schedule – STAT 218 Spring 2026

Course Content

The course content, available here, is further enriched by in-class presentations and activities. Each week, we’ll engage with the material through:

Reading assignments introducing key concepts for the unit/topic.
Followed by lectures, in-class activities, investigations or lab sessions exploring the week’s content.
Submitting weekly assignments through Canvas.

Weekly Layout

Discover the Weekly Layout — a comprehensive guide to your week’s agenda. Access

lecture slides ,
videos ,
reading materials ,
investigations
weekly assignments ,
group assignments and
due dates ,

all conveniently organized for your academic journey.

Week 1 (Apr 1 - Apr 3)

BEFORE CLASS	DURING CLASS	AFTER CLASS
Cal Poly Holiday (No class meeting)
Nothing, just come to the class!	Covering the syllabus An Introduction to Statistics, Data, Variables and Statistical Studies	The best stats you’ve ever seen Using data to better understand agriculture. Using statistics to treat chronic illnesses. NO SUBMISSION FOR TODAY!
CH 1: Introduction Section 1.2: Types of Evidence Section 2.1: Introduction to Variables FROM Samuels et al. (2016)	Lecture 2 introductory slides Investigation 1	Investigation 1 DUE DATE: Tue, Apr 07
CH 1: Introduction Section 1.2: Types of Evidence Section 2.1: Introduction to Variables Section 1.3: Random Sampling FROM Samuels et al. (2016)	Lecture Slides - Statistical Studies	Weekly Assignment Exercise 1.2.2 Exercise 1.2.4 Exercise 1.2.6 Exercise 1.3.3 and Exercise 2.1.1 DUE DATE: Tue, Apr 7

Week 2 (Apr 7 - Apr 10)

BEFORE CLASS	DURING CLASS	AFTER CLASS
Introduction to R and RStudio – Lab 1 Install R Install RStudio First Steps in R	Lab Slides - Introduction to R & RStudio	Upload the PDF file that we created today! DUE DATE: Tue, Apr 7 (literally today)
CH 2: Description of Samples and Populations Section 2.2: Frequency Distributions Section 2.3: Descriptive Statistics Section 2.6: Measures of Dispersion FROM Samuels et al. (2016)	Lecture Slides - Description of Samples and Populations Rossman & Chance Applet	Weekly Assignment Course Survey DUE DATE: Tue, Apr 14
CH 2: Description of Samples and Populations Section 2.3: Descriptive Statistics Section 2.6: Measures of Dispersion FROM Samuels et al. (2016)	Investigation 2	Investigation 2 DUE DATE: Fri, Apr 10
CH 2: Description of Samples and Populations Section 2.2: Frequency Distributions Section 2.3: Descriptive Statistics Section 2.6: Measures of Dispersion FROM Samuels et al. (2016)	Lab Slides - Descriptive Statistics - I	Lab Assignment 1 DUE DATE: Tue, Apr 14

Week 3 (Apr 14 - Apr 17)

BEFORE CLASS	DURING CLASS	AFTER CLASS
CH 1: Introduction Section 1.3: Random Sampling FROM Samuels et al. (2016)	Lecture Slides - Sampling in Statistics	Weekly Assignment Exercise 2.2.6 Exercise 2.3.3 Exercise 2.3.10 DUE DATE: Tue, Apr 21
Nothing, just come to the class! Print/Download the handout.	Sampling Distribution Handout (Word) Sampling Distribution Handout (PDF)	Review the handout we covered today!
Introduction to Confidence Intervals Nothing, just come to the class!	Lecture Slides - More on CLT and Introduction to Confidence Intervals Rossman & Chance Applet - Simulating Confidence Intervals
CH 2: Description of Samples and Populations Section 2.2: Frequency Distributions Section 2.3: Descriptive Statistics FROM Samuels et al. (2016)	Lab Slides - Descriptive Statistics - II	Lab Assignment 2 DUE DATE: Tue, Apr 21

Week 4 (Apr 21 - Apr 24)

BEFORE CLASS	DURING CLASS	AFTER CLASS
Review your Week 3 class notes!	Lecture Slides - More Confidence Intervals and Introduction to Hypothesis Testing Rossman & Chance Applet	Weekly Assignment See Canvas DUE DATE: Tue, Apr 28
CHAPTER 3 and CHAPTER 4 Section 3.1: Probability and the Life Sciences Section 3.2: Introduction to Probability Section 3.4: Density Curves Chapter 4 pp. 132- 137 FROM Samuels et al. (2016)	Lecture Slides - Introduction to Hypothesis Testing - Handout (Google Doc) Lecture Slides - Introduction to Hypothesis Testing - Handout (PDF)	No Assignment for today!
Review your notes!	Review of Week 1 - 4	No assignment for today!
Midterm 1 (In-class)

Week 5 (Apr 28 - May 1)

BEFORE CLASS	DURING CLASS	AFTER CLASS
Ch 6: Confidence Interval Section 6.3: CI for µ Section 6.4: Planning a Study to Estimate µ Section 6.5: Conditions for Validity of Estimation Methods FROM Samuels et al. (2016)	Lecture Slides - Confidence Interval for a Single Mean	No assignment for today!
Ch 6: Confidence Interval Section 6.3: CI for µ Section 6.5: Conditions for Validity of Estimation Methods FROM Samuels et al. (2016)	Investigation 3 - Sleepless Nights Part 1	Investigation 3 DUE DATE: Fri, May 1
Ch 6: Confidence Interval Section 6.3: CI for µ Section 6.5: Conditions for Validity of Estimation Methods FROM Samuels et al. (2016)	Lecture Slides - More on CI & One Sample t-Test	No Assignment for Today!
Review your Hypothesis Testing for One Mean notes!	Investigation 4 - Sleepless Nights Part 2	Investigation 4 DUE DATE: Tue, May 5

