Advanced Experimental Design & Statistical Analysis

Instructor Information

• Instructor: Dr. Leah Carver (Assistant Professor of Psychology)
• Email: lcarver@university.alkimi.ai
• Office: Lovell Hall 162
• Office Hours:
  • Tuesday & Friday: 1:00–2:30 p.m. (In person, Lovell Hall 162)
  • Monday: 9:00–10:00 a.m. (Virtual via Zoom; link posted in Canvas)
  • Also available by appointment.

Course Description

Factorial and repeated-measures designs, analysis of variance and covariance, multiple regression, mediation and moderation, power analysis, and reproducible analysis in R for behavioral research. PSYC 380 provides advanced methodological and statistical training for behavioral science majors preparing for graduate study or empirical research careers. Emphasizing open science and reproducible workflow practices, students formulate complex experimental and quasi-experimental designs and conduct sophisticated hypothesis testing using R and R Markdown. Core analytical topics include factorial analysis of variance (ANOVA), repeated-measures and mixed ANOVA, analysis of covariance (ANCOVA), multiple linear regression, mediation and moderation models, statistical power estimation, effect size reporting, and nonparametric alternatives.

Prerequisites

PSYC 205 and STAT 205.

Measurable Student Learning Outcomes

Upon successful completion of PSYC 380, students will be able to:

1. Implement Reproducible Data Workflows in R: Write clean, annotated R scripts and compile R Markdown reports conforming to open-science standards and APA 7th edition formatting.
2. Design and Analyze Factorial Experimental Designs: Compute main effects, interaction contrasts, and simple effects for between-subjects, repeated-measures, and mixed-model ANOVA designs.
3. Execute Multiple Regression and Moderation Models: Test hierarchical multiple regression models, evaluate multicollinearity and residual assumptions, and probe interactions using spotlight and floodlight analysis.
4. Conduct Statistical Mediation and Path Analyses: Estimate direct, indirect, and total effects using bootstrapping techniques in R to evaluate psychological mediation mechanisms.
5. Perform A Priori and Post Hoc Power Analyses: Calculate required sample sizes and statistical power using G*Power and R packages for diverse experimental effect sizes.
6. Interpret and Report Statistical Findings: Synthesize complex statistical findings into clear, APA-compliant results sections complete with confidence intervals, effect sizes, and data visualizations.

Required Course Materials & Approximate Costs

1. Field, Andy, Jeremy Miles, and Zoë Field. Discovering Statistics Using R. SAGE Publications, 2012. Approx. $50 for digital rental; approx. $85 for print purchase.
2. Navarro, Danielle. Learning Statistics with R: A Tutorial for Psychology Students and Other Beginners. Free open-access digital edition. Free.
3. R (v4.3+) and RStudio Desktop development environment. Free open-source software.
4. Total estimated cost: $0 to $85.

Generative AI Policy (AI Level 2: AI Permitted with Disclosure for Specified Tasks)

In accordance with Alkimi University Academic Policies (Student Handbook §5.8), PSYC 380 operates under AI Level 2.

• What is permitted: You may use AI tools to troubleshoot R syntax errors, explain statistical package error messages (e.g., from car, lme4, or mediation), generate practice datasets, and refine R Markdown documentation formatting.
• What is prohibited: You may not submit AI-generated statistical interpretation text, automated data analysis write-ups, or unverified R code. The use of generative AI tools is strictly prohibited during exams and in-class data analysis challenges.
• Disclosure: For each empirical problem set and the reproducible research project, include an AI disclosure appendix specifying which tools were consulted, prompts entered, and how you verified the statistical output, or state that no AI was used.

Grading Components and Weights

• Midterm Exam 1: 15% (In class, Thursday, September 24)
• Midterm Exam 2: 15% (In class, Thursday, October 29)
• Weekly R Problem Sets & Reproducible Scripts: 25% (Due Fridays at 11:59 p.m. in Canvas (weeks 2–13; lowest dropped))
• Reproducible Empirical Research Project: 20% (Due Friday, November 20 at 11:59 p.m.)
• In-Class Data Analysis Challenges: 5% (Canvas and R coding checks administered alternate Thursdays; lowest dropped)
• Final Comprehensive Examination: 20% (Thursday, December 17, 2026, 1:00–3:00 p.m.)

Grading Scale (Alkimi University Standard)

• A: 93–100% | A-: 90–92%
• B+: 87–89% | B: 83–86% | B-: 80–82%
• C+: 77–79% | C: 73–76% | C-: 70–72%
• D+: 67–69% | D: 60–66% | F: Below 60%
• Extra credit: Students can earn up to 2% extra credit by participating as a research subject in university-approved psychology experiments via SONA Systems or by attending designated psychology research colloquia.

Course Schedule (Fall 2026)

Course Policies

Attendance Policy

Mastering advanced statistical analysis in R requires active, hands-on computer lab participation during class sessions. If an illness or university-approved absence arises, email Dr. Carver in advance. More than three unexcused absences will negatively affect your final course grade. Students who miss the first two class meetings without notifying the instructor may be dropped. Students may miss class for religious observance without penalty if they notify the instructor in writing within the first two weeks of the semester (by Wednesday, September 9, 2026). Absences for university-sponsored activities (athletics, performances, conferences) are excused with a letter from the sponsoring office at least one week in advance.

Late Work Policy

R problem sets submitted after the Friday deadline lose 10% per day and will not be accepted more than three days late. Complete solution scripts are posted after that window. The single lowest weekly problem set score is automatically dropped at the end of the semester.

Final Exam Policy

The final examination (Thursday, December 17, 2026, 1:00–3:00 p.m.) is scheduled by the University Registrar and can't be moved without the Dean's written approval (Faculty Handbook §5.5). A student with three or more final exams on the same calendar day may reschedule one of them. Requests go to the instructor of the middle exam by the last day of classes. For this term, send the request by Wednesday, December 9, 2026 (Student Handbook §6.4).