.4 Independence and originality requirements

Although these are group projects, each student works independently on typing and completing each writing assignment throughout the semester. Plagiarism is not permitted in this class (nor is it ever, anywhere, in case you “missed the memo”.

You may ask questions of each other (especially your group-mates) to help complete these assignments. HOWEVER, every person must turn in an individual assignment and no two (or more) students’ assignments should be identical in form or even similar (content yes; form no). To clarify, you can be saying the same thing, but your wording cannot match or even be similar. Assignments that are too similar may not be graded and may be treated as violations of the honor code, specifically: plagiarism. You will get a lecture on plagiarism in lab.

Violations of this requirement are also not covered further in Grades below (section 5) since each case is unique and has to go through the Aggie Honor System Office (AHSO) to finalize grading penalties (and possibly more).

Typically, the penalty we apply is a zero for the assignment. But penalties can be more severe if we so determine, or if the student has a previous record with AHSO.

Note that reporting to AHSO is mandatory for professors in such cases (if the professor determines that such academic dishonesty has occurred).

Also, do not bother your TAs with issues of plagiarism. Their job is to identify the possibility of plagiarism, and then contact the head professor. They are merely the messenger. Once the issue reaches the professor, it is out of the TA’s hands. And the student will only be notified after the issue has reached the professor. So in sum, do not contact the TA about any kind of academic dishonesty that is suspected on your part; communicate only with the head professor.


4.2.3.4 Helpful hint

4.2.3.4.1 Confirming your uploads in Peerceptiv

For Peerceptiv, make sure that it says “Document Submitted” (after submitting) [take a screenshot if you want proof]; if it doesn’t, SUBMIT AGAIN.

4.2.3.5 Requirement

4.2.3.5.1 Cloud-based documents

We are now requiring that you write your papers as a Google Doc.

This is actually to help you, and my guess is that from here on you, you will want to write all your papers as Google Docs.

Here’s why:

Versioning!!. Google will save versions of your documents automatically, meaning that it will save time-stamped snapshots of your document as you work on it. The primary advantage to this (and this is HUGE) is that you can prove to your professors (even in other courses) that a particular draft was completed at a particular time.

And in case you were wondering, this problem comes up every single semester, no exceptions so far.

EVERY.SINGLE.SEMESTER

Although Microsoft 365 also does this (with Word documents on that cloud service), Google is a little bit better since you can control the versioning yourself. Specifically, within your Google Doc, if you go to File > Version history > Name current version, then you can give a name to whatever version you just finished working on (e.g., WA1_FinalRoughDraftForPeerceptiv). Then, if you ever happen to mess up the uploading to Peerceptiv (which happens every semester for some students, even the best ones), all you need to do is grant your professor Editor privileges to the document, and they can see all the versions of the document, the time stamps, and even compare them for changes.

In Office 365, it seems that you need to trust Microsoft to create versions for you automatically. This is why we want you to use Google Docs.


5 Grades

5.1 Breakdown by Assignment

Final grades will be assigned at the end of the semester on the basis of the total number of points earned out of a possible 1000 points, based on the following components:

Locus Component Points per Component Number of Components Total Points %
Main Class Exams 75 4 300 30%
Main Class Perusall Readings 4 14 56 5.6%
Main Class Easier HW Problems 5 4 20 2%
Main Class Harder HW Problems 8 7 56 5.6%
Main Class Hardest HW Problems 12 2 24 2.4%
Lab Rough Drafts 30 4 120 12%
Lab Final Draft Assignment 1 44 1 44 4.4%
Lab Final Draft Assignment 2 55 1 55 5.5%
Lab Final Draft Assignment 3 45 1 45 4.5%
Lab Final Draft Assignment 4 75 1 75 7.5%
Lab Support Tasks 12 8 96 9.6%
Lab Perusall Videos 4 11 44 4.4%
Lab Attendance 5 13 65 6.5%
TOTALS: 1000 100%


5.2 Final Letter Grades


The Total Points in Class tab is what your grade will be, assuming that you have met Condition 1 (section 5.2.2) and Condition 2 (5.2.3). Those additional conditions are covered in separately, as you can see below.


