For this case we are going to look at housing starts again, but this time we are going to add another variable to the equation. The historical values below give interest rates, lumber prices (dollars per board-foot) and number of starts. We will compute a multiple regression equation using these variables, with starts as the D
For this case, we will examine some hypothetical data concerning interest rates and the number of housing starts per month. A new "housing start" is counted when a contractor begins construction of a new private house. Create a scatterplot with interest rates on the X-axis and the number of housing starts on the Y-axis. (Fo
1. A sample of 12 homes sold last week in St. Paul, Minnesota, is selected (see table below). Size of Home('000 Sq. Ft) Selling Price ($'000) 1.4 100 1.3 110 1.2 105 1.1 120 1.4 80 1.0 105 1.3 110 0.8 85 1.2 105 0.9 75 1.1 70 1.1 95 A) If we want to estimate selling price based on the size of home, which va
What is the idea behind linear regression? What is it? Why do it? What are some limitations of linear regression?
The fast food restaurant "FRIED CHICKEN POPEYE" periodically offers lunches that include three pieces of chicken, chips, soda and desserts can be eaten in the restaurant or take it elsewhere, special prices. Let Y be the number of lunches sold and X the price. Based on historical observations and calculations in the table below,
Please provide step-by-step solutions for this problem so that when I do my other homework I can figure out how to do problems that have the same kind of context. For the following sets of scores, a) compute the Pearson correlation, and b) find the regression equation for predicting Y from X. X Y 0 16 1 6 2 9 3 0 4 9.
Wages Versus Sales Volume: A Department Store Chain collected data from each of its stores for a month. The date on total wages paid to sales personnel and on sales volume are as follows... (I need help with the attached document file).
For the data below Year Automobile Sales Year Automobile Sales 1990 116 1977 119 1991 105 1998 34 1992 29 1999 34 1993 59 2000 48 1994 108 2001 53 1995 94 2002 65 1996 27 2003 111 (a) Determine the least squares regression line. (b) Determine the predicted value for 2004. (c) Determine the MAD. (d) Determine th
Simple Linear Regression -- Sales "A recent study was conducted to determine the relation between advertising expenditures and sales of widgets for the first year of production. " You would like to determine the effect of your ad expenditures in predicting sales. the following data was colle
Assistance to use algebraic and graphing concepts to solve problems involving real data. Exercise 1.3 39. Internet Recruiting The percentage of fortune Global 500 firms that actively recruited workers on the internet from 1998 through 2000 can be modeled by P(x) = 26.5x - 194.5 percent, where x is the numb
This is a forecasting and regression analysis problem that requires the regression analysis to be done to find the slope and intercept. Also adjust the chart to show the Y variables in excel 2007. Please explain that also. Carpet City wants to develop a means to forecast its carpet sales. The store manager believes that the s
Apply linear regression to population growth forecasting. 1. Use it to predict the population of the U.S. in 2010 and 2020. 2. Discuss mathematical factors that might make those predictions inaccurate. 3. Discuss real-world factors that might make those predictions inaccurate.
Find the equation of the regression line. X|10 8 7 12 14 5 ___________________ Y|20 19 17 25 28 9
Find the equation of the regression line. X|12 14 10 9 15 8 _____________________ Y|29 35 28 23 36 18
PART I. HYPOTHESIS TESTING PROBLEM 1 A certain brand of fluorescent light tube was advertised as having an effective life span before burning out of 4000 hours. A random sample of 84 bulbs was burned out with a mean illumination life span of 1870 hours and with a sample standard deviation of 90 hours. Construct a 95 confide
This is a problem #13, chapter 9 - Regression Analysis, from the textbook by Cliff Ragsdale, "Spreadsheet Modeling and Decision Analysis". This problem requires the use of Excel and the add-in, called Solver. The course is Excel-based and Solver is the optimization application used for all problems. Scatter plot of the data nee
This is a problem #12, chapter 9 - Regression Analysis, from the textbook by Cliff Ragsdale, "Spreadsheet Modeling and Decision Analysis". This problem requires the use of Excel and the add-in, called Solver. The course is Excel-based and Solver is the optimization application used for all problems. Scatter plot of the data nee
This is a problem #7, chapter 9 - Regression Analysis, from the textbook by Cliff Ragsdale, "Spreadsheet Modeling and Decision Analysis". This problem requires the use of Excel and the add-in, called Solver. The course is Excel-based and Solver is the optimization application used for all problems. Scatter plot of the data need
Great news! ABC Advertising has called you in for an interview to join their advertising team. During the interview process, you are expected to solve a linear regression problem. Consider the following data in the table below that show U.S. advertising expenditures in millions of the current U.S. dollars. Based on these
Use regression analysis to set up and solve whether or not college experience really determines someone's salary in the work place. I've sampled a few of my colleagues. Years of college and salary = 2yrs / $30,000 4yrs / $60,000 6yrs / $70,000 6yrs / $80,000 8yrs / $100,000 3yrs / $40,000 4yrs / $70,000 5yrs / $60,
Please see attachment. F test of a multiple regression model The finance department of an automobile insurance company uses a multiple regression model to estimate the total number of accident claims that will be filed each month. Based on the most recent months of claims data, the company has selected independent variabl
How many degrees of freedom are there in this case? Please see the attached file for the fully formatted problem. Hypothesis tests for the correlation coefficient and the slope of the least-squares regression line Newburg Park, Florida is a popular, beach resort town. Property values are fairly high there and, as such, ar
Hypothesis tests for the correlation coefficient and the slope of the least-squares regression line Newburg Park, Florida is a popular, beach resort town. Property values are fairly high there and, as such, are rather well studied. One topic of study has been the relationship between housing prices and distance from the beach.
An electric utility wishes to examine the relationship between temperature and electricity use in its service region during the summer months. The bivariate data below give the maximum temperature (denoted by , in degrees Fahrenheit) and the electricity use (denoted by , in thousands of kilowatt hours) for a random sample of f
12.50) In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two-tailed test for zero slope and find the critical value at α = .05. (c) What is your conclusion about the slope?
Please see attachment for a full description of the problem. A researcher used stepwise regression to create regression models to predict BirthRate (births per 1,000) using five predictors: LifeExp (life expectancy in years), InfMort (infant mortality rate), Density (population density per square kilometer), GDPCap (Gross Dom
13.32) An expert witness in a case of alleged racial discrimination in a state university school of nursing introduced a regression of the determinants of Salary of each professor for each year during an 8-year period (n = 423) with the following results, with dependent variable Year (year in which the salary was observed) and
4-16 Thirteen students entered the undergraduate business program at Rollins College two years ago. The following table indicates what their grade-point averages (GPAs) were after being in the program for two years and what each student scored on one part of the SAT exam when he or she was in high school. Is there a meaningful r
The gym has developed the regression model to forecast demand for trainers Demand = 185 + (.15*advertising expenditures)-(.05*doughnuts) + (.23*swim gear sales) What is the forecast for October, being advertising expendeitures of 1000, doughnut sales of 2450, and swim gear sales of 782 in September?
In regression analysis, if a person spends $20 how much can he expect to win for the below money spent money won 16 330 12 270 18 380 14 300 Would I use excel and what formula would I use?