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[Sample] Hypothesis Testing: An Intuitive Guide
This free sample includes the full Table of Contents and the first two chapters. To obtain the complete content, please buy the full ebook.
Build a solid foundation for understanding how hypothesis tests work and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and interpret the results correctly. Chances are high that you’ll need a working knowledge of hypothesis testing to produce new findings yourself and to understand the work of others. I present a wide variety of tests that assess characteristics of different data types. I focus on helping you grasp key concepts, methodologies, and procedures while deemphasizing equations. Learn how to use these tests painlessly in this ebook!
In today’s data-driven world, we hear about making decisions based on the data all the time. Hypothesis testing plays a crucial role in that process, whether you’re in academia, making business decisions, or in quality improvement. Without hypothesis tests, you risk drawing the wrong conclusions and making bad decisions. The world today produces more data and more analyses designed to influence you than ever before. Are you ready for it?
In this 371-page ebook, build the skills and knowledge you’ll need for effective hypothesis testing, including the following:
- Why you need hypothesis tests and how they work.
- Using significance levels, p-values, confidence intervals.
- Select the correct type of hypothesis test to answer your question.
- Learn how to test means, medians, variances, proportions, distributions, counts, correlations for continuous and categorical data, and outliers.
- One-Way ANOVA, Two-Way ANOVA and interaction effects.
- Interpreting the results.
- Checking assumptions and obtaining reliable results.
- Manage the error rates for false positives and false negatives.
- Understand sampling distributions, central limit theorem, and statistical power.
- Know how t-tests, F-tests, chi-squared, and post hoc tests work.
- Learn about the differences between parametric, nonparametric, and bootstrapping methods.
- Examples of different types of hypothesis tests.
- Downloadable datasets so you can try it yourself.
For each hypothesis test I cover, you will learn what it tells you, understand its assumptions, know how to interpret the results, and work through examples with downloadable datasets.
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