5.2.1 Total Points in Class


Below, \(y\) represents any particular student’s total percentage/points for the course. Letter grades (with strict cutoffs) will be assigned as follows:


Grade A B C D F
Percents 89.5% \(\le y\) 79.5% \(\le y \lt\) 89.5% 69.5% \(\le y \lt\) 79.5% 59.5% \(\le y \lt\) 69.5% \(y \lt\) 59.5%
Points 895 \(\le y\) 795 \(\le y \lt\) 895 695 \(\le y \lt\) 795 595 \(\le y \lt\) 695 \(y \lt\) 595

5.2.2 Condition 1: The 60% requirement


As noted above in section 4.2.3.3.1, this is a W Course. This means that you must get 60% of the point total for the final drafts in the lab; otherwise, you fail the entire PSYC 301 course. Below, \(k\) represents any particular student’s total percentage/points on the final-draft assignments (they are collectively worth 219 points.)


Grade A-D F
Percent 60% \(\le k\) \(k \lt\) 60%
Points on Final Drafts (\(k\)) 130 \(\le k\) \(k \lt\) 130

5.2.3 Condition 2: All 8 drafts submitted


As mentioned above in Tasks (section 4.2.3.3.2), you MUST turn in all 8 drafts of the writing assignments (4 rough drafts; 4 final drafts); otherwise, you fail the entire course. The grade breakdown is simple, but as follows, where \(j\) is the number of drafts any given student turns in:


