Chapters show a more natural logical flow, and topics covered reflect current business statistical practice. There is new material on random sampling, stem and leaf plots, confidence intervals, hypothesis testing, estimation, correlation, and formulation of general linear models for fitting data.
Table of Contents
The Relationship Between Sampling and Statistics.
Displaying Sample Data.
Descriptive Sample Statistics.
Probability, Populations, and Random Variables.
Some Useful Discrete and Continuous Distributions.
Estimation (One Sample).
Two Related Examples (Matched Pairs).
Estimation and Hypothesis Testing with Two Independent Samples.
Time Series Analysis.
Formulating General Linear Models for Fitting Data.
Multiple Linear Regression.
Analysis of Variance of One-Factor Experiments.
Analysis of Variance of Two-Factor Experiments.
Other Useful Topics in Experiment Design.
Decision Theory Under Uncertainty.
Decision Theory with Sample Information.