Exam Name___________________________________ Instructions: Read all the questions carefully and show all your work for full credit. All answers must be supported by correct work to receive full credit. SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Solve the problem. 1) Multiple-choice questions on a test each have 4 possible answers‚ one of which is correct. Assume that you guess the answers to 4 such questions. a. Use the multiplication rule to
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distribution or the Fisher - Snedecor distribution ( After R.A. Fisher and George W. Snedecor)(2) which arises in the testing of whether two observed samples have the same variance. (1) Note that three of the most important distributions (namely the normal distribution‚ the t distribution‚ and the chi-square distribution) may be seen as special cases of the F distribution: (3) Example: We want to measure the monthly sales volume from Microsoft and Apple. We collect data for a year ( 12 months). We
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250 units‚ and 20% of the time demand is less than 200 units. What is the average demand? What is the standard deviation of demand? (Demand can be assumed to follow a normal distribution) The demand of a product is observed to vary from one quarter to the other. The demand of each quarter can be assumed to follow a normal distribution with means and standard deviations given below: Demand Quarter Mean Standard Deviation 1 300 10 2 250 10 3 400 13 4 450 15 What is the probability that the annual
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is started. All of the data that used to be input into the old system‚ now goes into the new one. (13) Normal Data Values the system should accept it‚ process it‚ and we can then check the results that are output to make sure they are correct. Extreme Data Values the values are chosen to be at the absolute limits of the normal range. Extreme values are used in testing to make sure that all normal values will be accepted and processed correctly. Abnormal Data Values This is data that should not normally
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percentile of the distribution of yearly returns. Below 10 percentile = 10% and above 10 percentile=90% b. Find the first quartile. Q‚ and the third quartile‚ O‚‚ of the distribution of yearly returns. 5.43 Under what condition may we use the normal approximation to the binomial distribution? if and ‚ binominal random variable x趨近於常態分配 5.47 An advertising agency conducted an ad campaign aimed at making consumers in an Eastern state aware of a new product. Upon completion of the campaign‚ the
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The monthly demand for this product has a normal distribution with a mean of 100 and a standard deviation of 30. The store adopts a continuous review policy in which the order quantity equals the average demand for one month and the reorder point equals 43 boxes. The lead time for an order is one week‚ where each month contains exactly four weeks. a. What is the cycle service level for this product? (see appendix for the look-up tables of a standard normal distribution) b. What is the fill rate for
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University of Phoenix Material Time to Practice – Week Two Complete Parts A‚ B‚ and C below. Part A 1. Why is a z score a standard score? Why can standard scores be used to compare scores from different distributions? 2. For the following set of scores‚ fill in the cells. The mean is 74.13 and the standard deviation is 9.98. Raw score Z score 68.0 ? ? –1.6 82.0 ? ? 1.8 69.0 ? ? –0.5 85.0 ? ? 1.7 72.0 ? 3. Questions 3a through 3d are based on a distribution of scores with and the standard
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Statistics for Management Unit 9 Unit 9 Testing of Hypothesis in Case of Large and Small Samples Structure: 9.1 Introduction Objectives Relevance Assumptions 9.2 Testing Hypothesis Null and Alternate hypothesis Interpreting the level of significance Hypothesis are accepted and not proved 9.3 Selecting a Significance Level Preference of type I error Preference of type II error Determine appropriate distribution for the test of Mean 9.4 Two–tailed Tests and One–tailed Tests
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The linear probability model‚ ctd. When Y is binary‚ the linear regression model Yi = β0 + β1Xi + ui is called the linear probability model. • The predicted value is a probability: • E(Y|X=x) = Pr(Y=1|X=x) = prob. that Y = 1 given x • Yˆ = the predicted probability that Yi = 1‚ given X • β1 = change in probability that Y = 1 for a given ∆x: Pr(Y = 1 | X = x + ∆x ) − Pr(Y = 1 | X = x ) β1 = ∆x 5 Example: linear probability model‚ HMDA data Mortgage denial v. ratio of debt payments to income (P/I
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marks) Sandra Enright of Techtronics Inc.‚ an electronics supply firm‚ has been examining the times required for stock pickers to fill orders requested from inventory. She has determined that individual order-filling times approximately follow a normal distribution with a mean value of 3.2 minutes and standard deviation of 68 seconds. a) What is the probability that a randomly selected order will require more than three minutes? b) What is the probability that a randomly selected order will
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