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Introductory Statistics / Edition 1
     

Introductory Statistics / Edition 1

by Stephen Kokoska
 

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ISBN-10: 0716757621

ISBN-13: 9780716757627

Pub. Date: 01/01/2008

Publisher: Freeman, W. H. & Company

Written to appeal to students and instructors who appreciate statistics for its precision and logic, Introductory Statistics: A Problem-Solving Approach helps students learn statistical concepts by using a stepped problem-solving approach.

After completing an introductory statistics course with this textbook, students should understand the process of

Overview

Written to appeal to students and instructors who appreciate statistics for its precision and logic, Introductory Statistics: A Problem-Solving Approach helps students learn statistical concepts by using a stepped problem-solving approach.

After completing an introductory statistics course with this textbook, students should understand the process of basic statistical arguments. They should grasp the importance of assumptions and be able to follow valid arguments or identify inaccurate conclusions. Most importantly, they should understand the process of statistical inference.

The philosophy of this text is simple: statistics is often hard for students, and in order to understand concepts, the material must be presented in an orderly, precise, friendly manner. It must be easy to read and follow, and there must be numerous examples and exercises. The text aims to be easy-to-read, down-to-earth, systematic, and methodical. Each new idea builds upon concepts presented earlier. A touch of humor is important, especially for many students who are afraid of, and even dislike, mathematics and statistics.

Product Details

ISBN-13:
9780716757627
Publisher:
Freeman, W. H. & Company
Publication date:
01/01/2008
Edition description:
First Edition
Pages:
977
Product dimensions:
8.50(w) x 10.80(h) x 1.80(d)

Table of Contents

*Optional sections found online

1 An Introduction to Statistics and Statistical Inference
1.1 Statistics Today
1.2 Populations, Samples, Probability, and Statistics
1.3 Experiments and Random Samples

2 Tables and Graphs for Summarizing Data
2.1 Types of Data
2.2 Bar Charts and Pie Charts
2.3 Stem-and-Leaf Plots 2.4 Frequency Distributions and Histograms

3 Numerical Summary Measures
3.1 Measures of Central Tendency
3.2 Measures of Variability
3.3 The Empirical Rule and Measures of Relative Standing
3.4 Five-Number Summary and Box Plots

4 Probability
4.1 Experiments, Sample Spaces, and Events
4.2 An Introduction to Probability
4.3 Counting Techniques
4.4 Conditional Probability
4.5 Independence

5 Random Variables and Discrete Probability Distributions
5.1 Random Variables
5.2 Probability Distributions for Discrete Random Variables
5.3 Mean, Variance, and Standard Deviation for a Discrete Random
Variable
5.4 The Binomial Distribution
5.5 Other Discrete Distributions

6 Continuous Probability Distributions
6.1 Probability Distributions for a Continuous Random Variable
6.2 The Normal Distribution
6.3 Checking the Normality Assumption
6.4 The Exponential Distribution

7 Sampling Distributions
7.1 Statistics, Parameters, and Sampling Distributions
7.2 The Sampling Distribution of the Sample Mean
7.3 The Distribution of the Sample Proportion

8 Confidence Intervals Based on a Single Sample
8.1 Point Estimation
8.2 A Confidence Interval for a Population Mean when s Is Known
8.3 A Confidence Interval for a Population Mean when s Is Unknown
8.4 A Large-Sample Confidence Interval for a Population Proportion
8.5 A Confidence Interval for a Population Variance

9 Hypothesis Tests Based on a Single Sample
9.1 The Parts of a Hypothesis Test and Choosing the Alternative
Hypothesis
9.2 Hypothesis Test Errors
9.3 Hypothesis Tests Concerning a Population Mean when Is
Known
9.4 p Values
9.5 Hypothesis Tests Concerning a Population Mean when s Is Unknown
9.6 Large-Sample Hypothesis Tests Concerning a Population Proportion
9.7 Hypothesis Tests Concerning a Population Variance or Standard
Deviation

10 Confidence Intervals and Hypothesis Tests Based on Two Samples
or Treatments

10.1 Comparing Two Population Means Using Independent Samples
when Population Variances Are Known
10.2 Comparing Two Population Means Using Independent Samples
from Normal Populations
10.3 Paired Data
10.4 Comparing Two Population Proportions Using Large Samples
10.5 Comparing Two Population Variances or Standard Deviations

11 The Analysis of Variance
11.1 One-Way ANOVA
11.2 Isolating Differences
11.3 Two-Way ANOVA

12 Correlation and Linear Regression
12.1 Simple Linear Regression
12.2 Hypothesis Tests and Correlation
12.3 Inferences Concerning the Mean Value and an Observed Value of Y for x = x*
12.4 Regression Diagnostics
12.5 Multiple Linear Regression
*12.6 The Polynomial and Qualitative Predictor Models
*12.7 Model Selection Procedures

13 Categorical Data and Frequency Tables
13.1 Univariate Categorical Data, Goodness-of-Fit Tests
13.2 Bivariate Categorical Data, Tests for Homogeneity and Independence

14 Nonparametric Statistics
14.1 The Sign Test
14.2 The Signed-Rank Test
14.3 The Rank-Sum Test
14.4 The Kruskal-Wallis Test
14.5 The Runs Test
14.6 Spearman's Rank Correlation

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