Week 6 (May 5 - May 8)

BEFORE CLASS	DURING CLASS	AFTER CLASS
CH 6: Confidence Intervals Section 6.6: Comparing two means Section 6.7: Confidence Interval for µ1 - µ2 FROM Samuels et al. (2016)	Lecture Slides - Comparing Two Means - Simulation Based Approach	No assignment for today!
Review these previous lecture slides	Investigation 5 - Dung Beetles	Investigation 5 DUE DATE: Mon, May 11
CH 6: Confidence Intervals Section 6.6: Comparing two means Section 6.7: Confidence Interval for µ1 - µ2 FROM Samuels et al. (2016)	Lecture Slides - Comparing Two Means - Theory Based Approach	No assignment for today!
None	Review of Midterm 1	No assignment for today

Week 7 (May 12 - May 15)

BEFORE CLASS	DURING CLASS	AFTER CLASS
Start studying the take-home portion of the Second Midterm. See Instructions and Paper here.
Ch 7: Inference for Numerical Data 7.1.5 One sample t-tests FROM Diez et al. (2022) CH 6: Confidence Intervals Section 6.6: Comparing two means Section 6.7: Confidence Interval for µ1 - µ2 FROM Samuels et al. (2016)	Lab Slides - Applications of t-tests	Lab Assignment 3 DUE DATE: Wed, May 13
Ch 8: Comparison of Paired Samples Section 8.1: Introduction Section 8.2: The Paired-Sample t Test and Confidence Interval Section 8.3: The Paired Design FROM Samuels et al. (2016)	Lecture Slides - The Paired Design	Weekly Assignment Week 6 & 7 Review Assignment (CANVAS) DUE DATE: Tue, May 19
Ch 7: Inference for Numerical Data 7.1.5 One sample t-tests FROM Diez et al. (2022) CH 6: Confidence Intervals Section 6.6: Comparing two means Section 6.7: Confidence Interval for µ1 - µ2 FROM Samuels et al. (2016)	Lab Slides - R Lab - Paired Sample t-test	Lab Assignment 4 DUE DATE: Tue, May 19
NO CLASS, STUDY YOUR TAKE-HOME MIDTERM

Week 8 (May 19 - May 22)

BEFORE CLASS	DURING CLASS	AFTER CLASS
Ch 6: Inference for Categorical Data Sec. 6.2 Difference of two proportions FROM Diez et al. (2022)	Lecture Slides - Difference of Two Proportions	No assignment for today!
Ch 6: Inference for Categorical Data Sec. 6.2 Difference of two proportions FROM Diez et al. (2022)	Lecture Handout - Difference of Two Proportions (Google Doc) Lecture Handout - Difference of Two Proportions (PDF)	No Assignment for today!
Review these previous lecture slides Lecture Slides - Association and Confounding Lecture Slides - Difference of Two Proportions	Investigation 6 - Do COVID vaccines work?	Investigation 6 DUE DATE: Tue, May 26
Midterm 2 (In-class)

Week 9 (May 26 - May 29)

BEFORE CLASS	DURING CLASS	AFTER CLASS
Ch 6: Inference for Categorical Data Sect. 6.3 Testing for goodness of fit using chi-square Sect. 6.4 Testing for independence in two-way tables FROM Diez et al. (2022)	Lecture Slides - Chi Square Tests	No assignment for today!
Ch 6: Inference for Categorical Data Sect. 6.3 Testing for goodness of fit using chi-square Sect. 6.4 Testing for independence in two-way tables FROM Diez et al. (2022)	Investigation 7 - Comparing Multiple Proportions	Investigation 7 DUE DATE: Fri, May 29
Ch 11: Comparing the Means of Many Independent Samples Sec. 11.1 Introduction Sec. 11.2 The Basic One-Way ANOVA Sec. 11.4 The Global F Test Sec. 11.5 Applicability of Methods FROM Samuels et al. (2016)	Lecture Slides - Introduction to One Way ANOVA	Week 9 Individual Assignment (on CANVAS) DUE DATE: Tue, Jun 2
Ch 11: Comparing the Means of Many Independent Samples Sec. 11.1 Introduction Sec. 11.2 The Basic One-Way ANOVA Sec. 11.4 The Global F Test Sec. 11.5 Applicability of Methods FROM Samuels et al. (2016)	Investigation 8 - Comparing Multiple Means	Investigation 8 DUE DATE: Tue, Jun 2

Week 10 (Jun 2 - Jun 5)

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BEFORE CLASS	DURING CLASS	AFTER CLASS
Ch 12: Linear Regression and Correlation Sec. 12.1 Introduction Sec. 12.2 The Correlation Coefficient FROM Samuels et al. (2016)	Lecture Slides - Correlation	No assignment for today
Ch 12: Linear Regression and Correlation Sec. 12.3 The Fitted Regression Line Sec. 12.4 Parametric Interpretation of Regression: The Linear Model Sec. 12.5 Statistical Inference Concerning \(\beta_1\) FROM Samuels et al. (2016)	Lecture Slides - Bivariate Regression	Week 10 Individual Assignment (on CANVAS) DUE DATE: Fri, Jun 5
Ch 12: Linear Regression and Correlation Sec. 12.1 Introduction Sec. 12.2 The Correlation Coefficient Sec. 12.3 The Fitted Regression Line Sec. 12.4 Parametric Interpretation of Regression: The Linear Model Sec. 12.5 Statistical Inference Concerning \(\beta_1\) FROM Samuels et al. (2016)	Lab Slides - Correlation & Bivariate Regression	Lab Assignment 5 DUE DATE: Fri, Jun 5
Review Session (Q&A)