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Regression Analysis

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

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

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 analysis for advertising expense.

Ann's furniture store is a family business that has been selling to retail customers in the Chicago area for many years. They advertise extensively on radio, TV, and the Internet, emphasizing the low prices and easy credit terms. The owner would like to review the relationship between sales and the amount spend on advertising.

Regression analysis problems .

A town assessor was trying to determine a relationship between the size of a parcel of land (x) and the selling price (y) the assessor used the data in the following table. Size in acres (x) Selling price in thousands of dollars (y) 0.5 25 1.0 40 1.5 55 2.0 65 2.5 75 3.0 80 a. Draw a scatter diagram. Does the sellin

Regression Analysis

1. You are a college admissions officer, and you have the following data: HS GPA College GPA 2.00 2.50 2.50 1.80 2.70 1.50 3.00 2.00 3.10 2.50 3.20 2.50 3.50 3.00 3.70 2.80 3.75 3.00 3.80 3.90 3.85 4.00 4.00 3.75 These, of course, are High School GPAs and College GPAs (at the end of First Year

Regression analysis in SAS

Problem A high-tech company wants to study the relationship between salary (Y) and some factors such as degree obtained (1=bachelor's degree, 2=master's degree. 3=doctoral degree), year of experience, and the number of persons currently supervised. The data is given as follows. The first column denotes the salary (in thousand

Regression Analysis - Study Time and Exam Score

Using Excel, prepare a linear regression equation for the following data and use it for prediction. A random sample of study times for 12 students tracks hours of study for their advanced tax exam and the percentage grades they subsequently earned on their tax exam. Assume that study times have been compiled over a weekend.

Correlation and regression analysis

1. DEFINE: Correlation 2. Students were asked the following: Imagine that you lost (X dollars) amount of money. How much (Y dollars) would you pay to get it back? Imagine that these are the answers. Calculate the correlation coefficient for the following X - Y pairs. X___ __Y _ 10.00

Regression analysis

Your employer asks you to determine whether current salaries (DV) can be predicted from years of experience (IV) What is the right statistical test one should use and why?

Calculating coefficients

Calculate the following coefficient to see if height and shoe size are correlated: Subject 1: 70 inches, size 90.0 Subject 2: 62 inches, size 6.5 Subject 3: 66 inches, size 8.0 Subject 4: 69 inches, size 7.5 Subject 5: 72 inches, size 8.5

Scatterplots and coefficients and regression analysis

I need help with the attached. It deals with scatter plots. Thank you for you help. ------------------------------------------------------------------------------------------ 1. A value of r = -0.851 shows that there is very little relationship between the two variables being compared. 2. A value of r = 0.158 shows that

Multiple regression model in SPSS.

Problem 1: In an earlier assignment, you estimated a simple t-test to ascertain if IMF lending programs in Latin America served to attract or deter foreign direct investment. Of course, the principal problem with this result is that we really can't say much definitively because we don't control for alternative explanations.

Regression analysis for Managerial Economics Assignment.

Managerial Economics Assignment Below are data on quantity produced at a group of shirt manufacturing plants. Each plant also reports its total cost. This exercise tests your knowledge of empirically verifying economic theory of short-run production cost. a. What is the theoretical regression equation of the short-run to

Correlation analysis in SPSS

Answer all three of the questions below. You must show all of your work .Please do this assignment as a Word document with SPSS output pasted where appropriate. Problem 1: Operationalizing variables can be a challenge. One measure of a country's human rights record is a measure known as the Political Terror Scale. This var

Multiple linear regression in SAS

Data: This data consists of a random sample of 113 hospitals selected from the original 338 hospitals surveyed. Each line of the data set has an identification number and provides information on 11 other variables for a single hospital. The data presented here are for the 1975-76 study period. The 12 variables are: Va

Regression analysis and Confidence interval

Question 1 A random sample of 85 students in Chicago's city high schools take a course designed to improve SAT scores. Based on this sample, a 90% confidence interval for the mean improvement μ in SAT score for all Chicago city high school students taking this course is found to be (72.3, 91.4). Which of the following st

Regression, Linear Correlation and Scatterplots

. 1. Describe in your own words what is meant by "line of best fit." 2. Answer the following: a. What is the relationship between the sign of the correlation coefficient and the sign of the slope of the regression line? b. As the value of the correlation coefficient increases from 0 to 1, or decreases from 0 to -1, how d

Chi square test and regression analysis

1. A researcher selects a random sample of college students and measures the number of hours they spend watching television per week and their grade point average. The results are as follows: X Y Subject # TV hours GPA 1 50 1.90 2 20 2.20 3 19 2.40 4 10 3.30 5 9 2.90 6 14 2.50 7 7

Regression: Degrees of Freedom and Confidence Limits

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 use Appendix D to find the critical value at α= .05. (c) What is your conclusion about the

Independent variable

What is the difference between an independent and a dependent variable? Does a regression model imply causation? Why or why not? Provide an example which provides and independent and dependent variable from your place of work.