Grade A-D F
Number of Drafts Turned In (\(j\)) \(j =\) 8 \(j \lt\) 8


6 Schedules

6.1 Main Class Schedule

Table 6.1: Main Class Schedule by Week
Week Start Date End Date Topic(s) Reading/Watching Start Finish
Unit 1: Background & Descriptive Statistics
1 1/18/2022 1/21/2022
  • welcome
  • introductions
  • syllabus
  • group research projects
  • why we do statistics; scales of measurement
  • read NF19: chs. 1, & 2 (2.1 to 2.2 only)
  • read Bolger20: Preface
  • Support Task #1 - Topic Brainstorm (by Saturday at 5pm)
2 1/24/2022 1/28/2022
  • research design (reliability; more on variables; validity; threats to validity)
  • descriptive statistics (central tendency)
  • read NF19: chs. 2 (2.3 to 2.8 only [skipping 2.5]), & 4 (4.1)
  • HW01: Central Tendency on Friday at 11:59 pm
3 1/31/2022 2/4/2022
  • descriptive statistics (measures of variability; standard scores)
  • read NF19: ch. 4 (4.2 to 4.5 only [skipping 4.4])
  • Window opens for EXAM #1 ON FRIDAY AT 5:00 pm
  • HW02: Variation on Friday at 11:59 pm
  • HW03: z-scores on Friday at 11:59 pm
Unit 2: Visualization & Probability
4 2/7/2022 2/11/2022
  • drawing graphs
  • probability (What is it? Why is it part of a stats class?; frequentism; binomial distribution; normal distribution; other distributions)
  • read NF19: 5 & 7 (7.1 - 7.7 only)
  • Window opens for EXAM #1 ON FRIDAY AT 5:00 pm
  • HW04: Boxplots on Friday at 11:59 pm
  • Window closes for EXAM #1 on Wednesday at 11:59 pm
  • HW01: Central Tendency by Friday at 11:59 pm
5 2/14/2022 2/18/2022
  • Cronbach’s Alpha
  • samples & populations (sampling; central limit theorem; estimating parameters; confidence intervals)
  • hypothesis testing (hypothesis and error types; test statistics; decisions)
  • read NF19: ch. 15 (15.5 only), chs. 8, & 9 (9.1 to 9.4 only)
  • HW05: SE & CI on Friday at 11:59 pm
  • HW06: Area Under Curve on Friday at 11:59 pm
  • HW02: Variation by Friday at 11:59 pm
  • HW03: z-scores by Friday at 11:59 pm
  • Window closes for EXAM #1 on Wednesday at 11:59 pm
6 2/21/2022 2/25/2022
  • hypothesis testing
  • p-values
  • reporting
  • effect sizes
  • read NF19: ch. 9 (9.5 to 9.10 only)
  • Window opens for EXAM #2 on Friday at 5:00 pm
  • HW04: Boxplots by Friday at 11:59 pm
Unit 3: Inferential statistics you need for your papers
7 2/28/2022 3/4/2022
  • categorical data analysis: goodness-of-fit test; test of independence
  • effect size
  • assumptions
  • other tests
  • read NF19: ch. 10 (10.1 to 10.9 only)
  • HW07: Chi-Square on Friday at 11:59 pm
  • Window opens for EXAM #2 on Friday at 5:00 pm
  • Window closes for EXAM #2 on Wednesday at 11:59 pm
8 3/7/2022 3/11/2022
  • Comparing two means (one-sample z- and t- tests; independent-samples t-test; one-sided tests; effect size; assumptions)
  • read NF19: ch. 11 (11.1 to 11.10 only [skipping 11.5, 11.7.3, and 11.9 for now])
  • HW08: t-test on Friday at 11:59 pm
  • HW05: SE & CI by Friday at 11:59 pm
  • HW06: Area Under Curve by Friday at 11:59 pm
  • Window closes for EXAM #2 on Wednesday at 11:59 pm
9 3/14/2022 3/18/2022 SPRING BREAK - no classes
10 3/21/2022 3/25/2022
  • Comparing several means (one-way ANOVA) - theory; effect size; multiple comparisons; assumptions
  • read NF19: ch. 13 (skipping 13.3, 13.8, and 13.9)
  • HW09: ANOVA Problem on Friday at 11:59 pm
  • HW10: ANOVA Sums of Squares Problem on Friday at 11:59 pm
  • HW07: Chi-Square by Friday at 11:59 pm
11 3/28/2022 4/1/2022
  • correlation (Pearson’s r; Spearman’s rank correlation; scatterplots; correlation matrices)
  • read NF19: ch. 12 (12.1 only)
  • HW11: Correlation on Friday at 11:59 pm
  • HW08: t-test by Friday at 11:59 pm
12 4/4/2022 4/8/2022
  • simple linear regression (estimation, interpretation)
  • read NF19: ch. 12 (12.3 to 12.4 only)
  • HW12: Simple Regression on Friday at 11:59 pm
  • Window opens for EXAM #3 on Friday at 5:00 pm
  • HW09: ANOVA Problem* by Friday at 11:59 pm
  • HW10: ANOVA Sums of Squares Problem by Friday at 11:59 pm
Unit 4: Other inferential statistics
13 4/11/2022 4/15/2022
  • paired-samples t-test (basics; assumptions; effect size)
  • repeated-measures ANOVA) (adjustment to MS-within; sphericity)
  • read NF19: chs. 11 (11.5 & 11.7.3 only) & 13 (13.8 only)
  • HW13: Paired-samples t-test on Friday at 11:59 pm
  • HW11: Correlation by Friday at 11:59 pm
  • Window closes for EXAM #3 on Wednesday at 11:59 pm
14 4/18/2022 4/22/2022
  • factorial ANOVA
  • Epilogue
  • read NF19: ch. 14 (14.1 to 14.4 only) & 17
  • HW12: Simple Regression by Friday by 11:59 pm
15 4/25/2022 4/29/2022
  • multiple linear regression (basics; quantifying fit; hypothesis tests; understanding coefficients)
  • read NF19: ch. 12 (12.5 to 12.9 only)
  • HW13: Paired-samples t-test by 11:59 pm
Final Exam
16 5/2/2022 5/3/2022
  • Review
  • Begin Final Exam
  • Window opens for Final Exam at 8am on Thursday
17 05/05/2022 05/10/2022
  • Window closes for Final Exam on Tuesday at 4:30 pm

