golf balls. The testing was performed with a mechanical fitting machine so that any difference between the mean distances for the two models could be attributed to a difference in the design. The outcomes are given in the table of appendix 1. 3. Hypothesis testing The first thing to do is to formulate and present the rationale for a hypothesis test that Par‚ Inc. could use to compare the driving distance of the current and new golf balls. By formulation of these hypothesis there is assumed
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An alpha level of 0.05 is arbitrary and was set as a standard by scientists. One of the key concepts in hypothesis testing is that of significance level or‚ the alpha level‚ which specifies the probability level for the evidence to be an unreasonable estimate. Unreasonable means that the estimate should not have taken its particular value unless some non-chance factor(s) had operated to alter the nature of the sample such that it was no longer representative of the population of interest Remember
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unknown = (5.16 x 7500)/4728 = 8.185 Therefore n = 67 and the mean of the population is 82‚636 + (4728/2) = 85‚000. 1|Page 1c (1) Hypothesis testing is used to determine the probability that a specified hypothesis is true. The assumption in this case that the mean salary of the population is 85‚000‚ is called the null hypothesis (H0). The alternative hypothesis (H1) is a claim to be
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which are: 1. Formation of Topic 2. Hypothesis (testable) 3. Conceptual Definition and 4. Operational Definition 5. Gathering of data 6. Analyses of data 7. Testing 8. Conclusion: The very last step in the research endeavor is to make the research findings available as useful information to the consumers‚ either by publishing the work or making it available to the relevant institution/organization. While talking about testing Hypotheses he listed two. They are the Null
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Chapter 9 Hypothesis Testing Case Problem 1: Quality Associates‚ Inc. 1. The hypothesis testing results are shown below: Sample 1 Sample 2 Sample 3 Sample 4 Sample Size 30 30 30 30 Mean 11.959 12.029 11.889 12.081 Standard Deviation 0.220 0.220 0.207 0.206 Level of Significance (alpha) 0.010 0.010 0.010 0.010 Critical Value (lower tail) -2.576 -2.576 -2.576 -2.576 Critical Value (upper tail) 2.576 2.576 2.576 2.576 Hypothesized value 12 12 12 12 Standard Error 0.040
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suburban customers more than $3200? Hypothesis testing and confidence intervals for situations A-D are calculated. A. THE AVERAGE (MEAN) ANNUAL INCOME WAS LESS THAN $45‚000. Solution: Step 1: Null Hypothesis: The average (mean) annual income was equal to $45‚000. H_0: μ=45‚0000 Step2: Alternate Hypothesis: The average (mean) annual was less than $50‚000. H_a: μ 45 ‚ a z-test for the mean will be used to test the given hypothesis. As for the alternative hypothesis‚ which is Ha:μ0.45 and the given
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Analyzing and Interpreting Data QNT/351 September 16‚ 2014 Analyzing and Interpreting Data BIMS management team has been facing a major dilemma of high turnover and extremely low employee morale. BIMS management team has asked Team B to help identify the main cause of the high turnover and low morale and propose an acceptable solution that will result in a decrease of both. Data Collection Conclusion In the past few months we at BIMS have learned‚ thru the drop in employees that the company’s
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steps in testing a research hypothesis: There are five steps that need to be taken when conducting a research hypothesis. The first step of research hypothesis is to state the problem in the form of a question. The question should identify the population(s) of interest to the researcher‚ the parameter(s) of the variable under investigation‚ and the hypothesized value of the parameter(s). The second step is to state the questions in a null or alternative hypothesis. A null hypothesis is the parameter
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error free. In other words‚ if something has often happened in the past‚ it will likely happen in the future (Lee & Baskerville‚ 2003). In research that is extremely important because once researchers have collected enough data to support their hypothesis‚ they can develop a premise to predict the outcome in similar situations with a certain degree of accuracy (Lee & Baskerville‚ 2003). In order to increase our confidence in the generalizability of a study‚ it would have to be repeated with the
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your sample of data or a sample with results more extreme‚ assuming the null hypothesis is true” (Simon‚ 2007); or in simpler terms‚ a p-value is a measure of how much evidence there is against the null hypothesis. The null hypothesis‚ traditionally represented by the symbol HO‚ “represents the hypothesis of no change or no effect” (Simon‚ 2007). If the obtained p-value is small then it can be said either the null hypothesis is false or an unusual event has occurred. A confidence interval “gives
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