Schedule and Textbooks Information
Fall 2021 Schedule and Textbook Information for STAT 501
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STAT 501 - Textbook(s) for Fall 2021
| CRN | Title | Author | ISBN | Version | Req/Opt |
|---|---|---|---|---|---|
| 26012 | Introduction to the Practice of Statistics | David S. Moore,George P. McCabe,Bruce A. Craig | 9781319013387 | 9th | Y |
STAT 501 - Schedule information for Fall 2021
| CRN | Section | Instructor | Day | Time | Room |
|---|---|---|---|---|---|
| 26012 | 002 | Yuan Qu | TR | 10:30-11:45am | LILY G420 |
STAT 501 - Course Outline
- Data Analysis--Distributions: graphical and numerical methods for looking at data including stemplots, histograms, time plots, median, mean, quartiles, interquartile range, boxplots, standard deviation; normal distributions as models for real data; normal distribution calculations and normal quantile plots.
- Data Analysis--Relationship: scatterplots, least squares regression; outliers and influential observations; correlation; relations in categorical data, causation.
- Producing Data: design of experiments; design of sample surveys; the importance of randomization; sampling distributions and variability.
- Sampling Distributions: Informal probability; counts and proportions--binomial distributions; normal approximation to the binomial; the distribution of a sample mean, law of large numbers and central limit theorem.
- Introduction to Inference: confidence intervals; choice of sample size for a desired margin of error; tests of significance; P-values and tests with fixed significance level; use and abuse of tests.
- Inference for Distributions: one-sample confidence intervals and tests based on t distributions; paired data; robustness of the t procedures; power of the t test; two-sample t confidence intervals and tests; inference for standard deviations.
- Inference for Count Data: confidence intervals and tests for a single proportion; choosing the sample size; confidence intervals and tests for comparing two proportions; chi-square test for two-way contingency tables.
- Inference For Regression: statistical model for simple linear regression; confidence intervals and tests for regression coefficients; confidence intervals for mean response; prediction intervals for a future observation; analysis of variance table for regression.
- Analysis of Variance: model for one-way ANOVA; hypothesis testing and the ANOVA table.