6.2 Lab Schedule

Table 6.2: Lab Schedule by Week
Week Start Date End Date Topic(s) Reading/Watching Start Finish
No labs
1 1/18/2022 1/21/2022
  • No Lab during first week
NA NA NA
Writing Assignment 1: Introduction
2 1/24/2022 1/28/2022
  • introductions
  • syllabus
  • pretest
  • group research projects
  • “do’s and don’ts on Google Forms”
  • read Bolger20: chs. 10, 12, & 13
  • Writing Assignment #1 (Introduction)
NA
3 1/31/2022 2/4/2022
  • jamovi (familiarization; basic operations)
  • practice peer review
  • read read Bolger20: chs. 1 & 2
  • watch Perusall Video 1: Orientation to jamovi
NA
  • Support Task #2 - Finalize Study Designs (Friday at 11:59 pm)
4 2/7/2022 2/11/2022
  • jamovi (descriptive statistics; data visualization
  • PEER REVIEW of Writing Assignment #1 (Introduction)
  • read Bolger20: chs. 3 & 4
  • watch Perusall Video 2: Operations and descriptives
NA
  • rough draft of Writing Assignment #1 (Introduction) to Peerceptiv by 9 am the day of your lab
Writing Assignment 2: Method
5 2/14/2022 2/18/2022
  • research projects (preparing data for analysis; Cronbach’s Alpha)
  • writing (writing Method sections)
  • read Bolger20: chs. 11 (11.1 to 11.4 only) & 14
  • watch Perusall Video 3: Getting your data into and ready in jamovi
  • Writing Assignment #2* (Method section)
  • Support Task #3 - Full Dataset for Semester by Friday at 11:59 pm
6 2/21/2022 2/25/2022
  • research projects (final steps before analysis)
  • peer review practice
  • read Bolger20: ch. 11 (11.5 only)
NA
  • final draft of Writing Assignment #1 (Introduction) by Friday at 11:59 pm
  • Support Task #4 - Statistical output Method Section by Friday at 11:59 pm
7 2/28/2022 3/4/2022
  • chi-square (basic analyses; advanced analyses are optional)
  • PEER REVIEW of Writing Assignment #2 (Method)
  • read Bolger20: ch. 5
NA
  • rough draft of Writing Assignment #2 (Method section) to Peerceptiv by 9 am the day of your lab
Writing Assignment 3: Study 1
8 3/7/2022 3/11/2022
  • jamovi (independent-samples t-test)
  • writing (writing Results sections)
  • read Bolger20: ch. 6 (6.1 only) & 15
  • Writing Assignment #3* (Study 1: Results & Discussion)
  • Support task #5 - Statistical output for t-test by Friday at 11:59 pm
9 3/14/2022 3/18/2022 SPRING BREAK - no classes NA NA NA
10 3/21/2022 3/25/2022
  • jamovi (oneway ANOVAs)
  • writing (Discussion sections)
  • read Bolger20: ch. 8 (8.1 only) & 16
NA
  • final draft of Writing Assignment #2 (Method section) to Turnitin on Friday at 11:59 pm
  • Support task #6: Statistical output for ANOVA by Friday at 11:59 pm
Writing Assignment 4: Study 2 / General Discussion
11 3/28/2022 4/1/2022
  • jamovi (correlations)
  • PEER REVIEW of Writing Assignment #3 (Study 1: Results & Discussion)
  • read Bolger20: ch. 7 (7.1 only)
NA
  • rough draft of Writing Assignment #3 (Study 1: Results & Discussion) to Peerceptiv by 9 am the day of your lab
12 4/4/2022 4/8/2022
  • jamovi (linear regression)
  • writing (Results & Discussion sections for correlation and regression)
  • Bolger 20: chs. 7 (7.2 only) & 17
  • Writing Assignment #4* (Study 2: Results & Discussion; and then General Discussion [covering the entire paper])
  • Support Task #7: Statistical output for correlation by Friday at 11:59 pm
  • Support Task #8: Statistical output for regression by Friday at 11:59 pm
13 4/11/2022 4/15/2022
  • paired-samples t-tests
  • writing the General Discussion section
  • read Bolger20: ch. 6 (6.2 only)
NA
  • final draft of Writing Assignment #3 (Study 1: Results & Discussion) to Turnitin
14 4/18/2022 4/22/2022
  • PEER REVIEW of Writing Assignment #4 (Study 2: Results & Discussion; General Discussion)
  • factorial ANOVA
  • read Bolger20: ch. 9
NA
  • rough draft of Writing Assignment #4 (Study 2: Results & Discussion; General Discussion) to Peerceptiv by 9 am the day of your lab
15 4/25/2022 4/29/2022
  • Course Evaluations | Posttest
NA NA NA
16 5/2/2022 5/3/2022
  • Tuesday is Redefined Day [Friday classes] (no lab)
  • Wednesday is Reading Day (no lab)
NA NA
  • final draft of Writing Assignment #4 (Study 2: Results & Discussion; General Discussion) to Turnitin on Tuesday at 11:59 pm
Note:
NF19 = Navarro & Foxcroft (2019) - your main textbook
Bolger20 = Bolger (2020) - your lab manual
All times refer to the day of your particular lab, unless otherwise specified
However, note that all uploads to Peerceptiv are due at 9:00 AM on the day of your lab, no matter what time your lab actually meets


