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# Regression Analysis

### Multiple regression model in Excel

Data Set to be used: Lottery Education Age Children Income 5 15 50 2 41 7 10 26 0 22 0 13 40 3 24 10 9 46 2 20 5 14 40 3 32 5 15 39 2 42 3 8 36 3 18 0 16 44 1 47 0 20 47 4 85 6 10 52 1 23 0 18 51 2 61 0 17 41 2 70 12 9 42 2 22 7 12 53 1 27 11 9 72 1 25 2 16 38 2 43 11 12 41 5 34 2 14 50 3 53 7 9 41 3 20 0 16

### Regression Processing Tool

Using Excel as your processing tool, work through three simple regression analyses. 1. First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Create

### Statistics of simple regression analyses

Using Excel as your processing tool, work through three simple regression analyses. First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Create a

### Correlation Analysis for a Survey

Information: A survey was conducted utilising a questionnaire. Population was 81 persons. Respondents was actually 56 persons. Correlation Analysis was used to test the relationship between several hypotheses. Question: How do compute/state the Significance Values for the Correlations?

### Regression results for a bivariate model

12.59 A common belief among faculty is that teaching ratings are lower in large classes. Below are MINITAB results from a regression using Y = mean student evaluation of the professor and X = class size for 364 business school classes taught during the 2002-2003 academic year. Ratings are on a scale of 1 (lowest) to 5 (highes

### Calculation of Regression and Correlation Coefficient

6. Given the following: Salary (in Thousands) annual absences 22 2.3 23 2.0 25 2.0 27 1.8 31 2.2 32 1.5 34 1.2 37 1.3 40 0.6 a. Graph the data _ b. What is x _ c. What is y d. Find b0 e. Find b1 f. Determine the equation of th

### Regression analysis

Life insurance companies are interested in predicting how long their customers will live, because their premiums and profitability depend on such numbers. An actuary for one insurance company gathered data from 100 recently deceased male customers contained in the file longevity.xls. He recorded the age at death of the customer

### Choice of Cost Driver

Study Appendix 3. Richard Ellis, the director of cost operations of American Micro Devices, wishes to develop an accurate cost function to explain and predict support costs in the company's printed circuit board assembly operation. Mr. Ellis is concerned that the cost function that he currently uses? based on direct labor cos

### Regression and Correlation Business Relationships

A business owner considers the relationship between square footage and monthly sales. Square footage, Sales (1,000s) 380 32 400 37 250 33 320 31 330 29 360

### Regression and Correction

You are investigating the relationship between training (x) and performance (y) for your company's employees. The variable y in the following table represents the average job performance rating verses the number of days of training per year for the employees. Training Time(x) Performance(y) 2.49 147.1 2.57 130.1

### The Solution to Statistics - Regression

In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald's employees. (a) Write the fitted regression equation.(b) State the degrees of freedom for a two- tailed test for zero slope, and use Appendix D to find the critical value at &#945; = .05.(c) What is your conclusion about the slope? (d) Int

### Predictions from the least-squares regression line

Fill in the blank: For these data, temperature values that are greater than the mean of the temperature values tend to be paired with values for electricity use that are ____ (greater than or less than) the mean of the values for electricity use. According to the regression equation, for an increase of one degree Fahrenheit

### F test of a multiple regression model

F test of a multiple regression model To help schedule staffing and equipment needs, a large hospital uses a multiple regression model to predict its 'bed census' , the number of beds occupied at the end of each day. Using hospital records from the most recent days, a total of independent variables are used to find the esti

### F test of a multiple regression model

F test of a multiple regression model To help schedule staffing and equipment needs, a large hospital uses a multiple regression model to predict its 'bed census' , the number of beds occupied at the end of each day. Using hospital records from the most recent days, a total of independent variables are used to find the esti

### F Test of a Multiple Regression Model for a Finance Department

(Let B = beta) 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 17 months of claims data, the company has selected 4 independent variables that it believes are related to accident c

### Hypothesis tests for the correlation coefficient and the slope of the least-squares regression line

Hypothesis tests for the correlation coefficient and the slope of the least-squares regression line The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. For a random sample of Cadets, each bought "new" two years ago and each sold "used" within the past month, the sample correlatio

