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- A producer of pocket calculators purchases the main processor chips in lots of1,000. The producer would like to have a 1 percent rate of defectives but willnormally not refuse a lot unless it has 4 percent or more defectives. Samples of50 are drawn from each lot, and the lot is rejected if more than two defectives arefound.a. What are p0, p1, n, and c for this problem?Suppose 55 percent of the customers at Pizza Palooza order a square pizza, 72 percent order a soft drink, and 48 percent order both a square pizza and a soft drink. Is ordering a soft drink independent of ordering a square pizza? Yes NoA research report concludes that there are significant differences among treatment conditions, with "F(2, 24) = 8.62, p<0.01." If the same number of participants was used in each of the treatment conditions, then how many individuals were in each treatment condition?
- A purchaser of alarm clocks buys them in lots of size 10. It is his policy to inspect 3 clocks randomlyfrom a lot and to accept the lot only if all 3 are nondefective. If 30 percent of the lots have 4 defectiveclocks and 70 percent have only 1, what proportion of lots does the purchaser reject?Flasher Marketing Research (FMR) specializes in assessing the prospects for a women's clothing store in a central hub. Al Flashner, the company's director, explains that he rates a prospect based on good, fair, and bad criteria. Records show that 60 percent of store prospects are good, 30 percent are fair, and 10 percent are bad. Of the stores that had a good prospect, 80 percent of the profits in the first year, from sufficient stores, 60 percent of them made a profit in the first year, and of the stores that had a bad chance, 20 percent made a profit in the first year. Connie's women's clothing store is one of Flashner's customers. Connie's women's clothing store made a fortune in the last year. What is the probability that the shop has a bad prospect?In a public opinion survey, 60 out of a sample of 100 high-income voters and 40 out of a sample of 75 low-income voters supported a decrease in value-added tax, VAT. Conclude at the 5% level of significance that the population of voters favouring a VAT decrease differs between high- and low-income voters. (Where p1 is the proportion of all high-income voters who supported a decrease in VAT; p2 is the same for the low-income voters). The rejection region to test the above hypothesis at the 5% significance level (rounded off to two decimals) is: A. T < -1.96 B. T < -1.64 or Z > 1.64 C. Z < -1.96 or Z > 1.96 D. Z < -1.64 E. None of the preceding
- In a public opinion survey, 60 out of a sample of 100 high-income voters and 40 out of a sample of 75 low-income voters supported a decrease in value-added tax, VAT. Conclude at the 5% level of significance that the population of voters favouring a VAT decrease differs between high- and low-income voters. (Where p1 is the proportion of all high-income voters who supported a decrease in VAT; p2 is the same for the low-income voters). The rejection region to test the above hypothesis at the 5% significance level is: A. T < - 1.96 B. T < - 1.96 or Z > 1.64 C. Z< - 1.96 or Z > 1.96 D. Z < -1.64In a public opinion survey, 60 out of a sample of 100 high-income voters and 40 out of a sample of 75 low-income voters supported a decrease in value-added tax, VAT. Conclude at the 5% level of significance that the population of voters favouring a VAT decrease differs between high- and low-income voters. (Where p1 is the proportion of all high-income voters who supported a decrease in VAT; p2 is the same for the low-income voters). The hypotheses are: A. H0: p1 - p2 = 0 vs H1: P1 - p2 ≠ 0 B. H0: p1 - p2 > 0 vs H1- P1 - p2 < 0 C. H0: p1 - p2 > 0 vs H1: P1 - p2 ≠ 0 D. H0: p1 - p2 ≠ 0 vs H1: P1 - p2 = 0 E. None of the precedingDace is a political analyst for a presidential candidate (Aspirant A) with two strong competitors (Aspirants B and C). She analyzed that B and C have exactly the same chance of winning a seat while A has twice the chance of either B and C. With the given information, what is the chance of A in winning.
- The National Highway Association is studying the relationship between the number of bidders on a highway project and the winning (lowest) bid for the project. Of particular interest is whether the number of bidders increases or decreases the amount of the winning bid. Bidders Price 9.0 5.1 9.0 8.0 3.0 9.7 10.0 7.8 5.0 7.7 10.0 5.5 7.0 8.3 11.0 5.5 6.0 10.3 6.0 8.0 4.0 8.8 7.0 9.4 7.0 8.6 7.0 8.1 6.0 7.8 Given: Correlation of Coefficient: 0.7064 (This is correct) Coefficient of determination: 49.90% (This is correct) ŷ = 11.2360 + (-0.4667)x (This is correct) Create a scatter plot of the data Complete a regression analysis of the relationship. Slope = ______ Estimate the winning bid if there were seven bidders. Winning bid cost ______ millions. Compute the 95% prediction interval for a winning bid if there are seven bidders. [ _____________, ______________]The National Highway Association is studying the relationship between the number of bidders on a highway project and the winning (lowest) bid for the project. Of particular interest is whether the number of bidders increases or decreases the amount of the winning bid. Bidders Price 9.0 5.1 9.0 8.0 3.0 9.7 10.0 7.8 5.0 7.7 10.0 5.5 7.0 8.3 11.0 5.5 6.0 10.3 6.0 8.0 4.0 8.8 7.0 9.4 7.0 8.6 7.0 8.1 6.0 7.8 GIVEN: correlation coefficient: - 0.7064 Slope: -0.4667 Coefficient of determination: 49.90% regression equation: ŷ= 11.2360 + (-4467)x FIND: Estimate the winning bid if there were seven bidders. Winning bid cost _________ millions. Explain. Compute the 95% prediction interval for a winning bid if there are seven bidders. [ _______________ , _______________ ] (Explain).A stock market analyst examined the prospects of the shares of a large number of corporations. When the performance of these stocks was investigated one year later, it turned out that 25% performed much better than the market average, 25%, much worse, and the remaining 50%, about the same as the average. Forty percent of the stocks that turned out to do much better than the market were rated good buys by the analyst, as were 20% of those that did about as well as the market and 10% of those that did much worse. What is the probability that a stock rated a good buy by the analyst performed much better than the average?