7 Materials

7.1 OER

You do not need to purchase anything beyond the university’s requirement of a computer, necessary peripherals, and your tuition/fees. Well, almost. The one exception is just a suggestion that you purchase a headset with a microphone in case you need to quarantine. All of the other materials in this course come at no further cost to you.

That is, they are free, Open Educational Resources (OER).

So although these materials are free, they do still exist, and you need to get them. See below.



7.2 Textbooks


7.2.1 Main Class

  • Navarro, D. J., & Foxcroft, D. R. (2019). Learning statistics with jamovi: A tutorial for psychology students and other beginners. Retrieved from https://www.learnstatswithjamovi.com.


7.2.2 Lab


7.3 Hardware


7.3.1 Main Class

The university now requires you to possess the following:

Oddly, the university does not seem to explicitly require a microphone or speakers. I have to assume it must be implicit with the “integrated webcam.”

Anyway, I’ll include them below

  • a microphone
  • speakers (or headphones/earbuds, etc.)

Technically, no other hardware is required for the main class.


7.4 Software

7.4.1 Main Class

7.4.1.1 Online test-taking technology

For the “take-home” online exams, the main class requires the use of the Respondus LockDown Browser\(^{\dagger\dagger}\) and a webcam. The webcam can be the type that’s built into your computer or one that plugs in with a USB cable.

\(\dagger\dagger\) IMPORTANT: If you use a Google Chromebook and have no access to another computer, please contact the head instructor. There are limitations to using the Lockdown Browser with Google Chromebooks, so we will need to plan for these limitations.

7.4.1.1.1 Respondus

Watch this brief video to get a basic understanding of the LockDown Browser and the webcam feature.

7.4.1.1.1.1 Download
  • Download and install LockDown Browser from this link.
7.4.1.1.1.2 Once Installed
  • Start LockDown Browser
  • Log into Canvas
  • Navigate to the test

Note
- You won’t be able to access the exams with a standard web browser
- If this is tried, an error message will indicate that the test requires the use of LockDown Browser
- Simply start LockDown Browser and navigate back to the exam to continue


