1. Efficiency in a manufacturing process is crucial for the profitability of firms in competitive markets. Currently, one particular stage of the process requires 130 seconds to complete. In an effort to improve efficiency, a number of employees have developed a new approach. Their goal is to reduce the amount of time required to less than 125 seconds. After making the appropriate adjustments and operating on the new system, they collect a sample of production times for 50 units. The summary statistics are below. You are required to perform two tests: First, perform a test to determine if they've succeeded at reducing the amount of time required relative to the current standard. Second, perform a test to determine if they've achieved their goal. Use a 5% level of significance for both tests. Be sure to include all necessary steps AND briefly discuss the implication of committing either a Type I or Type II error (whichever applies to your conclusion) for each test. Completion Time (seconds) Mean 117.97 Standard Error 5.53 Median 119.28 Standard Deviation 39.10 Sample Variance 1529.07 Count 50.00 Confidence Lvl (95.0%) 11.11
2. A designer of commercial retail space is performing a study to determine whether there is a difference in the amount of time customers wait in line ups at the tills in three different departments: Grocery, Toys, and Electronics. This information will be used to help inform the decision of where to place express and selfcheckouts. The following table contains summaries of their samples. Data is measured in minutes. Grocery Electronics Toys Mean 4.94 5.76 8.38 Std Error 0.72 0.52 0.42 Median 5.55 5.85 8.14 Std Dev. 2.03 1.47 1.18 Sample Var. 4.14 2.17 1.40 Range 6.92 4.36 3.10 Count 8 8 8 Perform the appropriate test. Be sure to include all necessary steps and a complete ANOVA table. Comment on whether a Fisher's LSD is required and why or why not, but do not perform one.
3. 

The following regression equation states that quantity demanded of a good [(1.1]. measured in number of units. is a function of its own price {Pr}. the price of a related good {Pf}. advertising expenditures {A}, average household income 1M] and time of year. Time of year is measured quarterly using dummy variables. The first quarter {January through March} is the base case. Second quarter {April through June] is identified with dummy [1; = 1. the third quarter {July through September} is identified with dummy (1; = 1, while the fourth quarter {October through December] is identied with dummy Co = 1. E(Qd} = 13:] + 1313: + 32% + 133-4 + .34\" +ss+3eos+sr04 Prices are measured in dollars, while advertising and income are measured in thousands of dollars. The results of the estimated regression and its residuals can be found on page E- of this exam. a) Write the estimated regression equation. b) Interpret the estimated coefcients on its own price (Pal, the price of a related good (P3,) and on Q4. c) Interpret the interval estimates of the coefcients on income {M}, and on Q3.