Objective:
The objective of this course is to provide a comprehensive overview of core concepts in Statistics. Emphasis is placed on the foundations of statistics; probability; correlation and regression; sampling distributions; and inferential statistics.
Learning Outcomes:
- describe data types and levels of measurement including sample vs. population, and distribution
- understand random sampling, and the importance of randomness
- describe the distribution of a numeric variable by its center and spread
- represent numeric variable distributions graphically by dot plot, stem-and-leaf plot, box-and-whisker plot, and histogram
- discuss the center and spread of the distribution of a numeric variable
- define the normal distribution of a variable and calculate normal probabilities
- construct and analyze a scatter plot for a set of bivariate data
- calculate the regression model for a set of bivariate data and use it to make predictions
- calculate the probability of simple and compound events
- use a variety of probability distributions to calculate the probability of an event
- construct one and two sample confidence intervals for population means or proportions
- conduct one and two sample hypothesis tests for population means or proportions
- understand errors in hypothesis testing and their causes
- conduct Chi-square tests for uniformity of univariate data or independence of two categorical variables
- compare multiple population means using an ANOVA test; analyze a randomized block experiment with an F-test
General Course Topics:
- Collecting and interpreting data
- Numerical methods for describing data
- Normal distributions
- Bivariate data
- Linear regression
- Non-linear bivariate data
- Probability
- Probability distributions
- Sampling distributions
- Inferential statistics using a single sample
- Inferential statistics with multiple samples