Applied Statistical Data Analysis and Inference

DSC 152, Fall 2026 at UC San Diego

All course communications should be posted on Piazza (Piazza is also accessible through Canvas); please direct all questions you have during the quarter either as a public post or to “instructors & TAs” there.

Next to each lecture below, “code” is the .Rmd file that makes the slides, and “write” is the pdf that will (more or less) be what I project in class, and that you can either print or download to take notes on. You can ignore the “code” file unless you are curious about how anything in the slides was created. Note: if you want to open it in a new tab, you can right-click and select “Open link in new tab” there; (I couldn’t figure out how to make it automatically open in a new tab with a left-click in this website theme).

Week 1 – Background, Basic Type I Error Rate Estimation

Mon Sep 28

DISC 1 Getting Started with R and R Markdown

code Discussion R code

Tue Sep 29

LEC 1 Introduction and Background   

SPA 2-3

Thu Oct 1

LEC 2 Type I Error Estimation with the t-Test   

MD 9.5

Fri Oct 2

LAB 1 Introduction to R

Week 2 – Type I Error Rate and Power

Mon Oct 5

DISC 2 Simulations in R

Tue Oct 6

LEC 3 One sample nonparametric tests and Type I Errors   

PS 11

Thu Oct 8

LEC 4 One sample tests and power

DHVS 23

Fri Oct 9

LAB 2 Type I Error Rate and Power

Week 3 – Effect Size and A/B Testing

Mon Oct 12

DISC 3 tidyverse basics (dplyr, ggplot2, etc)

Tue Oct 13

LEC 5 Statistical Significance vs. Effect Size   

Forbes, Guardian

Thu Oct 15

LEC 6 A/B Testing Principles and t-Test vs. Permutation Test

Jalapic, Medium, data36, Unbounce

HW 1 One Sample Type I Errors and Power

Fri Oct 16

LAB 3 Effect Size, A/B Testing

Week 4 – Multiple Linear Regression

Mon Oct 19

MIDTERM 1 Midterm 1 covers Lectures 1-5

Tue Oct 20

LEC 7 Statistical Inference for Simple Linear Regression

MD 10, SPA 6.12-6.13

Thu Oct 22

LEC 8 Statistical Inference for Multiple Linear Regression

HRM 4.3

SUR Mid-Quarter Survey

Fri Oct 23

LAB 4 Type I Error rates and power in Regression

Week 5 – Interaction

Mon Oct 26

DISC 4 HW1 and Midterm 1 review

Tue Oct 27

LEC 9 Model Diagnostics in Regression

HRM 4.5

Thu Oct 29

LEC 10 Categorical Predictor Variables

HRM 4.4.3

Fri Oct 30

LAB 5 Model Diagnostics, Dummy Variables

Week 6 – Model Selection, Logistic Regression

Mon Nov 2

DISC 5 Extra Office Hours

Tue Nov 3

LEC 11 Interaction Terms: Interpretation and Inference

HRM 4.6.1

Thu Nov 5

LEC 12 Interaction Terms: Inference and Diagnostics

HW 2 Inference in Regression

Fri Nov 6

LAB 6 Interaction Terms

Week 7 – Transformations, Model Selection, Logistic Regression

Mon Nov 9

MIDTERM 2 Midterm 2 covers Lectures 6-11

Tue Nov 10

LEC 13 Transformations of Variables

IS 6.15, 6.16

Thu Nov 12

LEC 14 Pitfalls of Mixing Model Selection with Inference

Berk 2013

Fri Nov 13

LAB 7 Transformations, Model Selection and Inference

Week 8 – Logistic Regression

Mon Nov 16

DISC 6 HW2 and Midterm 2 review

Tue Nov 17

LEC 15 Introduction to Logistic Regression

IS 8, HRM 5

Thu Nov 19

LEC 16 Statistical Inference for Logistic Regression

IS 8, HRM 5

Fri Nov 20

LAB 8 Logistic Regression

Week 9 – Time Series

Mon Nov 23

DISC 7 Extra Office Hours

Tue Nov 24

LEC 17 Introduction to Time Series

TSR 4-6

Week 10 – Time Series

Mon Nov 30

LAB 9 Poker and Slot Machines: Model Selection and other considerations

Tue Dec 1

LEC 18 Time Series Regression

TSR 8-9

HW 3 Logistic Regression, Interaction Terms, Model Selection

Thu Dec 3

LEC 19 Time Series Models

RC 14.13-14.20

SUR SETs (due 8AM)

Thu Dec 10

Final Exam (3-6pm)

EXAM Final Exam (3-6pm)