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Regression Analysis

Mr. William Profit is studying companies going public for the first time

Mr. William Profit is studying companies going public for the first time. He is particularly interested in the relationship between the size of the offering and the price per share. A sample of 15 companies that recently went public revealed the following information. Company Size ($ millions), X Price per Share, Y Company Si

Regression - A mortgage department of a large bank is studying its recent loans.

To answer the following question, please use statistical software like SPSS. Data can be found in the attached excel sheet. 4. A mortgage department of a large bank is studying its recent loans. Of particular interest is how such factors as the value of the home (in thousands of dollars), education level of the head of the h

Regression of Gross Income

To answer the following question, please use statistical software like SPSS. Data can be found in the excel sheet attached. 1. A suburban hotel derives its gross income from its hotel and restaurant operations. The owners are interested in the relationship between the number of rooms occupied on a nightly basis and the reven

Real Estate Regression Equation

Refer to the Real Estate data, which reports information on homes sold in Denver, Colorado, last year. a. Let selling price be the dependent variable and size of the home the independent variable. Determine the regression equation. Estimate the selling price for a home with an area of 2,200 square feet. b. L

Regression, Least squares and Correlation Coefficients

The following table shows the number of workdays absent based on the length of employment in years. Number of workdays absent 2 3 3 5 7 7 8 Length of employment (years) 5 6 9 4 2 2 0 a. What is the independent variable? What is the dependent variable? b. Using Megastat or Excel

Sample Survey on Boat Costs and Buyer Income

5. A sample survey of boat owners in southeast Florida has yielded the following data on boat costs and buyer income. (See Excel attachment for data and solution) a. Compute with statistical software a linear regression of Y on X. How do you interpret the results? b. Interpret the coefficient of correlation squared.

R&D is considered one of the vital components of IT company performance.

Please see attached file for full problem description. R&D is considered one of the vital components of IT company performance. It is common believe that IT R&D spend will directly impact the company revenues. The following data shows the annual IT spending of a company A and annual Revenue (data with one year lag) over the

Statistical Data-Regression, Correlation

Problem: A sales manager for an advertising agency believes there is a relationship between the number of contacts and the amount of sales. To verify this belief, the following data were collected: (SEE ATTACHED DATA FOR THIS PROBLEM-thanks) (a) Create a scatter diagram. Put the independent variable on the X (

Multiple Regression & Correlation Analysis

Please see attached file for full problem description. Ques. 1: Suppose that the sales manager of a large automotive parts distributor wants to estimate as early as April, the total annual sales of a region. Based on regional sales, the total sales for the company can also be estimated. If, based on past experience, it is fou

Real life applications of regression

"What are some examples of practical applications for correlation and regression analysis that might be of use to us?" The goal is to get people thinking about how they can actually use correlation and regression in their real life, and where and how can they can really benefit from these techniques? Please provide ex

Regression, Forecasting, Minimization

Please see attached file. 1. Four alternative manufacturing processes are being considered for our company. The below information on the profitability of the four processes in three different demand levels is provided for your information in order to answer upper management's below listed questions.

Regression Line, RMSE and Interpretation of Slope

A regression (trend) line model is fit to examine the relationship between daily high temperatures (T), measured in degrees, and power consumption (P), and measured in thousands of kilowatt hours in a small Kansas town. The data are collected in the months of July and August. A straight line is found to fit the data relativel

Forecasting, Time Series

The following data show the time series of the most recent quarterly capital expenditures (in billions of dollars) for the 1000 largest manufacturing firms: 24, 25, 23, 24, 22, 26, 28, 31, 29, 32, 37, and 42. a. Develop a linear trend equation for the time series. b. Graph the time series and the linear trend equation.

Examining Regression Analysis

I need to identify a business research issue, problem, or opportunity that can be examined using regression analysis. 1- Prepare a paper examining a regression analysis on your collected data. Begin by describing the research issue, problem, or opportunity and the accompanying data. Then, perform a regression analysis on your

LINEAR REGRESSION AND CORRELATION

Question 1. Refer to the Wage Data which reports information on annual wages for a sample of 100 workers. Also included are variables relating to the industry, years of education, and gender for each worker. Wage Data is at: http://highered.mcgraw-hill.com/sites/0073030228/student_view0/index.html a. Determine the correlatio

Linear Regression and Correlation

LINEAR REGRESSION AND CORRELATION Please note ALL answers and explanation is to be done in EXCEL -no word documents. Question 1: The Bardi Trucking Co. located in Cleveland Ohio, makes deliveries in the great Laes region, the southeast and the Northeast. Jim Bardi, the president, is studying the relations

Linear Regression - Least Squares Line

"The linear regression line is sometimes called the least squares line. Why?" What is the idea of "least squares"? What is the connection between "least squares" and linear regression? Could "least squares" and regression be generalized to more complicated cases than lines?

Regression - College Graduation Rates

Regression problem must be neatly prepared and typed (double spaced) with all relevant printouts from SPSS included. You MUST refer to your SPSS printout in each section, clearly explaining what you did and what were the results. consider a simple regression model (using only one independent variable) and will include 3 part

Business Statistics : Hypothesis Testing, Regression and Data Analysis

1. Descriptive statistics 1.1 The variable "Stock" is the stock price of a company quoted on an international exchange. Give summary statistics for price and daily returns and comment your results. The information you produce should be contained in two pages maximum for tables and eventually graphs and one page for comments. 1

Correlation Coefficient

Four research participants take a test of manual dexterity (high scores mean better dexterity) and an anxiety test (high scores mean more anxiety). The scores are as follows. Person Dexterity Anxiety 1 1 10 2 1 8 3 2 4 4 4

The declaration of sleep is X and TV viewing is Y

Please perform the following statistical operations on the data provided in the attachment and compile your results in a Microsoft Word document: 1. Organize the data and create a scatter diagram 2. Calculate the correlation coefficient in terms of r 3. Determine the standardized regression coefficient 4. Predict fiv

Workplace Regression Analysis

Set up and solve a problem related to your workplace that is amenable to the use of regression analysis and solve it using regression analysis. Show all work.

Graphing JTI's costs

See attachment for sample of graph and graph the month of April figures, please explain 1. why you use the method you choose 2. Are the cost more correlated with out units production or set up? Units Produced Cost Driver Month Units Produced Production Cost February 1950 $14900 March 2050 $14950 April* 8

Linear Regression Analysis

The Skelton Manufacturing company recently did a study of its customers. A random sample of 50 customer accounts was pulled from the computer records. Two variables were obser4ved: y = Total dollar volume of business this year x = Miles customer is from corporate headquaters The following statistics were computerd: