Introduction to Statistics: Understanding the Methods Section (On-Demand)

The goal of this course is to improve your ability to thoroughly read and critically appraise the methods sections of scientific literature. The focus will be on understanding when each technique is appropriate and interpreting written methods and results in scientific literature. For each technique, you will gain an understanding of when to use a given approach, what assumptions it has, and the interpretation of the associated statistics.

Across 5 modules, you will be systematically introduced to the most common statistical techniques, along with articles that use those techniques so we can see the techniques in action in the wild. No previous experience with statistics or coding is required or expected.

Resource URL: https://www.nnlm.gov/training/class-catalog/introduction-statistics-understanding-methods-section-demand

Learning Objectives:

1. Summarize the differences between various descriptive statistics and describe when it is appropriate to use each.
2. Develop understanding of statistical inference, why we need to use a sample to learn about a population, and how we infer from a sample to a population.
3. Define a p-value, describe its drawbacks, and list some alternatives.
4. Identify scenarios where each statistical test is appropriate (t-test, ANOVA, linear regression, chi-square, logistic regression, survival analysis, Poisson regression).
5. Describe the assumptions of each statistical test (t-test, ANOVA, linear regression, chi-square, logistic regression, survival analysis, Poisson regression).
6. List common alternatives used when assumptions are not met.

Agenda

Lesson 1: Introduction & Descriptive Statistics
1.1 Video Lectures
1.2 Descriptive Statistics Knowledge Check
1.3 Hypothesis Testing Knowledge Check
1.4 Sampling Distribution Activity

Lesson 2: Two-Sample Tests & ANOVA
2.1 Video Lectures
2.2 Comparing Group Means Comprehension Check
2.3 Experimental Design Matching Assignment

Lesson 3: Linear Regression
3.1 Video Lectures
3.2 Linear Regression Comprehension Check
3.3 Design Matching Knowledge Check

Lesson 4: Analysis of Categorial Variables
4.1 Video Lectures
4.2 Logistic Regression Comprehension Check
4.3 Experimental Design Matching Assignment

Lesson 5: Other Common Statistical Tests
5.1 Video Lectures
5.2 Hypothesis Testing Knowledge Check
5.3 Experimental Designs Matching Assignment

MLA CE Credits: 10