7.4.1.2 Online exam guidelines

  • When taking an online test, follow these guidelines:
    • Ensure you’re in a location where you won’t be interrupted.
    • Turn off all other devices (e.g. tablets, phones, second computers) and place them outside of your reach.
    • Before starting the test, know how much time is available for it, and also that you’ve allotted sufficient time to complete it
    • Clear your desk or workspace of all external materials not permitted - books, papers, other devices
    • Remain at your computer for the duration of the test.
    • If the computer, Wi-Fi, or location is different than what was used previously with the “Webcam Check” and “System & Network Check” in LockDown Browser, run the checks again prior to the exam.
    • To produce a good webcam video, do the following:
      • Avoid wearing baseball caps or hats with brims
      • Ensure your computer or device is on a firm surface (a desk or table)
      • Do NOT have the computer on your lap, a bed, or other surface where the device (or you) are likely to move.
      • If using a built-in webcam, avoid readjusting the tilt of the screen after the webcam setup is complete
      • Take the exam in a well-lit room, but avoid backlighting (such as sitting with your back to a window)
  • Remember that LockDown Browser will prevent you from accessing other websites or applications
    • You will be unable to exit the test until all questions are completed and submitted
7.4.1.2.1 Help
  • Several resources are available if you encounter problems with LockDown Browser:
    • The Windows and Mac versions of LockDown Browser have a “Help Center” button located on the toolbar
      • Use the “System & Network Check” to troubleshoot issues
      • If an exam requires you to use a webcam, also run the “Webcam Check” from this area
    • You can get support from Texas A&M through this link
    • Respondus has a Knowledge Base
      • Select the “Knowledge Base” link and then select “Respondus LockDown Browser” as the product
        • If your problem is with a webcam, select “Respondus Monitor” as your product
      • If you’re still unable to resolve a technical issue with LockDown Browser, go to support.respondus.com and select “Submit a Ticket”
        • Provide detailed information about your problem and what steps you took to resolve it

7.4.2 Lab

  • jamovi (freeware available for Windows, Mac, Linux, and Chromebook)
    • Install the following modules from within jamovi:
      • lsj-data - learning statistics with jamovi
      • scatr

7.5 Optional Materials


7.5.1 Main Class

We have set up a “collection” of LinkedIn Learning tutorials available to you for free from within the Howdy! portal. They correspond pretty well with much of the course material. Links will be provided in the Course Schedule below as well, but more usefully, in Canvas under the relevant sections.


7.5.2 Lab

7.5.2.1 The University Writing Center

Because this class emphasizes writing so much, we encourage you to visit the website for the University Writing Center or UWC. The UWC is a great resource for help with any stage of the writing process and offers help both online and in person. Click here for hours and locations. Click here for a 5-minute YouTube overview video, which is also on their YouTube Channel. They also have some interactive learning modulues here.


8 Policies

8.1 Main Class Policies


8.1.1 Classroom Behavior

PSYC 301 is a learning community where civility and mutual respect are crucial for success. we will be be prepared to teach the material in an animated, but professional manner. We will treat you like mature members of a learning community. Likewise, we expect that you will attend the labs, work with your research group on completing tasks in the lab, and be prepared to both learn and contribute to the course in a thoughtful manner. Let’s be nice to each other and have a great semester!


8.1.2 Grade Disputes

If you wish to dispute a grade on an assignment or exam, you must submit a written rationale (email is fine) to justify the change within 1 week of receiving your score in Canvas for exams, written papers, or lab activities. Submit the rationale to the head instructor if it’s an exam score. Otherwise, submit the rationale to your TA.


8.1.3 Cheating

Cheating in the main class will almost certainly be restricted to taking online exams.

Since the exams are formative now, it makes sense to use every precaution to make sure that cheating does not occur. To this end, you will take exams through either the Respondus Lockdown Browser, which you will need to download (for free) through Texas A&M’s Software Center, or the Honorlock system, which is an extension to the Chrome Browser. You will also need a webcam

For exams, there will two steps you need to follow before and during the exams to ensure integrity.

  • Show your photo ID
  • Record your exam with a webcam

The lockdown browser and Honorlock both have settings that can require these from you so that you don’t forget.

What we really want to make sure of is that you are you and that now one else is there helping you.

More details are below.

8.1.4 Cheating in the main class

(adapted from wording provided by Drs. Duane and Tilly McVay)

8.1.4.1 What constitutes academic misconduct?

  • During an examination
    • … looking at another student’s work or using external aids (for example, books, notes, conversation with others, internet resources, etc.) unless specifically allowed in advance by instructor
    • … acquiring answers for any assigned work or examination from any unauthorized source, including obtaining information from students who have previously taken the examination or quiz
    • … knowingly allowing another student to copy your work

