Hypothesis Testing

Cheng-Few Lee, John Lee, Jow-Ran Chang and Tzu Tai
Additional contact information
Cheng-Few Lee: Rutgers University, Department of Finance
John Lee: Center for PBBEF Research
Jow-Ran Chang: National Tsing Hua University, Department of Quantitative Finance
Tzu Tai: Mezocliq, LLC

Chapter Chapter 11 in Essentials of Excel, Excel VBA, SAS and Minitab for Statistical and Financial Analyses, 2016, pp 385-417 from Springer

Abstract: Abstract In the last chapter, we made inferences about a population parameter by creating a confidence interval from a sample. We will now look at another method, called hypothesis testing, for making inferences about a population parameter. In hypothesis testing we infer that the stated null hypothesis (H0) is true until there is convincing but not perfect evidence that the null hypothesis is not true. Our evidence is from the sample that we obtain. We conclude that there is convincing evidence when the p-value is less than the alpha value. The p-value will be discussed later in this chapter.

Keywords: Hypotheses; Hypothesis testing; Null hypothesis; Alternative hypothesis; Power function; Type I error; Type II error; One-tailed test; Two-tailed test; Upper-tailed test; Critical value; Parameter; The power of a test (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-38867-0_11

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DOI: 10.1007/978-3-319-38867-0_11

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