Statistical Methods and Motivations (Fall 2021 Primary Instructor)

Primary Instructor

As a primary instructor, I gave lectures and led discussions, created course syllabus, developed and designed lecture slides (21 sections) using Beamer, provided handouts (19), problem sets, posted weekly summaries (16), wrote exams (3), and quizzes (5). In addition, I set up and managed a Canvas site for the course. I made myself available to students by holding in-person office hours, staying after each class to answer questions, and conducting review sessions (3) and providing study guides (3) before each exam. I was also involved in assisting with WileyPLUS homework, grading non-WileyPLUS assignments (13), exams, and workbook problems (18). At the end of the semester, I assigned an individual final project focused on hypothesis testing based on a given dataset. Throughout the semester, I closely monitored each student’s progress and was quick to respond to their emails. I was nominated for the 2021-2022 R.L. Anderson Outstanding Teaching Award.

Textbooks

• Required Textbook:
  • Lock, “Statistics: Unlocking the Power of Data”

Course Description

Introduction to principles of statistics with emphasis on conceptual understanding. Students will articulate results of statistical description of sample data (including bivariate), application of probability distributions, confidence interval estimation and hypothesis testing to demonstrate properly contextualized analysis of real-world data.

Student Learning Outcomes

The primary goals of this course are:

• Demonstrate understanding of p-value, margins of error and confidence intervals, formal hypothesis tests through their creation or evaluation.
• Generate an/or analyze critically quantitative and graphic data summaries in their real-world contexts.
• Integrate knowledge from huge reservoir of available data and illustrate their comprehension of that knowledge through individual summarization.

Course Schedule

• Sampling Terminology - population vs sample, SRS, bias.
• Experiments and obs. studies.
• Scatterplots/Correlation.
• Regression.
• Sampling distributions - General.
• CI general setup, interpretation.
• Constructing Bootstrap CIs, 95% CI using 2*SE.
• Bootstrap CIs Using Percentiles.
• Setting up hypotheses, statistical significance.
• P-values from Randomization Distributions.
• Statistical Significance/Conclusions.
• Issues with Hypothesis Testing.
• Confidence Intervals and Hypothesis Tests.
• Hypothesis Tests Using Normal Distributions.
• Confidence Intervals Using Normal Distributions.
• Inference for Single Proportions.
• Inference for Single Proportions.
• Inference for Single Mean.
• Inference for Two Proportion.
• Inference for Two Means - Independent Samples
• Inference for Two Means - Paired Samples.
• Regression Inference.

Software

StatKey and/or Excel.