Test of Hypothesis – Large Sample Test Critical Value (Zx) | Level of Significance (x) | | 1% | 5% | Two tailed test | Z = 2.58 | Z = 1.96 | One tailed test | Z = 2.33 | Z = 1.64 | Q. Z= X- μ σ√n = x- μS.EX The mean height of a random sample of 100 students is 64” and standard deviation is 3”. Test the statement that the mean height of population is 67” at 5% level of significance. Solution: We are given n = 100
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Inferential Statistics Drawing Conclusions based on Samples Introduction This chapter introduces how you can use data from a sample to draw conclusions about the larger population from which the sample was taken. Data often arises from the results of a survey of individuals. For example‚ the management of a fast food chain might be interested in determining the total number of dollars that Baylor students spend each year eating in Waco fast food restaurants. The fast food chain would
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properties. 5. For a continuous random variable‚ the total area beneath the probability distribution curve will be greater than 0 but less than 1. A) True False 6. The standardized normal distribution always has a mean of zero and a standard deviation of one. True A) False 7. Excel’s RAND() function produces random numbers that are uniformly distributed from 0 to 1. The standard deviation of this distribution is about A) .5000
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of factors influence the sample size for a substantive test of details of an account balance. All other factors being equal‚ which of the following would lead to a larger sample size? A. Greater reliance on internal accounting controls. B. Greater reliance on analytical review procedures. C. Smaller expected frequency of misstatements. D. Smaller measure of tolerable misstatements. 4. Which of the following sample planning factors would influence the sample size for a substantive test of details
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Man and nature I went to Henan with my parents and my brother for my passport last week.Armed with luggage‚ we started a travel. Approaching my home town‚ I saw the beautiful scenery and I smell fresher air in the train. But not everywhere is beautiful like that. When we arrived the county of my hometown‚ we went to the local police station to deal with my ID card first. Then we had to go to the police station in the countryside which has the data of me and brought the data back to the police
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non-probability / ’judgement ’ • to describe stages in the process of sampling‚ and the possible intrusion of ‘bias’ • to describe methods of probability sampling and methods of non-probability sampling • to be able to estimate your desired sample size‚ - using rules of thumb - or charts (e.g. in deVaus) • to describe the problem of non-response‚ and how to minimise it • to consider methods used for ‘sampling’ and generalisability in qualitative / ‘flexible’ designs External
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Intelligence vs. Brain size Project 2: Data Collection College Algebra 161 November 15‚ 2012 Intelligence vs. Brain size The Data Collection project was designed to teach students how to collect‚ and organize‚ describe and document data using Excel lists and graphs. I chose this particular subject to research to further my understanding of the evolution of human species. “Can intelligence and brain size be directly related‚ and as intelligence increases‚ what happens to the size of our brains
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References: Sample Size 155 702 1‚772 324 19 20 53 44 30 Productivity Growth Differential + 0.1%m + 3.4% + 2.6% + 0.6% + 0.4% n.a. + 0.2% n.a. 0.0% Author Allen (1988) Denny (1997) Gregg et al
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layers‚ how your business is functionally divided and the overall reporting structure. Multiple organizational designs can be used to enhance your business’s strategy including simple‚ functional‚ matrix‚ hybrid or a self-designed structure. Size: Larger business size often equates to a more elaborate or complex organizational structure. As your business expands‚ additional layers of management‚ business units and a formal chain of command are generally needed. While a small business may function on an
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vs. Shoe Size I chose two quantitate variables in this study in order to see if they had any linear relationship. The dependent (response) variable was a person’s shoe size in united states meaurements and the independent (explanatory) variable was person’s height in inches. I chose these two variables because I assume before the study that there would be appositive linear relationship between height and shoe size. In other words‚ the taller the individuals are‚ the larger their foot size will be
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