Weekly Overview

While the class is generally organized by calendar week, sometimes we will cover two topics in a week or one topic will span multiple weeks.

Due dates are displayed on the calendar only. Consider subscribing to this Google calendar and stay up to date!

Date Topic Details Reading HW
Week 1
08/22 Welcome Introduction to the Class and your materials Syllabus
Help page
PMA6 Ch 2
HW00 Getting Setup
08/22 Data architecture Data entry, spreadsheets, metadata, codebooks Tidy data principles (Optional) HW01 Data Entry
08/24 Project Stage 1: Choosing your topic Choosing project research data
Week 2
08/29 Formulating research questions Asking questions is easy. Asking answerable questions is more difficult. How to Write an Effective Research Question HW02 RQ Formulation
08/31 Preparing data for analysis Where an inordinate amount of time is spent PMA6 Ch 3
Project Structure by Danielle Navarro
HW03 Data Management
Week 3
09/05 Labor Day. No Class
09/07 Data wrangling Keep coding, coding, coding, keep them fingers flowing, keep them data scrolling, Compile!
Week 4
09/12 Describing distributions of data Visualizing your data is the first line of defense against bad data PMA6 Ch 4
ASCN Ch 2.3
HW04 Univariate Graphing
09/14 Project Stage 2: Introduce your research question and variables of interest Poster prep Stage 2
Week 5
09/19 Describing relationships between two variables First step in investigating a question about an association PMA6 Ch 4
ASCN Ch 2.4
HW05 Graphing Relationships
Week 6
09/26 Best practices in Data Visualization Just because you can add it to a graph, doesn’t mean you should. PMA6 Ch 4.6
09/28 Project Stage 3: Exploratory Data Analysis Poster prep Stage 3
Week 7
10/03 Study Design How did the data come to be? IMS - Chapter 2
10/05 Foundations for Inference If all else fails, use “significant at p>.05 level” and hope no one notices. IMS - Chapter 13.1-13.3 and IMS Chapter 11-11.1 Quiz: Quantifying Uncertainty
Quiz: Foundations for Inference
Week 8
10/10 Foundations for Inference cont. Inference with Mathematical Models
10/12 Modeling Bivariate relationships Choosing appropriate analysis, T-tests for difference in means ASCN Ch 5 IMS - Chapter 20](https://openintro-ims.netlify.app/inference-two-means.html) HW06 Bivariate Modeling
Week 9
10/17 ANOVA & Kruskill Wallas IMS - Chapter 22 Quiz: T-test & ANOVA
10/19 Chi-Square & Fishers Exact Test Quiz: Chi-Square
Week 10
10/24 Correlation
10/24 Linear Modeling Everything is a linear model. PMA6 Ch 7
IMS Ch 24
Quiz: Regression Modeling
10/26 Project Stage 4: Bivariate Inference Poster prep Stage 4
Week 11
10/31 Moderation and Stratification Identifing different trends within subgroups ASCN Ch 8 HW 07 Moderation Quiz: Moderation
Week 12
11/07 Multiple Regression, Confounding Because life isn’t bivariate PMA6 Ch 8 ASCN Ch 9 HW08 Multiple Regression
11/09 Categorical Predictors PMA6 Ch 10.3 ASCN 10.1, 10.2
Week 13
11/14 Generalized Linear Models Modeling binary and log transformed outcomes. PMA6 Ch 12 ASCN 11 Quiz: Multiple Regression
Week 14
11/28 Model Building Part science, part art PMA6 8.11, 9 ASCN Ch 10
11/28 Project Stage 5: Multivariable Analysis & Conclusions Poster prep Stage 5
11/30 Assessing Model Fit
Week 15
12/05 Develop Research Poster Poster Guidelines
12/07 Other types of models
12/12 Poster Presentation Monday 6pm-8pm.
12/16 Final Exam Due Friday 12/16 EOD