MAT 241 - Modern Statistics with Software (R)
Syllabus (Fall 2024)
Course Description: This is a fundamental course in modern-day data, data visualization, and the application of statistical techniques to analyze and make inferences from sample data. In a world where data is being constantly collected, it is necessary for individuals to be data literate, to have exposure to the power of data, and to understand as well as practice proper and ethical analyses with data. In a world where data has become abundant, rather than scarce, statistical tools are evolving. This course looks at modern statistical techniques in the age of “Big-Data”.
Students in this course should expect to use R via RStudio either using Posit.cloud or a local installation of R and RStudio if you wish. The notebooks and all required packages are pre-loaded at this Posit.cloud workspace, which can be copied once you are logged in with your own free account. Students will work through scripted workbooks outside of class meetings (more on this below) and then will get their hands dirty, working with real data during class time. Applications will vary according to student and instructor interests.
Still not quite sure what to expect? Check out this in-browser version of the Day 1 Material
Course Timeline and Notebooks
Below is a tentative timeline for our course. It includes preparatory work that should be done prior to each class meeting, a description of what to expect during a given class meeting, and assignments following each class meeting. The preparatory work consists of interactive R notebooks and is accessed via the tutorials tab of the rop-right pane in RStudio on Posit.cloud.
| Class Meeting | Before Class | During Class | After Class |
|---|---|---|---|
| 1 | Review Syllabus Create Posit.cloud account and access materials |
Introduction and What to Expect Troubleshooting Data Exploration (html, or Quarto) |
|
| 2 | 01_IntroToData |
Austin Housing Dataset (html or Quarto) | MyOpenMath HW 1 |
| 3 | 02_IntroToR |
Getting Familiar with R Austin Housing (Cont’d) Companion Slides |
|
| 4 | 03_DescriptiveNumCat |
Exploring and Describing Data Austin Housing (Cont’d) Companion Slides |
MyOpenMath HW 2 |
| 5 | 04_DataViz |
Data Visualization Austin Housing (Cont’d) Companion Slides |
|
| 6 | 05_DiscreteDistributions |
Probabilities and Simulation Doris and Buzz (html or Quarto) or Companion Slides |
|
| 7 | 06_NormalDistributions |
Probabilities and Normal Distributions MyOpenMath Problems (html or Quarto) or Companion Slides |
MyOpenMath HW 4 |
| 8 | Discrete Distributions Lab 07_DiscreteDistributionsLab |
||
| 9 | Normal Distributions Lab 08_NormalDistributionLab |
||
| 10 | Exam I, Part I (Group) | ||
| 11 | Exam I, Part II (Individual) | ||
| 12 | 09_FoundationsForInference |
More on the Sampling Distribution 10_IntroInferenceLab, or Companion Slides |
MyOpenMath HW 5 |
| 13 | 11_HTandCIprop |
Hypothesis Tests and Confidence Intervals for Proportions Companion Slides |
|
| 14 | 12_InferencePractice |
Inference for Categorical Data (html or Quarto) Companion Slides |
MyOpenMath HW 6 |
| 15 | Inference for Categorical Data Lab 13_InferenceCategoricalLab |
||
| 16 | 14_ChiSquare |
Inference for More than Two Proportions (html or Quarto) or Companion Slides |
MyOpenMath HW 7 |
| 17 | 15_HTandCInum |
Hypothesis Tests and Confidence Intervals for One or Two Means (html or Quarto) or Companion Slides |
|
| 18 | Additional Inference Practice, Day I 16_InferencePractice Practice Problems |
||
| 19 | Additional Inference Practice, Day II 16_InferencePractice (Cont’d) Practice Problems Two Examples and Discussion on Error Types |
MyOpenMath HW 8 | |
| 20 | Additional Inference Practice, Day III 16_InferencePractice (Cont’d) Practice Problems “Answer” Key |
||
| 21 | Inference for Numerical Data Lab 17_InferenceNumericalLab Slides on Reading Software Output |
MyOpenMath HW 9 | |
| 22 | 18_ANOVA |
Inference for More than Two Means (html or Quarto) | |
| 23 | Exam II, Part I (Group) | ||
| 24 | Exam II, Part II (Individual) | ||
| 25 | Linear Regression Lab 19_LinearRegression |
MyOpenMath HW 10 | |
| 26 | Review | ||
| 27 | Final Exam, Part I | ||
| 28 | Final Exam, Part II (Optional) |