Practical uses of statistical power in business research studies An important use of power is in the planning of sample sizes prior to gathering data used to evaluate statistical hypotheses. A number of business statistics texts illustrate this use of power (Anderson‚ Sweeney‚ & Williams‚ 1999; Daniel & Terrell‚ 1995). Again‚ however‚ the presentation is somewhat technical and developed through formulas‚ and is restricted to simple one-sample tests involving a mean or binomial proportion as the
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CHAPTER 4 – THE BASIS OF STATISTICAL TESTING * samples and populations * population – everyone in a specified target group rather than a specific region * sample – a selection of individuals from the population * sampling * simple random sampling – identify all the people in the target population and then randomly select the number that you need for your research * extremely difficult‚ time-consuming‚ expensive * cluster sampling – identify
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modifications for many recent graduates is the decrease in the amount of partying‚ and the realization that it ends when college does. I conducted a statistical analysis on the consumption of alcohol for those still enrolled in undergraduate programs compared to the consumption of recent graduates. My research objectives include the following: * Document with statistical evidence that UMass Amherst students currently enrolled in courses consume more alcohol than UMass Amherst recent graduates. * Use
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Statistical Analysis for Quick Stab Collection Agency Executive Summary The purpose of the paper is to provide a statistical analysis of overdue bills for Quick Stab Collection Agency (QSCA). The data will be taken from accounts closed over a six month period. The goal is to determine if a correlation between the type of account‚ the amount of the bill and the days to collection exists. To determine the existence of a correlation‚ regression analysis of several variables was completed. This
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EXERCISE 36 Questions to be graded 1. The researchers found a significant difference between the two groups (control and treatment) for change in mobility of the women with osteoarthritis (OA) over 12 weeks with the results of F(1‚ 22) = 9.619‚p = 0.005. Discuss each aspect of these results. Answer F-value shows significance between the two groups. The null hypothesis should be rejected because the P-Value is 0.005 which would mean that the groups are different. 2. State the null hypothesis
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Practice with p-values Work through these problems with your computer partner and/or instructor. Answers follow the problem set. 1. Suppose we’ve done the computation of the Z test statistic. For each of the following situations determine the p-value that goes along with Z. a. Z = 2.12‚ two-sided test b. Z = 4.55‚ two-sided test c. Z = -1.40‚ lower-tail test 2. Suppose Z = 1.92.Which has a smaller p-value‚ the upper-tail test or the two-sided test? From this‚ is it more likely to have a
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CHAPTER 10: TWO-SAMPLE TESTS WITH NUMERICAL DATA 1. The t test for the difference between the means of 2 independent populations assumes that the respective a) sample sizes are equal. b) sample variances are equal. c) populations are approximately normal. d) all of the above ANSWER: c TYPE: MC DIFFICULTY: Moderate KEYWORDS: pooled-variance t test‚ assumption 2. The t test for the mean difference between 2 related populations
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Chapter 10 Statistical Inferences Based on Two Samples True/False 1. An independent sample experiment is an experiment in which there is no relationship between the measurements in the different samples. Answer: True Difficulty: Medium 2. When testing the difference between two proportions selected from populations with large independent samples‚ the Z test statistic is used. Answer: True Difficulty: Medium 3. In forming a large sample confidence interval for [pic]‚ two assumptions
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| Statistical Analysis of Yearly Checkups based on Gender | | STAT 3125 Section 04 | | 11/29/2012 | | This statistical analysis is of a randomly selected sample of 300 from the 2010 version of the Behavioral Risk Factor Surveillance System (BRFSS) database1. The selected study on the length of time since last routine checkup was listed under the SAS Variable Name – CHECKUP1.This data set specified how long it had been since the respondent had been in for a routine checkup‚ defining
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