8.1.4.2 Reporting an academic violation – What happens?

  • We will report the violation to AHSO, regardless of the magnitude of the violation.
  • The report is submitted online and includes the following:
    1. the details of the violation\(^{\dagger\dagger}\)
    2. an election to handle autonomously or refer to the Honor Council
    3. specification of sanctions, and
    4. student acknowledgment of acceptance/rejection of violation and/or sanction, though you have the right to appeal to the AHSO
  • Importantly, you would then be logged into the AHSO system
    • If there is a second violation, you will automatically go before the Honor Council
  • We will treat students giving unauthorized help the same as students receiving help
    • Such cases would entail the same course sanctions and reporting to AHSO

\(\dagger\dagger\) Note that we can use the records from Respondus or Honorlock (or other online proctor) as evidence in our report to AHSO.

8.2 Lab Policies


8.2.1 Cheating


Cheating in the lab usually takes the form of plagiarism. Plagiarism consists of taking the ideas, words, style, or images (i.e., intellectual products) of another person and passing them off as your own. You are committing plagiarism if you copy the work of another person and turn it in as your own, even if you have their permission. Plagiarism is one of the worst academic crimes because it undermines trust and inhibits the proper allocation of credit for intellectual products. It is the intellectual equivalent of theft.

Suspected violations will be reported to the Aggie Honor System Office. Students who plagiarize material on written assignments will at the very least receive 0 points for that assignment, but the severity of the transgression could result in penalties even more detrimental to one’s course grade, up to and including outright failure of the class altogether.

See section 8.1.4.2 above for more information on the procedures we take once cheating (plagiarism) has been identified.

8.3 University Policies

8.4 Vaccines and Face-coverings Policy

To help protect Aggieland and stop the spread of COVID-19, Texas A&M University urges students to be vaccinated and to wear masks in classrooms and all other academic facilities on campus, including labs. Doing so exemplifies the Aggie Core Values of respect, leadership, integrity, and selfless service by putting community concerns above individual preferences. COVID-19 vaccines and masking — regardless of vaccination status — have been shown to be safe and effective at reducing spread to others, infection, hospitalization, and death.


8.4.1 Attendance Policy

The university views class attendance and participation as an individual student responsibility. Students are expected to attend class and to complete all assignments.

Please refer to Student Rule 7 in its entirety for information about excused absences, including definitions, and related documentation and timelines.


8.4.2 Makeup Work Policy

Students will be excused from attending class on the day of a graded activity or when attendance contributes to a student’s grade, for the reasons stated in Student Rule 7, or other reason deemed appropriate by the instructor.

Please refer to Student Rule 7 in its entirety for information about makeup work, including definitions, and related documentation and timelines.

Absences related to Title IX of the Education Amendments of 1972 may necessitate a period of more than 30 days for make-up work, and the time frame for make-up work should be agreed upon by the student and instructor” (Student Rule 7, Section 7.4.1).

“The instructor is under no obligation to provide an opportunity for the student to make up work missed because of an unexcused absence” (Student Rule 7, Section 7.4.2).

Students who request an excused absence are expected to uphold the Aggie Honor Code and Student Conduct Code. (See Student Rule 24.)


8.4.3 Academic Integrity Statement and Policy

An Aggie does not lie, cheat or steal, or tolerate those who do.

“Texas A&M University students are responsible for authenticating all work submitted to an instructor. If asked, students must be able to produce proof that the item submitted is indeed the work of that student. Students must keep appropriate records at all times. The inability to authenticate one’s work, should the instructor request it, may be sufficient grounds to initiate an academic misconduct case” (Section 20.1.2.3, Student Rule 20).

You can learn more about the Aggie Honor System Office Rules and Procedures, academic integrity, and your rights and responsibilities at aggiehonor.tamu.edu.

NOTE: Faculty associated with the main campus in College Station should use this Academic Integrity Statement and Policy. Faculty not on the main campus should use the appropriate language and location at their site.


8.4.4 Americans with Disabilities Act (ADA) Policy

Texas A&M University is committed to providing equitable access to learning opportunities for all students. If you experience barriers to your education due to a disability or think you may have a disability, please contact Disability Resources in the Student Services Building or at (979) 845-1637 or visit disability.tamu.edu. Disabilities may include, but are not limited to attentional, learning, mental health, sensory, physical, or chronic health conditions. All students are encouraged to discuss their disability related needs with Disability Resources and their instructors as soon as possible.


