March 7, 2005
- Descriptive Data Analysis
- Why Do we Need Statistics? Overview of Descriptive or Exploratory Data Analysis
- Type and Role of Variables in Studies and Experiments
- Visualizing and Summarizing Data: The Concept of a Distribution
- Characterizing Distributions with Numerical and Graphical Tools: mean, median, standard deviation, standard error, histogram, Box-plot, etc.
- Exploring the Relationship between Two variables: Scatter Plots, Correlation Coefficients, Frequency Tables
- Statistical Inference or Statistical Testing
- Overview: What is Statistical Inference?
- Statistical Inference with Hypothesis Testing: null and alternative hypotheses, one-tailed vs. two-tailed tests, test statistics, p-value, statistical significance, decision rules
- The Concept of Risk and Power: risks involved, type I and II errors, confidence level and power of test
- Statistical Inference with Confidence Intervals: how it works, when to use it
- Equivalence of the Hypothesis Testing and the Confidence Interval Approaches
- Statistical Inference for a Single Sample or Group: Hypothesis Testing vs Confidence Interval Approach