Instructor: Dr. Alan T. Arnholt
Office: Walker Hall 237
Student Help Hours: 10:30-11:30 am M-R, and by appointment

Make an appointment to see me by clicking here.

Course Description:

This course provides an overview of modern statistical data analysis. Programming with data, including simulations and bootstrapping, will be an integral part of the course. Techniques for parsing univariate and multivariate data sets will be examined. Coverage of probability, random variables, standard probability distributions and statistical sampling distributions will be sufficient to prepare the student for statistical inference. Inferential topics will include parameter estimation, hypothesis testing for proportions, means and medians, goodness of fit tests, and tests for independence. Standard and computationally intensive regression techniques may also be covered. (NUMERICAL DATA; COMPUTER) — Prerequisite: MAT 1110

Course Objectives:

  1. Students will learn how to use a reproducible research work flow.
  2. Students will improve their technology expertise.
  3. Students will learn to work with large data sets.
  4. Students will learn to create and present graphs for both univariate and multivariate data.
  5. Students will learn how to construct and test hypotheses using both classical and randomization approaches.
  6. Students will learn how to construct confidence intervals using both classical and bootstrap approaches.
  7. Students will learn how to generate random and simple random samples and their relationships to permutation and bootstrap distributions.
  8. Students will learn how to work with named sampling distributions (t, F, binomial, chi-square, and normal).
  9. Students will learn the scope of inferential conclusions for numerous scenarios (experiments, observational studies, etc.).

Course Texts:

Course Grading & Assessment:

The only way to learn statistics is to DO statistics, which includes using statistical software. Reading the textbook, learning the language, and practicing exercises using real data are critical to your learning and success. Class activities and assessments have been structured with these principles in mind.

You should read assigned textbook content and read/watch supplemental materials prior to coming to class. It will be easier to participate if you acquire some familiarity with the vocabulary and methods before we start to discuss and use them. You must “speak the language” (both statistics and R) to demonstrate your knowledge effectively.

Appalachian students are expected to make intensive engagement with courses their first priority. Practically speaking, students should spend approximately 2-3 hours on coursework outside of class for every hour they spend in class. For this four-hour course, you you should anticipate 8-12 hours per week of outside work.

How To Get Unstuck

Well constructed questions will elicit answers more rapidly than poorly constructed questions. This video provides some background on asking questions. This stackoverflow thread details how to create a minimal R reproducible example. Please read How To Ask Questions The Smart Way by Eric Raymond and Rick Moen and heed their advice.

University Policies

This course conforms with all Appalachian State University policies with respect to face coverings, academic integrity, disability services, class attendance, and student engagement. The details of the policies may be found at https://academicaffairs.appstate.edu/resources/syllabi-policy-and-statement-information. Please pay particular attention to the student engagement statement.

Computers and Software

This course will use the RStudio server (https://mathr.math.appstate.edu/) that has the programs listed below and more installed.

You must have an active internet connection and be registered in the course to access the server. To access the server, point any web browser to https://mathr.math.appstate.edu/. Use your Appstate Username and Password to access the server. A screen shot of the RStudio server is shown below.

If you have problems with your Appstate Username or Password visit IT Support Services or call 262-6266.

Required Technology

Note: All technology used in the class is either open source (free) or will be accessible to students enrolled in the course for no cost.

Assignments

The CoursePacing guide has all course assignments and due dates.