Stat21

Stat 21: Introduction to Statistical Methods 2

Here is an example syllabus and calendar.

This is the second in a series of introductory, undergraduate statistics courses. The course is an application-focused introduction to statistical modeling. For this course, students are required to use RStudio and the topics covered can be broken into three units. Unit 1 introduces RStudio and simple linear regression (SLR), Unit 2 introduces multiple linear regression (MLR), and Unit 3 explores ethical statistical modeling practices and analysis of variance (ANOVA) models.

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Review material

• Normal random variables

• The Central Limit Theorem and sampling distributions

• Inference for a single population proportion

• Simulation study with confidence intervals

• Inference for the difference between two population proportions

• Inference for a single population mean

• Inference for the difference between two population means

• Probability and conditional probability

• Chi-square goodness of fit procedure

• More chi-square procedures

Unit 1

Class notes

• Importing and visualizing data with RStudio

• Simple linear regression

• Understanding the coefficient of determination

• Inference with SLR models

• Estimating the error variance

• Residual analysis in R

Homework and in-class worksheets

• Homework 1

• Week 2 worksheet

• Homework 2

• Week 3 worksheet

• Homework 3

• Week 4 worksheet

• Week 4 SLR worksheet

Unit 2

Class notes

• Multiple linear regression and and example

• Comparing SLR and MLR

• Selecting predictors and identifing unsual data points

• MLR additional topics

• Adjusted R-squared

• Categorical predictors

• Defining and detecting multicollinearity

• MLR interpretation and effect sizes

• Defining and interpreting interaction terms

Homework and in-class worksheets

• Week 5 worksheet

• Homework 4

• Week 7 worksheet

• Homework 5

• Homework 6

• Week 9 worksheet

• Homework 7

Unit 3

Class notes

• Residual analysis for regression models

• Simpson’s paradox

• Ethical statistical modeling

• ANOVA notation

• Multiple comparisons

Homework and in-class worksheets

• Homework 8

• Homework 9

• Week 13 worksheet

• Homework 10

Other assessment items

Quizzes

• Quiz 1

• Quiz 2

• Quiz 3

Final project

Overview and rubric

As you can see in the link above, the final project has several components. Below are some helpful documents for each of the different project parts.

• Project proposal guidelines

• R Markdown template for report with tips on writing a .bib file and a sample .bib file

• Rubric for poster and oral presentation

• Poster guidelines and a short paper on how to make an academic poster.

• Peer evaluation form and peer evaluation rubric

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