Statistics : informed decisions using data

✍ Scribed by Michael Sullivan, III

• Publisher: Pearson
• Year: 2013
• Tongue: English
• Leaves: 968
• Edition: 4ed.
• Category: Library

✦ Synopsis

Michael Sullivan’s Statistics: Informed Decisions Using Data, Fourth Edition, connects statistical concepts to students’ lives, helping them to think critically, become informed consumers, and make better decisions. Throughout the book, “Putting It Together” features help students visualize the relationships among various statistical concepts. This feature extends to the exercises, providing a consistent vision of the bigger picture of statistics.

 

This book follows the Guidelines for Assessment and Instruction in Statistics Education (GAISE), as recommended by the American Statistical Association, and emphasizes statistical literacy, use of real data and technology, conceptual understanding, and active learning.

 

✦ Table of Contents

Content: pt. 1. Getting the information you need --
ch. 1. Data collection --
Introduction to the practice of statistics --
Observational studies versus designed experiments --
Simple random sampling --Effective sampling methods --
Bias in sampling --
Design of experiments --
pt. 2. Descriptive statistics --
ch. 2. Organizing and summarizing data --
Organizing qualitative data --
Organizing quantitative data : the popular displays --
Additional displays of quantitative data --
Graphical misrepresentations of data --
ch. 3. Numerically summarizing data --
Measures of central tendency --
Measures of dispersion --
Measures of central tendency and dispersion from grouped data --
Measures of position and outliers --
The five-number summary and boxplots --
ch. 4. Describing the relation between two variables --
Scatter diagrams and correlation --
Least-squares regression --
Diagnostics on the least-squares regression line --
Contingency tables and association --
Nonlinear regression : transformations --
pt. 3. Probability and probability distributions --
ch. 5. Probability --
Probability rules --
The addition rule and complements --
Independence and the multiplication rule --
Conditional probability and the general multiplication rule --
Counting techniques --
Baye's rule --
ch. 6. Discrete probability distributions --
Discrete random variables --
Binomial probability distribution --
The Poisson probability distribution --
The hypergeometric probability distribution --
ch. 7. The normal probability distribution --
Properties of the normal distribution --
Applications of the normal distribution --
Assessing normality --
The normal approximation to the binomial probability distribution --
pt. 4. Inference : from samples to population --
ch. 8. Sampling distributions --
Distribution of the sample mean --
Distribution of the sample proportion --
ch. 9. Estimating the value of a parameter --
Estimating a population proportion --
Estimating a population mean --
Estimating a population standard deviation --
Estimating with bootstrapping --
ch. 10. Hypothesis tests regarding a parameter --
Language of hypothesis testing --
Hypothesis tests for a population proportion --
Hypothesis tests for a population mean --
Hypothesis tests for a population standard deviation --
Probability of a Type II error and the power of the test --
ch. 11. Inferences on two samples --
Inference about two population proportions --
Inference about two means : dependent samples --
Inference about two means : independent samples --
Inference about two population standard deviations --
ch. 12. Inference on categorical data --
Goodness-of-fit test --
Tests for independence and the homogeneity of proportions --
ch. 13. Comparing three or more means --
One-way analysis of variance --
Post hoc tests on one-way analysis of variance --
The randomized complete block design --
Two-way analysis of variance.