Elementary Statistics: Picturing the World 6th Edition, (Ebook PDF) – Digital Instant Dowload.

Product details:

• ISBN-10 ‏ : ‎ 0321901118
• ISBN-13 ‏ : ‎ 978-0321901118
• Author: Ron Larson (Author), Betsy Farber (Author)

Statistics opens a window to the modern world, and this market-leading text makes it easy to understand! Larson and Farber’s Elementary Statistics: Picturing the World, Sixth Edition, provides stepped out instruction, real-life examples and exercises, and the use of technology to offer the most accessible approach. The authors carefully develop theory through strong pedagogy, and examples show how statistics is used to picture and describe the world. In keeping with the premise that students learn best by doing, it includes more than 210 examples and more than 2300 exercises, to make the concepts of statistics a part of students’ everyday lives.

Table contents:

PART ONE. DESCRIPTIVE STATISTICS

1. Introduction to Statistics

1.1. An Overview of Statistics

1.2. Data Classification

Case Study: Rating Television Shows in the

United States

1.3. Data Collection and Experimental Design

2. Descriptive Statistics

2.1. Frequency Distributions and Their Graphs

2.2. More Graphs and Displays

2.3. Measures of Central Tendency

Activity: Mean Versus Median

2.4. Measures of Variation

Activity: Standard Deviation

Case Study: Business Size

2.5. Measures of Position

PART TWO. PROBABILITY & PROBABILITY DISTRIBUTIONS

3. Probability

3.1. Basic Concepts of Probability and Counting

Activity: Simulating the Stock Market

3.2. Conditional Probability and the Multiplication Rule

3.3. The Addition Rule

3.4. Additional Topics in Probability and Counting

4. Discrete Probability Distributions

4.1. Probability Distributions

4.2. Binomial Distributions

4.3. More Discrete Probability Distributions

5. Normal Probability Distributions

5.1. Introduction to Normal Distributions and the Standard Normal Distribution

5.2. Normal Distributions: Finding Probabilities

5.3. Normal Distributions: Finding Values

Case Study: Birth Rates in America

5.4. Sampling Distributions and the Central Limit Theorem

Activity: Sampling Distributions

5.5. Normal Approximations to Binomial Distributions

PART THREE. STATISTICAL INFERENCE

6. Confidence Intervals

6.1. Confidence Intervals for the Mean (¡ Known)

6.2. Confidence Intervals for the Mean (¡ Unknown)

Activity: Confidence Intervals for a Mean

Case Study: Marathon Training

6.3. Confidence Intervals for Population Proportions

Activity: Confidence Intervals for a Proportion

6.4. Confidence Intervals for Variance and Standard Deviation

7. Hypothesis Testing with One Sample

7.1. Introduction to Hypothesis Testing

7.2. Hypothesis Testing for the Mean (¡ Known)

7.3. Hypothesis Testing for the Mean (¡ Unknown)

7.4. Hypothesis Testing for Proportions

Activity: Hypothesis Test for a Proportion

7.5. Hypothesis Testing for Variance and Standard Deviation

8. Hypothesis Testing with Two Samples

8.1. Testing the Difference Between Means (Independent Samples, ¡1 and ¡2 Known)

8.2. Testing the Difference Between Means (Independent Samples, ¡1 and ¡2 Unknown)

8.3. Testing the Difference Between Means (Dependent Samples)

8.4. Testing the Difference Between Proportions

PART FOUR. MORE STATISTICAL INFERENCE

9. Correlation and Regression

9.1 Correlation

Activity: Correlation by Eye

9.2. Linear Regression

Activity: Regression by Eye

Case Study: Correlation by Body Measurements

9.3. Measures of Regression and Prediction Intervals

9.4. Multiple Regression

10. Chi-Square Tests and the F-Distribution

10.1. Goodness-of-Fit Test

10.2. Independence

Case Study: Food Safety Survey

10.3. Comparing Two Variances

10.4. Analysis of Variance

Cumulative Review: Chapters 9 and 10

11. Nonparametric Tests

11.1. The Sign Test

11.2. The Wilcoxon Tests

Case Study: College Ranks

11.3. The Kruskal-Wallis Test

11.4. Rank Correlation

11.5. The Runs Test

Research