Introductory Statistics

Previous Slide Decks

This holds links to slide decks and videos from a previous incarnation of the course. The topics are similar enough that if you miss class, then these slide decks (and videos) wil keep you from falling too far behind.

To be clear, these are not the slide decks I use in the course this term. They are from Spring 2020. They are useful for you, however, if you become sick and need to hear a lecture over the material.

Module 1: Gathering Your Data
Getting Started: Statistics is the study of reality
Deck #1		HLS §1.1
Data Classification: What information does the variable contain?
Deck #2		HLS §1.2
The Process of a Statistical Study: The scientific method again rears its head
Deck #3		HLS §1.3
How to Critique a Published Study: Not all published articles are created equaly
Deck #4		HLS §1.4
Module 2: Knowing Your Data
Frequency Distributions: Illustrating discrete distributions
Deck #5		HLS §2.1
Graphical Displays of Data: How to summarize the data
Deck #6		HLS §2.2
Analyzing Graphs: How do I tell the story in pictures?
Deck #7		HLS §2.3
Measures of Center: Summarizing data with one number
Deck #8	R4S § 4.2	HLS §3.1
Measures of Dispersion: A second statistic on the data
Deck #9	R4S § 4.3	HLS §3.2
Measures of Relative Position: Standardizing variables
Deck #10		HLS §3.3
Module 3: Probability Theory
Introduction to Probability: What is this monster?
Deck #11		HLS §4.1
Addition Rules for Probability: Unions and sums
Deck #12		HLS §4.2
Multiplication Rules for Probability: Independence, Bayes, and conditional probability
Deck #13		HLS §4.3
Combinations and Permutations: Determining what counts
Deck #14		HLS §4.4
Combining Probability and Counting Techniques: Bringing it all together
Deck #15		HLS §4.5
An Introduction to Discrete Distributions: The foundations of half of probability
Deck #16	R4S § A.1	HLS §5.1
The Bernoulli and Binomial Distributions: Counting successful trials
Deck #17	R4S § A.2, A.3	HLS §5.2
The Poisson Distribution: Counting over time or space
Deck #18	R4S § A.7	HLS §5.3
The Hypergeometric Distribution: Countig scefl r
Deck #19	R4S § A.4	HLS §5.4
The Uniform Distribution: The other half
Deck #20	R4S § B.1, B.2
The Exponential Distribution: Time until success
Deck #21	R4S § B.5
The Normal Distribution: Gauss gave it to us
Deck #22	R4S § B.3, C.1, C.2	HLS §6.1–4
Estimating the Binomial Distribution: Why do this now?
Deck #23	R4S § C.3	HLS §6.5
Module 4: Introductory Inference
The Central Limit Theorem: The cornerstone of statistics
Deck #24	R4S § C.3	HLS §7.1
The Distribution of the Sample Mean: An important application of the CLT
Deck #25	R4S § C.3	HLS §7.2
The Distribution of the Sample Proportion: Recalling §6.5
Deck #26	R4S § C.3	HLS §7.3
The Theory of the Confidence Interval: Estimating the parameter
Deck #27	R4S Ch. 4	HLS §8.1–
Confidence Intervals in R: Using the computer to make life easier
Deck #28	R4S Ch. 5	HLS §9.1–
The Theory of Hypothesis Testing: Testing claims about reality
Deck #29	R4S Ch. 4	HLS §10.1
Hypothesis Testing in R: Using the computer to make life easier
Deck #30	R4S Ch. 5	HLS §10.2–
Module 5: Advanced Inference
Handling Proportions: One and two populations
Deck #31	R4S § 8.1, 8.2	HLS §10.4
Matching a discrete distribution: Chi-square Goodness-of-Fit test
Deck #32		HLS §10.6
Categorical Independence: Chi-square test of independence
Deck #33		HLS §10.7
ANOVA: Comparing multiple means
Deck #34	R4S § 7.1, 7.2	HLS §11.6
Beyond ANOVA: Which is different?
Deck #35	R4S § 7.3–7.5
Correlation: Is there a relationship?
Deck #36	R4S § 12.1	HLS §12.1
Linear Regression: What is that relationship?
Deck #37	R4S § 12.2–	HLS §12.2–
Course Summation
Introductory Statistics: How Far We’ve Come