Schedule and Textbooks Information


Fall 2017 Schedule and Textbook Information for STAT 501

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STAT 501 - Texbook(s) for Fall 2017

  Textbook information is not available at this time.

STAT 501 - Schedule information for Fall 2017

CRN Section Instructor Day Time Room
29235001Tadd ColverTR10:30-11:45amUNIV 019
29237002Tadd ColverTR09:00-10:15amUNIV 019

STAT 501 - Course Outline

  1. 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.

  2. Data Analysis--Relationship: scatterplots, least squares regression; outliers and influential observations; correlation; relations in categorical data, causation.

  3. Producing Data: design of experiments; design of sample surveys; the importance of randomization; sampling distributions and variability.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Analysis of Variance: model for one-way ANOVA; hypothesis testing and the ANOVA table.

Last Updated: Oct 10, 2017 11:37 AM

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