A Student Solutions Manual for First Course in Statistics 10th Edition by Nancy Boudreau, Terry Sincich ISBN 0136045197 9780136045199

Chapter 1: Introduction to Statistics

1.1 Introduction to Statistics and Data
1.2 Types of Data
1.3 Levels of Measurement
1.4 Organizing Data
1.5 Displaying Data: Tables and Graphs
1.6 Measures of Central Tendency
1.7 Measures of Dispersion
1.8 The Normal Distribution
1.9 Working with Data

Chapter 2: Descriptive Statistics

2.1 Organizing and Summarizing Data
2.2 Frequency Distributions and Histograms
2.3 Measures of Central Tendency
2.4 Measures of Dispersion
2.5 Boxplots
2.6 Visualizing Data with Graphs
2.7 Descriptive Measures for Grouped Data
2.8 Z-Scores and Standardization

Chapter 3: Probability

3.1 Introduction to Probability
3.2 Sample Spaces and Events
3.3 The Addition Rule
3.4 The Multiplication Rule
3.5 Conditional Probability
3.6 Bayes’ Theorem
3.7 Random Variables and Probability Distributions
3.8 The Binomial Distribution
3.9 The Poisson Distribution

Chapter 4: Discrete Probability Distributions

4.1 Random Variables
4.2 The Binomial Distribution
4.3 The Poisson Distribution
4.4 Mean, Variance, and Standard Deviation of Discrete Distributions
4.5 Expected Value and Variance
4.6 Applications of Discrete Distributions

Chapter 5: The Normal Distribution

5.1 Introduction to the Normal Distribution
5.2 Properties of the Normal Distribution
5.3 Standard Normal Distribution
5.4 Using Z-Scores for Probability Calculations
5.5 Applications of the Normal Distribution
5.6 Central Limit Theorem
5.7 Sampling Distributions of the Sample Mean

Chapter 6: Confidence Intervals

6.1 Introduction to Confidence Intervals
6.2 Confidence Interval for a Population Mean
6.3 Confidence Interval for a Population Proportion
6.4 Confidence Interval for the Difference Between Two Means
6.5 Confidence Interval for the Difference Between Two Proportions
6.6 Interpreting Confidence Intervals

Chapter 7: Hypothesis Testing

7.1 Introduction to Hypothesis Testing
7.2 Steps in Hypothesis Testing
7.3 Hypothesis Test for a Population Mean
7.4 Hypothesis Test for a Population Proportion
7.5 Hypothesis Test for the Difference Between Two Means
7.6 Hypothesis Test for the Difference Between Two Proportions
7.7 Errors in Hypothesis Testing (Type I and Type II Errors)
7.8 Power of a Hypothesis Test

Chapter 8: Comparing Two Populations

8.1 Two-Sample Hypothesis Tests
8.2 Confidence Intervals for the Difference Between Two Means
8.3 Paired Sample t-Test
8.4 Hypothesis Tests for the Difference Between Two Proportions
8.5 Comparing Population Variances

Chapter 9: Chi-Square Tests

9.1 Introduction to Chi-Square Tests
9.2 Chi-Square Test for Goodness of Fit
9.3 Chi-Square Test for Independence
9.4 Chi-Square Test for Homogeneity
9.5 Applications of Chi-Square Tests

Chapter 10: Analysis of Variance (ANOVA)

10.1 One-Way ANOVA
10.2 Hypothesis Test for More Than Two Means
10.3 Two-Way ANOVA
10.4 Interactions in Two-Way ANOVA
10.5 Post-Hoc Tests for ANOVA

Chapter 11: Simple Linear Regression and Correlation

11.1 Introduction to Regression and Correlation
11.2 The Least-Squares Method
11.3 The Regression Equation
11.4 The Coefficient of Determination (R²)
11.5 Correlation Analysis
11.6 Residual Analysis
11.7 Testing the Slope of a Regression Line

Chapter 12: Multiple Linear Regression

12.1 Multiple Regression Models
12.2 Interpreting Coefficients in Multiple Regression
12.3 Assessing the Fit of a Multiple Regression Model
12.4 Using Dummy Variables in Regression
12.5 Multicollinearity in Multiple Regression
12.6 Stepwise Regression

Chapter 13: Nonparametric Methods

13.1 Introduction to Nonparametric Methods
13.2 Sign Test
13.3 Wilcoxon Rank-Sum Test
13.4 Wilcoxon Signed-Rank Test
13.5 Kruskal-Wallis Test
13.6 Spearman Rank Correlation

Chapter 14: Statistical Process Control

14.1 Introduction to Statistical Process Control (SPC)
14.2 Control Charts for Variables
14.3 Control Charts for Attributes
14.4 Process Capability Analysis
14.5 Six Sigma and SPC

Chapter 15: Time Series Analysis and Forecasting

15.1 Introduction to Time Series
15.2 Decomposing Time Series Data
15.3 Moving Averages
15.4 Exponential Smoothing
15.5 Forecasting Using Time Series Data

Chapter 16: Sampling Distributions

16.1 Sampling Distribution of the Sample Mean
16.2 Central Limit Theorem
16.3 Sampling Distribution of the Sample Proportion
16.4 The Standard Error of the Mean