Topics List Exam 1

Statistical framework (parameter vs statistic)

Quantitative vs Categorical variables

What is a distribution?

• What values?
• How frequently?

Data visualizations

• Explanatory/response variables
• Univariate plots
• Bivariate plots
• Which plots associated with which variable types
• Which bar chart appropriate for conditional proportions

Numerical summaries

• Measures of centrality
• Measures of spread
• Percentiles
• When is each useful?

Tables

• Conditional statistics (row/column/total)
• Associate plots with tables
• Use quantitative variable as categorical (i.e., enrollment as large or small)

Study Design

• Experiment vs Observational study
• prospective vs retrospective
• representative samples
  • random sampling
  • generalization
• random assignment
  • causal relationships
• census
• biases
  • response
  • non-response
  • sampling
• intended vs actual population
• label parts of experiment
  • experimental units
  • factors / levels / treatments

Probability Rules

Practice: Look over and understand the probabilities lab. Questions will be mostly extremely similar to the labs

• Notation P()
• Disjoint events
• Conditional Probabilities
• How to check for Independence
• Algebra
  • Complement
  • Additive Rule
  • Multiplicative Rule
• Get probabilities from Tables
• Calculate Odds
• Odds-Ratio
  • calculate
  • Interpret
  • association?
• Risk