Use the attached data set to perform a regression analysis.Be sure to plot the data and plot and include various graphs that would help determine if the data is normally distributed (which is an assumption of ordinary least squared regression). Write-up a short summary in current APA format of the results. Be sure to include the resulting model (equation) for the relationship determined by the regression analysis and an interpretation of the model. At the 0.05 significance level is there evidence of a relation between assessed value and heated area of house?

Hi - will you be able to answer the 3 questions below by Thursday night?i also uploaded the same info in a word doc.1. Chapter 16 Case Study (Foot Locker), pages 618-619. (Start with “Supposing Foot Locker”) Hint: Use the chi-square test of independence formula on page 610 to compute by hand or go to: http://www.physics.csbsju.edu/stats/contingency_NROW_NCOLUMN_form.html (Links to an external site.)Foot Locker in the Shoe MixFoot Locker, Inc., is the world's number one retailer of athletic footwear and apparel. Headquartered in New York City, the company has over 44,000 employees and 3369 retail stores in 23 countries across North America, Europe, Australia, and New Zealand operating under such brand names as Foot Locker, Lady Foot Locker, Kids Foot Locker, Footaction, Champs Sports, and CCS. Foot Locker estimates that it controls about 18% of the U.S. $15 billion athletic footwear market. The company intends to increase its share of the worldwide market by adding additional stores and by growing its Internet and catalog business. In recent years, Foot Locker officials have been rethinking the company's retail mix. Determining the shoe mix that will maximize profits is an important decision for Foot Locker. By the year 2002, in an effort to stock more lower-priced footwear, the company had reduced its inventory of sneakers priced at $120 or more by 50%. DISCUSSION Suppose the data presented below represented the number of unit sales (million $) for athletic footwear in the years 2000 and 2012. Use techniques presented in this chapter to analyze these data and discuss the business implications for Foot Locker. Price Category 2000 2012 Less than $30 115 126 $30-less than $40  38  40 $40-less than $50  37  35 $50-less than $60  30  27 $60-less than $70  22  20 $70-less than $85  21  20 $85-less than $100  11  11 $100 or more  17  18 Suppose Foot Locker strongly encourages its employees to make formal suggestions to improve the store, the product, and the working environment. Suppose a quality auditor keeps records of the suggestions, the persons who submitted them, and the geographic region from which they come. A possible breakdown of the number of suggestions over a 3-year period by employee sex and geographic location follows. Is there any relationship between the sex of the employee and the geographic location in terms of number of suggestions? If they are related, what does this relationship mean to the company? What business implications might there be for such an analysis? Sex Male Female U.S. West 29 43 U.S. South 48 20 Location U.S. East 52 61 U.S. North 28 25 Europe 78 32 Australia 47 29 3. 16.1 The Financial database contains seven different types of companies. These seven are denoted by the variable Type. Use a chi-square goodness-of-fit test to determine whether the seven types of companies are uniformly distributed in this database. 4. 16.2 In the Manufacturing database, is the Value of Industrial Shipments (a four-category variable) uniformly distributed across the database? 5. 16.3 Use a chi-square test of independence to determine whether Control is independent of Service in the Hospital database. Comment on the results of this test. 6. 16.4 In the Consumer database, is Location independent of Region? Use a chi-square test of independence to answer the question. 2. Click this link http://www.physics.csbsju.edu/stats/contingency_NROW_NCOLUMN_form.html Input '6' for number of rows and '2' for number of columns, click 'submit', then you will see a new page with blank cells, type the data in the given problem into those cells, then click 'Calculate now' to see the results. Interpret the results. For supplemental file, click on the following link: BUS6780_M5HomeworkAssignment #2.docx 3. Chapter 12 Case Study (Caterpillar), pages 471-472, question 1 only. Use an alpha of .05. You need to submit your supporting formula work or work in Excel. The United States Department of Agriculture (USDA), in conjunction with the Forest Service, publishes information to assist companies in estimating the cost of building a temporary road for such activities as a timber sale. Such roads are generally built for one or two seasons of use for limited traffic and are designed with the goal of reestablishing vegetative cover on the roadway and adjacent disturbed area within ten years after the termination of the contract, permit, or lease. The timber sale contract requires out sloping, removal of culverts and ditches, and building water bars or cross ditches after the road is no longer needed. As part of this estimation process, the company needs to estimate haul costs. The USDA publishes variable costs in dollars per cubic-yard-mile of hauling dirt according to the speed with which the vehicle can drive. Speeds are mainly determined by the road width, the sight distance, the grade, the curves and the turnouts. Thus, on a steep, narrow, winding road, the speed is slow; and on a flat, straight, wide road, the speed is faster. Shown below are data on speed, cost per cubic yard for a 12 cubic yard end-dump vehicle, and cost per cubic yard for a 20 cubic yard bottom-dump vehicle. Use these data and simple regression analysis to develop models for predicting the haul cost by speed for each of these two vehicles. Discuss the strength of the models. Based on the models, predict the haul cost for 35 mph and for 45 mph for each of these vehicles. SPEED (MPH) HAUL COST 12-CUBIC-YARD END-DUMP VEHICLE $ PER CUBIC YD. HAUL COST 20-CUBIC-YARD BOTTOM-DUMP VEHICLE $ PER CUBIC YD. 10 $2.46 $1.98 15 $1.64 $1.31 20 $1.24 $0.98 25 $0.98 $0.77 30 $0.82 $0.65 40 $0.62 $0.47 50 $0.48 $0.40