Statistics 10th edition mcclave sincich

Chapter 12 Multiple Regression and Model Building. Two sections from the previous edition have been reorganized: Section Table of Contents 1. Statistics, Data, and Statistical Thinking 1. Methods for Describing Sets of Data 2. Probability from McClave 11e—Chap 3 3. Random Variables and Probability Distributions 4. Comparing Population Means 7. Comparing Population Proportions 8. Simple Linear Regression 9. About the Author s. Previous editions. First Course in Statistics, A, 9th Edition.

Sign In We're sorry! Username Password Forgot your username or password? Sign Up Already have an access code? Instructor resource file download The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning.

Signed out You have successfully signed out and will be required to sign back in should you need to download more resources. Instructors, sign in here to see net price. Continued emphasis on Ethics : where appropriate, boxes have been added emphasizing the importance of ethical behavior when collecting, analyzing, and interpreting data with statistics.

Also, recent examples of misleading graphics have been added to Section 2. Chapter 4 Discrete Random Variables and Chapter 5 Continuous Random Variables : Use of technology for computing probabilities of random variables with known probability distributions e. This reduces the use of tables of probabilities for these distributions. Chapter 6 Sampling Distributions : In addition to the sampling distribution of the sample mean, we now cover in new Section 6.

Throughout the remainder of the text, conclusions from a test of hypothesis are based on p-values. Table of Contents 1. Statistics, Data, and Statistical Thinking 1. Methods for Describing Sets of Data 2. Probability 3. Discrete Random Variables 4. Continuous Random Variables 5. Sampling Distributions 6. Simple Linear Regression Multiple Regression and Model Building Categorical Data Analysis Nonparametric Statistics available online Share a link to All Resources.

Instructor Resources. Websites and online courses. Other Student Resources. Course Resources. Instructors, you may still place orders with your bookstore. Discipline Resources. About the Author s.

Previous editions. Relevant Courses. Sign In We're sorry! Username Password Forgot your username or password? Sign Up Already have an access code? Instructor resource file download The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning.

Signed out You have successfully signed out and will be required to sign back in should you need to download more resources. Students, buy access. On-line Supplement. Study Card. This item is currently unavailable for purchase on our websites. Not yet available. Expected Values of Discrete Random Variables. The Binomial Random Variable. The Poisson Random Variable Optional. The Hypergeometric Random Variable Optional.

The Uniform Distribution. The Normal Distribution. Descriptive Methods for Assessing Normality. The Exponential Distribution Optional. The Central Limit Theorem. Statistics in Action: The Insomnia Pill. Determining the Sample Size.

Identifying the Parameter to be Estimated. Observed Significance Levels: p-Values. Identifying the Parameter to be Tested. Statistics in Action: Diary of a Kleenex User. Identifying the Parameter of Interest. The Completely Randomized Design. Multiple Comparisons of Means. The Randomized Block Design. Factorial Experiments. Statistics in Action: On the Trail of the Cockroach. Model Assumptions. The Coefficients of Correlation and Determination. Using the Model for Estimation and Prediction.

A Complete Example. Checking the Overall Utility of a Model. Model Building: Interaction Models. Model Building: Comparing Nested Models. Model Building: Stepwise Regression.

Residual Analysis: Checking the Regression Assumptions. Some Pitfalls: Estimability, Multicollinearity, and Extrapolation. Single Population Inferences. Comparing Two Populations: Independent Samples. Inferences about Rank Correlation.

Appendix A: Tables Random Numbers. Binomial Probabilities. Poisson Probabilities.