TAILIEUCHUNG - Ebook Understanding statistics in the behavioral sciences (9th edition): Part 2

(BQ) Part 2 book "Understanding statistics in the behavioral sciences" has contents: Review of inferential statistics, introduction to two way analysis of variance; chi square and other nonparametric tests, sampling distributions, sampling distribution of the mean, the normal deviate,.and other contents. | Chapter 11 Power CHAPTER OUTLINE LEARNING OBJECTIVES Introduction What Is Power? Pnull and Preal After completing this chapter, you should be able to: ■ Define power, in terms of both H and H . 1 0 ■ Define P null and Preal, and specify what Preal measures. ■ Specify the effect that N, size of real effect, and alpha level have on power. ■ Explain the relationship between power and beta. ■ Explain why we never “accept” H , but instead “fail to 0 reject,” or “retain” it. ■ Calculate power using the sign test. ■ Understand the illustrative examples, do the practice problems, and understand the solutions. Preal: A Measure of the Real Effect Power Analysis of the AIDS Experiment Effect of N and Size of Real Effect Power and Beta (b) Power and Alpha (a) Alpha–Beta and Reality Interpreting Nonsignificant Results Calculation of Power WHAT IS THE TRUTH? • Astrology and Science Summary Important New Terms Questions and Problems Notes Book Companion Site 267 268 C H A P T E R 11 Power INTRODUCTION MENTORING TIP Caution: many students find this is a difficult chapter. You may need to give it some extra time. We have seen in Chapter 10 that there are two errors we might make when testing hypotheses. We have called them Type I and Type II errors. We have further pointed out that the alpha level limits the probability of making a Type I error. By setting alpha to or , experimenters can limit the probability that they will falsely reject the null hypothesis to these low levels. But what about Type II errors? We defined beta 1b2 as the probability of making a Type II error. We shall see later in this chapter that b ϭ 1 Ϫ power. By maximizing power, we minimize beta, which means we minimize the probability of making a Type II error. Thus, power is a very important topic. WHAT IS POWER? Conceptually, the power of an experiment is a measure of the sensitivity of the experiment to detect a real effect of the independent variable. By “a real effect of the independent

• Toán học
• Understanding statistics
• The behavioral sciences
• Inferential statistics
• The normal deviate
• Sampling distributions
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• The binomial distribution
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• Complex quantitative transcriptional
• Statistics for management and economics abbreviated
• Discrete probability distribution
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• Graphical descriptive techniques I
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• Monte Carlo and Insomnia
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• Sampling simple distributions
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• Journal of Zoology
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