Applying ANOVA and Nonparametric test In the simulation‚ I selected the Kruskal-Wallis test which is used when it is difficult to meet all of the assumptions of ANOVA. The Kruskal-Wallis test is a nonparametric alternative to one way ANOVA. This test is used to compare three or more samples‚ to test the null hypothesis that the different samples in the comparison drawn from the same distribution or from distributions with the same median. Interpretation of the Kruskal-Wallis test is basically similar
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Composition II 2:00 22 November 2011 P.E.D.’s in M.L.B. Big muscles and performance enhancing drugs have changed the game of baseball forever. Performance enhancing substances‚ stimulants‚ and drugs of abuse are banned by Major League Baseball. According to the Los Angeles Times‚ there are a total of 58 substances‚ 30 stimulants‚ and 7 drugs of abuse that Major League Baseball has banned players from using. Performance enhancing drug usage was speculated as a problem‚ but wasn’t showcased on a national
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The five-step processes for hypothesis testing are the following. Step1. Specify the null hypothesis H0 and alternative hypothesis H1. The null hypothesis is the hypothesis that the researcher formulates and proceeds to test. If the null hypothesis is rejected after the test‚ the hypothesis to be accepted is called the alternative hypothesis. For example if the researcher wants to compare the average value generated by two different procedures the null hypothesis to be tested is [pic] and
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Vincent R. Dagohoy Date performed: 07-01-13 Student Number: 2009-33281 Date submitted: 07-08-13 Exercise 2 Formulation‚ Testing of Hypothesis‚ and Experimental Design I. Objectives: a. to define diffusion and demonstrate this process in gases b. to cite molecular weight and time as two factors affecting the rate of diffusion c. to formulate a hypothesis on the relationship of each of these factors on the rate of diffusion d. to conduct and experiment to determine the effects
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Critical-Value Approach to Hypothesis Testing We often use inferential statistics to make decisions or judgments about the value of a parameter‚ such as a population mean. For example‚ we might need to decide whether the mean weight‚ μ‚ of all bags of pretzels packaged by a particular company differs from the advertised weight of 454 grams (g)‚ or we might want to determine whether the mean age‚ μ‚ of all cars in use has increased from the year 2000 mean of 9.0 years. One of the most commonly
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On the research topic of major league baseball our goal is to research the dependence of salary‚ wins‚ and how many attend the games on an average. The issue is do salaries and overall team revenue based on wins or individual talent. Through research this question of is does the overall team salary depend on one more than the other. Is one factor more important than the next. Also is whether the league national or American plays a role in the overall salary from the start not factoring in the statistics
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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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U.S. economy only hinders people more with high gas prices. A one population test using the One Factor ANOVA test and a five-step hypothesis test can be used to determine if gas prices are equally high in many different states. The samples used to test the hypothesis come from data collected from 30 randomly selected gas stations in six different cities. The hypothesis test and some solutions to consider may have an effect on direct and indirect stakeholders and is very important to the economy as
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Table of Contents Frequencies: Statistics RESPONDED GENDER HSC GPA STUDY HOUR N Valid 75 75 75 Missing 0 0 0 Mean 1.51 4.8520 4.5600 Median 1.51a 4.9442a 4.5094a Mode 2 5.00 4.00 Std. Deviation .503 .23673 1.00324 Variance .253 .056 1.006 Skewness -.027 -1.608 .408 Std. Error of Skewness .277 .277 .277 Kurtosis -2.055 1.864 -.117 Std. Error of Kurtosis .548 .548 .548 Range 1 1.00 4.00 Sum 113 363.90 342.00 Percentiles
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KEYWORDS: t test for mean difference‚ assumption 3. If we are testing for the difference between the means of 2 related populations with samples of n1 = 20 and n2 = 20‚ the number of degrees of freedom is equal to a) 39. b) 38. c) 19. d) 18. ANSWER: c TYPE: MC DIFFICULTY: Easy KEYWORDS: t test for mean difference‚ degrees of freedom 4. If we are testing for the difference between the means of 2 independent populations with samples
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