About this Book
Introduction to Statistics: An Excel-Based Approach introduces students to the concepts and applications of statistics, with a focus on using Excel to perform statistical calculations. The book is written at an introductory level, designed for students in fields other than mathematics or engineering, but who require a fundamental understanding of statistics. The text emphasizes understanding and application of statistical tools over theory, but some knowledge of algebra is required.
Although the text focuses on concepts and applications, every effort has been made to provide both information essential to understanding a topic and sound methodological development. Generally accepted terminology and notation for each topic is used throughout without becoming overly focused on technical details.
In place of manual calculations and the use of probability distribution tables, the text utilizes Excel in the application of statistical analysis. Because of the prevalence and use of Excel in a wide-range of fields, it is important for students to understand how to leverage Excel’s statistical capabilities. Throughout the text, information is provided on the appropriate Excel function required for a calculation and the solutions to examples illustrate how to use the corresponding Excel function to solve problems.
The text is organized into thirteen chapters, and then divided into subchapters by concept or topic. The chapters are as follows:
| Chapter 1: Sampling and Data | Chapter 1 covers key definitions, terms, and terminology used in statistics, as well exploring different sampling methods, types of data, and level of measurement. |
| Chapter 2: Descriptive Statistics | Chapter 2 examines the different descriptive statistics, both graphical and numerical, required to organize, summarize, and describe data. |
| Chapter 3: Probability | Chapter 3 introduces the concept of probability, probability terminology, different approaches to probability, and various probability rules. |
| Chapter 4: Discrete Random Variables | Chapter 4 explores discrete random variables and their probability distributions, the mean and standard deviation of a discrete random variable, and examines the binomial and Poisson distributions. |
| Chapter 5: Continuous Random Variables and the Normal Distribution | Chapter 5 covers continuous random variables, focusing on the normal distribution and probability problems associated with the normal distribution. |
| Chapter 6: The Central Limit Theorem and Sampling Distributions | Chapter 6 examines the sampling distributions of sample mean and the sampling distribution of the sample proportion. |
| Chapter 7: Confidence Intervals for Single Population Parameters | Chapter 7 explores the construction, use and interpretation of confidence intervals to estimate a population mean or a population proportion, as well as determining the sample size necessary for the required accuracy of a confidence interval. |
| Chapter 8: Hypothesis Tests for Single Population Parameters | Chapter 8 introduces the formal hypothesis testing procedure, focusing on conducting and drawing a conclusion from a hypothesis test on a population mean or a population proportion. |
| Chapter 9: Statistical Inference for Two Populations | Chapter 9 extends confidence intervals and hypothesis testing to the difference between two population means or the difference between two population proportions. |
| Chapter 10: Statistical Inference Using the [latex]\chi^2[/latex]-Distribution | Chapter 10 covers the use of the [latex]\chi^2[/latex]-distribution in statistical inference, including confidence intervals and hypothesis testing for a population variance, the goodness-of-fit test, and the test of independence. |
| Chapter 11: Statistical Inference Using the [latex]F[/latex]-Distribution | Chapter 11 examines the use of the [latex]F[/latex]-distribution in statistical inference, including confidence intervals and hypothesis testing for the ratio of two population variances and the one-way ANOVA test on the equality of three or more population means. |
| Chapter 12: Simple Linear Regression and Correlation | Chapter 12 explores the linear relationship between two variables through the simple linear regression model, including methods to assess the validity of the model. |
| Chapter 13: Multiple Regression | Chapter 13 extends the linear regression model to include more than one independent variable, including methods to assess the validity of the model. |
For the Student
Each sub-chapter in this text begins with a list of relevant learning objectives and concludes with a concept review that highlights the key topics in the sub-chapter. Where appropriate, videos are included to review, enhance, and extend the material covered in the text. At the end of each chapter, a series of exercises are included to check retention and asses understanding.
Accessibility Statement
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The web version of this resource has been designed to meet Web Content Accessibility Guidelines 2.0, level AA. In addition, it follows all guidelines in Appendix A: Checklist for Accessibility of the Accessibility Toolkit – 2nd Edition.
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