Suppose you were preparing two-way tables of percentages for the following pairs of variables. How would you run the percentages? Crime rate and unemployment rate
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Suppose you were preparing two-way tables of percentages for the following pairs of variables. How would you run the percentages?
- Crime rate and
unemployment rate
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- The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?Suppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.Dilberts Department Store is trying to determine how many Hanson T-shirts to order. Currently the shirts are sold for 21, but at later dates the shirts will be offered at a 10% discount, then a 20% discount, then a 40% discount, then a 50% discount, and finally a 60% discount. Demand at the full price of 21 is believed to be normally distributed with mean 1800 and standard deviation 360. Demand at various discounts is assumed to be a multiple of full-price demand. These multiples, for discounts of 10%, 20%, 40%, 50%, and 60% are, respectively, 0.4, 0.7, 1.1, 2, and 50. For example, if full-price demand is 2500, then at a 10% discount customers would be willing to buy 1000 T-shirts. The unit cost of purchasing T-shirts depends on the number of T-shirts ordered, as shown in the file P10_36.xlsx. Use simulation to determine how many T-shirts the company should order. Model the problem so that the company first orders some quantity of T-shirts, then discounts deeper and deeper, as necessary, to sell all of the shirts.
- Use the below formula to calculate the CLV for the following: A manager of a cable company wants to determine if it is strategic to acquire the Brett family, by estimating their household-level CLV. The manager estimates that it will cost the company $80 (A) to get the Bretts’ to switch, and the Bretts’ will generate $150 profit each year (M), with a $30 annual marketing cost to retain them (C). The estimated retention rate (r) is 65%, and the current discount rate is 5%.(d) i) CLV= ii) Based on your calculation, are the Brett’s profitable to the cable company?Quarterly sales of a local department store over a 4-year period are given below: Quarters 2016 Q1 Sales (in millions) 500 Quarters 2018 Q1 Sales (in millions) 560 2016 Q2 490 580 2018 Q2 2018 Q3 2018 Q4 2019 Q1 2019 Q2 2016 Q3 570 630 2016 Q4 2017 Q1 2017 Q2 750 720 480 540 500 590 2017 Q3 580 2019 Q3 620 2017 Q4 740 2019 Q4 790 The data shows sign of seasonality. By computing seasonal indices for each quarter, forecast the sales for each quarter in year 2020, given that the estimated sales in 2020 isFor the E-Commerce Retail Sales (Million$) data given in the table below, provide estimates from the 1st Quarter (Q1) of 2016 to the 3rd Quarter (Q3) of 2017 by using two models: 1) Single Exponential Smoothing with α=0.3 2) Moving Average with k=2. Calculate MAPE for each model. Quarter Year Actual Q1 2016 86802 Q2 2016 92004 Q3 2016 93795 Q4 2016 124651 Q1 2017 99491 Q2 2017 106590 Q3 2017 108291 Compare two models above (Single Exponential Smoothing and Moving Average) based on their accuracies. Which forecasting method appears to be better? Using the model you choose, provide forecast for the 4th Quarter (Q4) of 2017. Assuming that this model is overestimating, find the actual value of the Q4 of 2017 based on MAPE value. Some residual graphs from the first forecast model (including wider range of E-Commerce Retail Sales data) are given below. What do these graphs tell about the model? Explain each graph.
- The following table shows the number of televisions sold over the last ten years at a local electronic store. YEAR TV SALES 1 150 2 300 3 480 4 600 5 630 6 640 7 700 8 825 9 900 10 980 Using trend projection, develop a formula to predict sales for years 11 and 12. You have to show all working. You will need to develop a table to calculate the slope and the intercept. Use that formula to forecast television sales for years 11 and 12.Answer in Excel: Consider the data below for the sales of widgets: 1. Using seasonal percentages or seasonal indexes, forecast the sales for each season in year 4, if the annual widgets sales is predicted to be 1500. 2. Develop a regression equation that captures both the trend and seasonality in this data. Use this equation to forecast the sales for each season in year 4. Season Year 1 Year 2 Year 3 Fall 505 240 210 Winter 555 460 365 Spring 400 310 204 Summer 560 450 394The following table shows the number of televisions sold over the last ten years at a local electronic store. Year TV Sales 1 150 2 300 3 480 4 600 5 630 6 640 7 700 8 825 9 900 10 980 i. Using trend projection, develop a formula to predict sales for years 11 and 12. You have to show all working. You will need to develop a table to calculate the slope and the intercept. ii. Use that formula to forecast television sales for years 11 and 12.
- a. Develop a simple linear regression equation to forecast annual sales. For this regression, the dependent variable, Y, is the demand in each year and the independent variable, X, is the index for the yearwhat do the standardized regression weights or coefficients tell you about the ability of the predictors to predict the dependent variable?What is the distinction between a dependent variable and an independent variable?