Explore BrainMass

Explore BrainMass

    Regression Analysis

    BrainMass Solutions Available for Instant Download

    Regression Analysis using Excel. For the complete description of the problem, please see the specific problem posted. Using Excel as your processing tool, work through three simple regression analysis. 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 graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value? Next, run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the EXTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value? Next, run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the OVERALL job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value? Finally, make very specific comments and give reasons regarding any similarities or differences in the output results. Which regression produces the strongest correlation coefficient result? Why?

    Using Excel as your processing tool, work through three simple regression analysis. 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

    Using Excel for Simple Regression Analyses

    Using Excel as your processing tool, work through three simple regression analyses and use the data from the attached files. 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

    Regression

    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 graph with the trendline displayed. What is the least squares regression line equation?

    Determining values and probability for exercise

    Problem 3 Use three decimal places in your answers for this problem. The following table was collected. Hours of weekly exercise % Body Fat 0 32 3 20 5 18 14 12 Using the above calculate the best fit line and the R value. Show all of your calculations. Problem 4 Use four decimal places in your answers

    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

    Regression Analysis for Pro Football Player Salary

    Seeking a regression analysis on the two pro football team player salaries.... Arizona Cardinals Year Median salary Total Payroll 2006 $ 710,000 $ 105,685,931 2005 $ 455,070 $ 76,539,161 2004 $ 621,424 $ 78,961,345 2003 $ 652,800 $ 81,034,928 2002 $ 383,165 $ 66,967,535

    Hagerty's Furniture Regression Analysis

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

    Coefficient of Correlation and Determination

    A sample of 12 homes sold in St.Paul, Minnesota, is selected. Can we conclude that as the size of the home (reported below in thousands of square feet) increases, the selling price (reported in $ thousands) also increases? Use the MegaStat Scatterplot function in Regression or the Excel Chart Wizard to create a scatter plot, an

    Multiple choice questions from linear regression analysis.

    1. In a study of foreign holding in U.S. banks, year-end share of assets in U.S. banks held by foreigners (as a % of total assets) was related to: X1 = Annual change, in billions of dollars, in foreign direct investment in the U.S. (excluding finance, insurance, and real estate) X2 = Bank price-earnings ratio X3 = In

    Multiple choice question from regression analysis

    1. A car maker developed a new engine and wants to recommend the grade of gasoline to use. The four grades are: below regular, regular, premium and super premium. The test car made 3 trial runs on the track using each grade. Assuming any grade can be used at 0.05 level, what is the critical value of F for the acceptance/rejec

    Forecast based on regression analysis

    A manufacturer of summer clothing has generated the following regression model for forecasting the number of pairs of walking shorts (in hundreds of thousands) that will be sold during the next few quarters: See attached file for full problem description. ^/Yt=4.4+0.13t-0.44Q1+0.88Q2+1.32Q3 Where Q1, Q2 , Q3 and are

    Questions from descriptive statistics, testing of hypothesis,ANOVA etc

    1. The difference between the maximum and minimum observations in the sample is called A. Sample Data B. Sample Mean C. Sample Range D. Sample Interval 2. The area under the normal curve between z=0 and z=1 is ___ the area under the normal curve between z=1 and z=2. A. Less than B. Greater th

    Regression analysis

    The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of fifteen Cadets, each bought "new" two years ago and each sold "used" within the past month. For each Cadet in the sample, we have listed both the mileage, (in thousands of

    Regression Equation and Standard Error

    The Bradford Electric Illuminating Company is studying the relationship between kilowatt-hours (thousands) used and the number of rooms in a private single-family residence. A random sample of 10 homes yielded the following: NUMBER OF KILOWATT ROOMS HOURS 12 9 9 7 14 10 6 5 10 8 8 6 10 8 10 10 5 4 7 7 a. Dete

    Statistics - forecasting

    1. Use the following time-series data to answer the given questions. Time Period Value Time Period Value 1 27 6 66 2 31 7 71 3 58 8

    Regression Analysis Example

    See the attached file. 6. The National Transportation Safety Board collects Data by state (Including the District of Columbia) on traffic fatalities. Part of this data is shown in the following table, along with potentially related factors including populations numbers of licensed drivers, number of resisted vehicles and to

    Test Regression Result of Cobb-Douglas Production Formula

    After a logarithmic transformation, we obtain the following regression result of Cobb-Douglas production formula for a firm: This symbol goes on top: ^ on top of the Ln Qi. Ln Qi = 2.294 +0.3451 Ln Ki + 0.7534 Ln Li a) Estimate the level of output if firm uses 140 units of capital and 230 units of labor. b) Write the

    Correlation and Regression Analysis and Descriptive Models

    1. How can correlation and regression analysis be used to make strategic decisions in a dynamic competitive business environment filled with risk and uncertainty (Consider the relations, either descriptive or predictive that can be accomplished with correlation regression analysis)? 2. What is the difference between a descri

    Managerial Economics -

    Since all the Hawkins Company's costs (other than advertising) are essentially fixed costs, it wants to maximize its total revenue (net of advertising expenses). According to a regression analysis (based on 124 observations) carried out by a consultant hired by the Hawkins Company, Q = -23 - 4.1P + 4.2I + 3.1A where Q is

    Chi-Square and Multiple Regression

    1) A survey was conducted at a university. 30 students randomly selected and asked if they watched football. Their answers (Y=yes, N=no) and their sex (M=male, F=female) follows: Viewing:YNNYYYNYYNYNNYYYNNYNNYNNNYNYNN Sex :MFFMFFMMFMMFFMFMMFMMFMFFFFFMMF Test the hypothesis that "watching football" is independent of "

    Estimating population regression equation

    A market analyst for the Weber Refrigerator Company has visited various appliance stores in a city to get data on the selling price of different brands of refrigerators. Use the following data to help determine whether the selling price in dollars is linearly related to the volume in cubic feet of the refrigerator. Price V

    Sample Regression

    The selling price of a used car is inversely(or negatively) related to the age of the car. That is, as the age increases, the selling price tends to decrease. The following table shows data for 10 cars of a certain make and model : Selling Price (In Dollars) Age (In years) (Y) (X)

    Multiple Regression

    Interpret the following results of multiple regression. Interpret each statistic (b and beta) for each independent variable and the intercept. Provide a complete interpretation using the five-step model of hypothesis testing (25 points). Regression: The Relationship Between Number of Math Courses Taken, High School Grade Po

    Regression Analysis on Half Life

    The half-life of aminoglycosides was measured on 43 patients given either Amikacin or Gentamicin. The data are reproduced in a different form in Table 7.21. (A) Perform a regression to estimate HALF-LIFE using DO_MG_KG for each type of drug separately. Do the drugs seem to have parallel regression lines? (B) Perform the a

    F test of a multiple regression model

    A company that manufactures computer chips wants to use a multiple regression model to study the effect that 4 different variables have on y, the total daily production cost (in thousands of dollars). Let denote the coefficients of the 4 variables in this model. Using 19 observations on each of the variables, the software pr

    Predicting bed census with multiple regression model

    To help schedule staffing and equipment needs, a large hospital uses a multiple regression model to predict its 'bed census' y, the number of beds occupied at the end of each day. Using hospital records from the most recent 30 days, a total of 3 independent variables are used to find the estimated regression model. Let B1, B2