Interpreting regression results, matching time periods. Nandita Summers works at Modus, a store that caters to fashion for young adults. Nandita is responsible for the store’s online advertising and promotion budget. For the past year, she has studied search engine optimization and has been purchasing keywords and display advertising on Google, Facebook, and Twitter. In order to analyze the effectiveness of her efforts and to decide whether to continue online advertising or move her advertising dollars back to traditional print media, Nandita collects the following data:
- 1. Nandita performs a regression analysis, comparing each month’s online advertising expense with that month’s revenue. Verify that she obtains the following result:
Required
- 2. Plot the preceding data on a graph and draw the regression line. What does the cost formula indicate about the relationship between monthly online advertising expense and monthly revenues? Is the relationship economically plausible?
- 3. After further thought, Nandita realizes there may have been a flaw in her approach. In particular, there may be a lag between the time customers click through to the Modus website and peruse its social media content (which is when the online ad expense is incurred) and the time they actually shop in the physical store. Nandita modifies her analysis by comparing each month’s sales revenue to the advertising expense in the prior month. After discarding September revenue and August advertising expense, show that the modified regression yields the following:
- 4. What does the revised formula indicate? Plot the revised data on a graph. Is this relationship economically plausible?
- 5. Can Nandita conclude that there is a cause-and-effect relationship between online advertising expense and sales revenue? Why or why not?
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HORNGRENS COST ACCOUNTING W/ACCESS
- The Lockit Company manufactures door knobs for residential homes and apartments. Lockit is considering the use of simple (single-driver) and multiple regression analyses to forecast annual sales because previous forecasts have been inaccurate. The new sales forecast will be used to initiate the budgeting process and to identify more completely the underlying process that generates sales. Larry Husky, the controller of Lockit, has considered many possible independent variables and equations to predict sales and has narrowed his choices to four equations. Husky used annual observations from 20 prior years to estimate each of the four equations. Following are definitions of the variables used in the four equations and a statistical summary of these equations: St=ForecastedsalesindollarsforLockitinperiodtSt1=ActualsalesindollarsforLockitinperiodt1Gt=ForecastedU.S.grossdomesticproductinperiodtGt1=ActualU.S.grossdomesticproductinperiodt1Nt1=Lockitsnetincomeinperiodt1 Required: 1. Write Equations 2 and 4 in the form Y = a + bx. 2. If actual sales are 1,500,000 in the current year, what would be the forecasted sales for Lockit in the coming year? 3. Explain why Larry Husky might prefer Equation 3 to Equation 2. 4. Explain the advantages and disadvantages of using Equation 4 to forecast sales.arrow_forwardThe Northwest regional manager of Logan Outdoor Equipment Company has conducted a study to determine how her store managers are allocating their time. A study was undertaken over three weeks that collected the following data related to the percentage of time each store manager spent on the tasks of attending required meetings, preparing business reports, customer interaction, and being idle. The results of the data collection appear in the following table: a. Create a stacked-bar chart with locations along the vertical axis. Reformat the bar chart to best display these data by adding axis labels, a chart title, and so on. b. Create a clustered-bar chart with locations along the vertical axis and clusters of tasks. Reformat the bar chart to best display these data by adding axis labels, a chart title, and the like. c. Create multiple bar charts in which each location becomes a single bar chart showing the percentage of time spent on tasks. Reformat the bar charts to best display these data by adding axis labels, a chart title, and so forth. d. Which form of bar chart (stacked, clustered, or multiple) is preferable for these data? Why? e. What can we infer about the differences among how store managers are allocating their time at the different locations?arrow_forwardThe controller for Dohini Manufacturing Company felt that the number of purchase orders alone did not explain the monthly purchasing cost. He knew that nonstandard orders (for example, one requiring an overseas supplier) took more time and effort. He collected data on the number of nonstandard orders for the past 12 months and added that information to the data on purchasing cost and total number of purchase orders. Multiple regression was run on the above data; the coefficients shown by the regression program are: Required: 1. Construct the cost formula for the purchasing activity showing the fixed cost and the variable rate. 2. If Dohini Manufacturing Company estimates that next month will have 430 total purchase orders and 45 nonstandard orders, what is the total estimated purchasing cost for that month? (Round your answer to the nearest dollar.) 3. What if Dohini Manufacturing wants to estimate purchasing cost for the coming year and expects 5,340 purchase orders and 580 nonstandard orders? What will estimated total purchasing cost be? What is the total fixed purchasing cost? Why doesnt it equal the fixed cost calculated in Requirement 2? (Round your answers to the nearest dollar.)arrow_forward
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- Measure Maps Silver Lining Inc. has a balanced scorecard with a strategy map that shows that delivery time and the number of erroneous shipments are expected to affect the company’s ability to satisfy the customer. Further, the strategy map for the balanced scorecard shows that the hours from ordered to delivered affects the percentage of customers who shop again, and the number of erroneous shipments affects the online customer satisfaction rating. The following information is also available: The company’s target hours from ordered to delivered is 30. Every hour over the ordered-to-delivered target results in a 0.5% decrease in the percentage of customers who shop again. The company’s target number of erroneous shipments per year is no more than 55. Every error over the erroneous shipments target results in a 0.5 point decrease in the online customer satisfaction rating and an added future financial loss of $600. The company estimates that for every 1% decrease in the percentage of…arrow_forwardThe Paymore Rental Car Agency rents cars in a small town. It wants to determine how many rental cars it should maintain. Based on market projections and historical data, the manager has determined probability distributions for the number of rentals per day and rental duration (in days only) as shown in the following tables: Number of customers per day Probability 0 .20 1 .20 2 .50 3 .10 Rental duration in days Probability 1 .10 2 .30 3 .40 4 .10 5 .10 Design a simulation experiment for the car agency and simulate using a fleet of four rental cars for 10 days. Compute the probability that the agency will not have a car available upon demand. Should the agency expand its fleet? Explain how a simulation experiment could be designed to determine the optimal fleet size for the Paymore Agency. Use the following random numbers in order (from left to right) for the simulation of number of customers per day: 0.62 0.48 0.96 0.86 0.86 0.29 0.79 0.22 0.08 0.62…arrow_forwardMeasure Maps Silver Lining Inc. has a balanced scorecard with a strategy map that shows that delivery time and the number of erroneous shipments are expected to affect the company’s ability to satisfy the customer. Further, the strategy map for the balanced scorecard shows that the hours from ordered to delivered affects the percentage of customers who shop again, and the number of erroneous shipments affects the online customer satisfaction rating. The following information is also available: The company’s target hours from ordered to delivered is 20. Every hour over the ordered-to-delivered target results in a 0.5% decrease in the percentage of customers who shop again. The company’s target number of erroneous shipments per year is no more than 55. Every error over the erroneous shipments target results in a 0.5 point decrease in the online customer satisfaction rating and an added future financial loss of $800. The company estimates that for every 1% decrease in the percentage of…arrow_forward
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