### Regression Equations and Prediction

For the following data, find the regression equation for predicting Y from X. X Y 7 16 5 2 6 1 3 2 4 9 A) SSX = 25, SP = 20, Y-hat = .8X - 6 B) SSX = 10, SP = 20, Y-hat = 2X - 5 C) SSX = 10, SP = 20, Y-hat = 2X - 4 D) SSX = 1

### Regression model for real estate data

Refer to the data included in the Excel file, which report information on homes sold in the Somewhere, USA, during a recent year. Use the selling price of the home as the dependent variable and determine the regression equation with number of bedrooms, size of the house, whether there is a pool, whether there is an attached gara

### Predictions from the least squares regression line.

Can movie rental revenue be predicted? A movie studio wishes to determine the relationship between the revenue from rental of comedies on DVD and videotape and the revenue generated from the theatrical release of such movies. The studio has the following bi-variate data from a sample of fifteen comedies released over the p

### Multiple Regression Analysis

Problem 1 A regression of attitude toward legalizing marijuana on age (X1) and education (X2) produced the following estimated coefficients and standard errors for a sample of 265 persons: b1 = -6.24 Sb1 = .346 b2 = +0.33 Sb2 = 0.12 Test one-tailed alternatives to the null hypotheses that ß2 > 0; use a = .01. Pro

### Regression models

37. A regional commuter airline selected a random sample of 25 flights and found that the correlation between the number of passengers and the total weight, in pounds, of luggage stored in the luggage compartment is 0.94. Using the .05 significance level, can we conclude that there is a positive association between the two v

### Multiple choice question form regression analysis

Please determine if the question is true or false. If the question is false than give a brief description why T F 1. One of the objectives of simple linear regression is to predict the value of the independent variable X as a linear function of the dependent variable Y. T F 2. Regression analysis is limited to establishin

### Regression analysis problem

The following regression analysis was designed to explain firm revenues from the number of employees, using a company database of 42 firms. Revenues are measured in millions of dollars, while employees represent the number of people. Regression analysis to predict Revenue from Employees. The prediction equation is: Revenue

### Correlation Analysis and Linear Regression

Describe a situation in which a correlation analysis or regression analysis could contribute to a better decision. The situation can be from a work situation, of general interest, or one experienced in a private life situation. Note:This is reffering to formal statistical correlation and linear regression.

### Anova, regression calculations in Excel

1. A research study is documenting the results of an investigation weight loss medication on eight overweight adult males, according to body mass index. Their pre-treatment weight is recorded and compared against their post-treatment weight four weeks later. Pre-Treatment: 185 174 160 225 191 200 172 175 Post-Treatment: 180

### Regression analysis

1. A hospital administrator is reviewing the relationship between the length of in-patient stays, x, in days and the total cost of care, y, in dollars. She collected the following sample data: X= 4 6 1 8 10 Y= 1105 1545 345 2125 2785 (a) Construct the regression model in the form , which is the best fit for this biv

### Multiple Regression in Excel

Problem #1: The Texas Transportation institute at texas A&M university conducted a survey to determine the number of hours per year drivers wasted sitting in traffic. the table below shows the number of hours wasted per year sitting in traffic. Denver Miami San Francisco 70

### Regression ,Hypotheses testing and confidence intervals

1. Scores on a statistics test are normally distributed with a mean of 80 and a SD of 5. The average for a class of 30 is 90. The teacher of that class says that her class has done significantly better than average. a. What null hypothesis would you use to test the teacher's statement? b. What is the mean and the

### Regression model for number of employees

The number of Employees of a major high tech company for 1999-2004 is given below: Year Employees (in 000) 1 45, 600 2 42,200 3 41,100 4 39, 300 5 34,300 6 30,300 Determine the least square trend equation. Estimate the number of employees in 2008. By how much the number of employees decreases (or in

### Regression model

A. develop a regression model that could be used to predict the final average in the course based on the first test grade. b. predict the final average of a student who made an 83 on the first test. c. give the values of r and r2 for this model. Interpret the value of r2 in the content of this problem.