8.4.5 Title IX and Statement on Limits to Confidentiality

Texas A&M University is committed to fostering a learning environment that is safe and productive for all. University policies and federal and state laws prohibit gender-based discrimination and sexual harassment, including sexual assault, sexual exploitation, domestic violence, dating violence, and stalking.

With the exception of some medical and mental health providers, all university employees (including full and part-time faculty, staff, paid graduate assistants, student workers, etc.) are Mandatory Reporters and must report to the Title IX Office if the employee experiences, observes, or becomes aware of an incident that meets the following conditions (see University Rule 08.01.01.M1):

  • The incident is reasonably believed to be discrimination or harassment.
  • The incident is alleged to have been committed by or against a person who, at the time of the incident, was (1) a student enrolled at the University or (2) an employee of the University.

Mandatory Reporters must file a report regardless of how the information comes to their attention – including but not limited to face-to-face conversations, a written class assignment or paper, class discussion, email, text, or social media post. Although Mandatory Reporters must file a report, in most instances, you will be able to control how the report is handled, including whether or not to pursue a formal investigation. The University’s goal is to make sure you are aware of the range of options available to you and to ensure access to the resources you need.

Students wishing to discuss concerns in a confidential setting are encouraged to make an appointment with Counseling and Psychological Services (CAPS).

Students can learn more about filing a report, accessing supportive resources, and navigating the Title IX investigation and resolution process on the University’s Title IX webpage.

NOTE: Faculty associated with the main campus in College Station should use this Title IX and Statement on Limits of Liability. Faculty not on the main campus should use the appropriate language and location at their site.


8.4.6 Statement on Mental Health and Wellness

Texas A&M University recognizes that mental health and wellness are critical factors that influence a student’s academic success and overall well-being. Students are encouraged to engage in proper self-care by utilizing the resources and services available from Counseling & Psychological Services (CAPS). Students who need someone to talk to can call the TAMU Helpline (979-845-2700) from 4:00 p.m. to 8:00 a.m. weekdays and 24 hours on weekends. 24-hour emergency help is also available through the National Suicide Prevention Hotline (800-273-8255) or at suicidepreventionlifeline.org.


8.5 College/Department Policies


8.5.1 Limits to Confidentiality

Texas A&M University and the Department of Psychological and Brain Sciences are committed to fostering a learning environment that is safe and productive for all. University policies and federal and state laws provide guidance for achieving such an environment. Although class materials are generally considered confidential pursuant to student record policies and laws, University employees—including instructors—cannot maintain confidentiality when it conflicts with their responsibility to report certain issues that jeopardize the health and safety of our community. As the instructor, we must report the following information to other University offices if you share it with me, even if you do not want the disclosed information to be shared:

  • Allegations of sexual assault, sexual discrimination, or sexual harassment when they involve TAMU students, faculty, or staff
  • Credible threats of harm to oneself, to others, or to university property

These reports may trigger contact from a campus official who will want to talk with you about the incident that you have shared. In many cases, it will be your decision whether or not you wish to speak with that individual.

If you would like to talk about these events in a more confidential setting, you are encouraged to make an appointment with the Student Counseling Service Students can report concerning, non-emergency behavior at Tell Somebody.


8.5.2 Respect for Diversity

To make this environment comfortable for everyone, please remember that there are many students with different experiences and needs in one room. This class does not tolerate remarks that are sexist, racist, homophobic, or otherwise ridicule people.

Respectful environment: There are a number of topics during the semester that can make some people uncomfortable. To make this environment comfortable for everyone, please remember that there are many students with different experiences and needs in one room and these diverse experiences and backgrounds are not always obvious to the casual observer. Whereas it is 100% OK to disagree with someone, you must state your disagreements about the issue (and not the other person) and in a way that is respectful (i.e., does not belittle people or groups). This class does not tolerate remarks that are sexist, racist, homophobic, or otherwise ridicule people.