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Hypothesis Testing: An Intuitive Guide for Making Data Driven Decision Paperback

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Item specifics

Condition
New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN
9781735431154

About this product

Product Identifiers

Publisher
James D. Frost
ISBN-10
173543115X
ISBN-13
9781735431154
eBay Product ID (ePID)
24050383159

Product Key Features

Number of Pages
382 Pages
Publication Name
Hypothesis Testing : an Intuitive Guide for Making Data Driven Decisions
Language
English
Publication Year
2020
Subject
General
Type
Textbook
Author
Jim Frost
Subject Area
Mathematics, Education
Format
Trade Paperback

Dimensions

Item Length
9 in
Item Width
6 in

Additional Product Features

Intended Audience
Trade
eBook Format
Adobe PDF
Synopsis
The world produces more data than ever. Are you ready for it? In today's data-driven world, you hear about making decisions based on data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, business, or data science. Without hypothesis tests, you risk making bad decisions. Chances are high you'll need to understand these tests to analyze your data and evaluate the work of others. Build the knowledge for effective hypothesis testing Know when to use each test, how to use them reliably, and how to interpret the results correctly Understand why you need hypothesis tests and how they work. Effectively use significance levels, p-values, confidence intervals. Select the correct type of test to answer your question. Learn how to test means, medians, variances, proportions, distributions, counts, correlations for continuous and categorical data, and find outliers. One-Way ANOVA, Two-Way ANOVA, and interaction effects. Check assumptions to obtain reliable results. Manage the error rates for false positives and false negatives. Understand sampling distributions, the central limit theorem, and statistical power. Know how t-tests, F-tests, chi-squared, and post hoc tests work. Learn about differences between parametric, nonparametric, and bootstrapping methods. Examples of many hypothesis tests. Access free downloadable datasets so you can try it yourself., 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 367-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. Use 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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