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Part D: Must show all your work step by step in order to receive the full credit; Excel is not allowed.Use the following information from a normal population with mean μ = 52 and variance σ2 = 22.5 to calculate the following questions. find P (X >55 )find P (50≤X≤60)find P (X≤55)A random sample from a population with mean and standard deviation produced the following sample information:n =110 x = 699 s = 20.4Find a 95% confidence interval for the mean μ. Interpret this interval.Find a 99% confidence interval for the mean μ. Interpret this interval.Consider the following hypothesis test.Ho: µ = 17Ha: µ ≠ 17A sample of 25 gives a sample mean of 14.2 and sample variance of 25.At α = 0.05, what is the rejection rule?Compute the value of the test statist
What is the p-value?What is your conclusion?Consider the following hypothesis test.Ho: μ = 15 Ha: μ ≠ 15 A sample of 50 gives a sample mean of 14.2 and sample standard deviation of 5.At α = 0.02, what is the rejection rule? Compute the value of the test statistic z. What is the p-value?What is your conclusion?Consider the following hypothesis testHo: µ ≥ 10Ha: µ < 10A sample of 50 provides a sample mean of 9.46 and sample variance of 4.At α = 0.05, what is the rejection rule?Reject null if z < 1:645Compute the value of the test statisticWhat is the p-value?What is your conclusion?Fill in the table and find the following answers:Months on job (x) Monthly sales (y) thousands of dollars X^2 Y^2 XY (Y-Y ¯) ?(Y-Y ¯)?^2 Y ^ Y-Y ^ ?(Y-Y ^)?^21 0.8 2 2.4 4 7 5 3.7 8 11.3 9 12 12 15 Total Find b_1. Find b_0.Write the estimated regression equation.Interpret the estimated regression equation.Calculate the coefficient of determination (R2).Interpret the coefficient of determination (R2).Calculate the adjusted coefficient of determination (Adjusted R2).A regression model relating x, number of sales persons at a branch office, to y, annual sales at the office ($1000s), has been developed. The computer output from a regression analysis of the data follows.The regression equation isY = 80.0 + 50.0XPredictor Coef Stdev t-ratioConstant 80.0 11.333 7.06X 50.0 5.482 9.12Analysis of VarianceSOURCE DF SS MSRegression 1 6828.6 6828.6Error 28 2298.8 82.1Total 29 9127.4Write the estimated regression equation.How many branch offices were involved in the study?Compute the F statistic and test the significance of the relationship at a .05 level of significance.Predict the annual sales at the Memphis branch office. This branch has 12 sales persons.The following regression equation was obtained using the five independent variables. The regression equation issales = - 19.7 - 0.00063 outlets + 1.74 cars + 0.410 income + 2.04 age - 0.034 bossesPredictor Coef SE Coef T PConstant -19.672 5.422 -3.63 0.022outlets -0.000629 0.002638 -0.24 0.823cars 1.7399 0.5530 3.15 0.035income 0.40994 0.04385 9.35 0.001age 2.0357 0.8779 2.32 0.081bosses -0.0344 0.1880 -0.18 0.864S = 1.507 R-Sq = 99.4% R-Sq(adj) = 98.7%Analysis of VarianceSource DF SS MS F PRegression 5 1593.81 318.76 140.36 0.000Residual Error 4 9.08 2.27Total 9 1602.89(Minitab Software)What percent of the variation is explained by the regression equation?What is the standard error of regression?
What is the critical value of the F-statistic?What sample size is used in the print out?What is the variance of the slope coefficient of income?Conduct a global test of hypothesis to determine if any of the regression coefficients are not zero.Conduct a test of hypothesis on each of the independent variables. Would you consider eliminating outlets and bosses?Computer output:Coefficients Std. Error t-Stat P-valueIntercept 729.8665 169.25751 4.3121659 0.0010099Price -10.887 3.4952397 -3.1148078 0.0089406Advertising 0.0465 0.0176228 2.6386297 0.0216284ANOVAdf SS MS F Significance FRegression 2 12442.8 6221.4 37.56127994 0.00000683Residual 12 1987.6 165.63333 Total 14 14430.4 Se =12.86986 R-sq = 0.862263 R-sq(adj) = 0.8393068Write and interpret the multiple regression equation.Does the model with Price and Advertising contribute to the prediction of Y? Use a 0.05 significance level.Which independent variable appears to be the best predictor of sales? Explain.What is the number of observations used in this study?Assuming that the coefficient on Advertising has Ha: B1 > 0, what statistical decision should be made at 5% level.What is the standard error of estimate? Can you use this statistic to assess the model's fit? If so, how?What is the coefficient of determination, and what does it tell you about the regression model?What is the coefficient of determination, adjusted for degrees of freedom? Explain how this statistic and the statistic referred to in part (f) help you to determine how well the model fits the data.Test the overall utility of the model. What does the p-value of the test statistic tell youFor the following ANOVA table are the results from treating 4 cultures with 6 observations for each culture. The enzymes are contained in test tubes with differing levels of enzymes applied. Please fill in the blank.Source of Variation df SS MS FTreatment 180 Error 60 Total What are the null and alternate hypotheses?What is your decision rule, Use α=0.05Indicate your statistical decision. Is there a difference among the means? A metropolitan bus system sampler's rider counts on one of its express commuter routes for a week. Use the following data to establish whether the rider ship is evenly balanced by day of the week. Let α=0.05 Day Monday Tuesday Wednesday Thursday FridayRider Count 10 34 21 57 44Is the χ2 value significant at 5% level of significanceWrite the conclusion for this question.
A random sample of 35m of the firm's accountants has a mean workday of 8.2 hours with a standard deviation of 0.5 hour. At α = 0.01, can you support the CEO's claim?
The distribution of diastolic blood pressures for the population of female diabetics between the ages of 30 and 34 has an unknown mean μd and a standard deviation σd = 9.1 mm Hg.
Formulate and LP model for this problem using Excel. Sketch the feasible region for this problem using Excel. Find the optimal solution
Is there a significant difference in the average prices for these two different supermarket chains? Test at α = 0.05
What is the probability that the next 100 customers will spend an average of less than $56 on dinner?
Using random numbers of 0.1567, 0.9823, 0.3419, 0.5572 and 0.7758, compute the time required for each of five simulated maintenance checks of the airplane's landing gear.
Do the data indicate that the lengths of one supplier's 2x4's are subject to more variability than those of the other supplier? Assume α = 0.05. (HINT: F Test for Differences in Two Variances)
Suppose that a random requisition is found to have been incorrectly entered. What is the probability that it was processed by data entry specialist 3?
A game involving a pair of dice pays you 3 with probability 17/36, costs you 2 with probability 14/36, and costs you 4 with probability 5/36. What is your probability of losing money in one play of the game?
Build a scatter plot, Find the value of the linear correlation coefficient r, and find the critical value of r using α=0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables.
Sketch and upload the density function for the random variable Y. Be sure to label your axes and provide values on the axes.
Compared for 5 randomly selected days at three plants. Does the data prove a significant difference in mean scrap rates? Which pairs of mean scrap rates differ significantly (3 plants)?
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