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    Regression Analysis

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    Interpret the multiple regression analysis

    EXHIBIT 1: A manager at a local bank analyzed the relationship between monthly salary and three independent variables: length of service (measured in months), gender (0=female, 1=male) and job type (0=clerical, 1=technical). The following tables summarizes the regression results: df

    Linear Regression Data and Sales

    Q1. A firm has the following data on Sales and Advertising. I want to estimate the following regression: sales=B0 + B1*advertising; specifically, what is the estimate of the slope term, B1. The following 10 observations are included: Advertising Sales 339 1103 451 921 504 1154

    Calculations for Simple Linear Regression

    6. Following is a table with the set of x-values and their corresponding y-values filled in xi yi xi2 xiyi 1 6 1 7 2 5 3 5 4 4 6 2 7 2 totals __ __ ___ ____ (sum of all values in each column) a. Complete the table. b. Find SSxy c. Find SSxx d. Find the least squares line. e. Calculate SSE f. Calcu

    Regression Equation

    Determine regression equation and estimated sales for attached problem: --- Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample informat

    Regression problem

    Thompson Machine Works purchased several new, highly sophisticated machines. The production department needed some guidance with respect to qualifications needed by an operator. Is age a factor? Is the length of service as a machine operator important? In order to explore further the factors needed to estimate performance on the

    Regression in SPSS

    Assume that you are an analyst for the City of Normalton in 1999. You have been asked by the Mayor to evaluate the effectiveness of two juvenile crime policies: The strict curfew put in place on Jan1, 1994 and The parental responsibility law put in place on March 1, 1994. The police department has provided you with the da

    REGRESSION MODELING IN EXCEL

    Using the BANK.SAV data file, construct a multiple regression model to test whether there is gender discrimination in the bank. The model should include one or more continuous variables and one or more dichotomous variables. Please submit to me the output you generate Describe your rationale for including the variables tha

    Chi-square test and Regression analysis

    1) What is the Chi-square test? Where can you apply it? Please site an example of how it was used and the outcome of the test. I think this could help me better than the book, it is difficult to understand. 2) What is regression analysis and multiple regression? How would they be used in an outpatient setting? Please indentif

    Daniel-James Financial Services Regression

    1. Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and the

    Statistics Problems - Regression Analysis, Autocorrelation, Multicollinearity

    1. Suppose an appliance manufacturer is doing a regression analysis, using quarterly time-series data, of the factors affecting its sales of appliances. A regression equation was estimated between appliance sales (in dollars) as the dependent variable and disposable personal income and new housing starts as the independent varia

    Regression

    Baseballs major leagues honor their outstanding first-year-players with the title "Rookie of the Year." From 1949 to 1994, the overall batting average for Rookies of the Year was .285 far above the major league batting average of .260. However, Rookies of the Year don't do so well in their second year- their overall bating avera

    Statistic Multiple Regression Model. Explain how to further optimize the model

    Bob wanted to build a multiple regression model based on advertising expenditures and price index. based on the selection of all normal values, he obtained the following: 1) Multiple R - 0.738 2) R-Square - 0.546 By using lagged values, he came up with the following: 3) Multiple R - 0.755 4) R-Square - 0.570 Explai

    Regression Equation for Cellulon

    Cellulon, a manufacturer of a home insulation, wants to develop guidelines for builders and consumers regarding the effects (1) of the thickness of the insulation in the attic of a home and (2) of the outdoor temperature on natural gas consumption. In the laboratory they varied the insulation thickness and temperature. A few of

    Determine the regression equation.

    Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and the Y

    Explaining results by the simple linear regression

    A linear regression analysis produced the equation: Profits = - $950 + $85 * no. of development hours a) How large would the profits or losses be if no time is spent in development? b) On average, an extra 20 hours spent in development produces what increase in profits? c) What is the break-even point - the number of hours f

    Decision Tree - Case Study

    In reference to the attached case study: Describe further analysis that might be useful and/or business actions that might be taken based on the decision tree results. Please see ** ATTACHED ** file(s) for complete details!!

    Case Study - Correlational Research, Causation, Practical Use of Results

    Share the practical applications of the study from the Unit 2 Individual Project. How would the results of this survey be used in the workplace? Briefly describe correlational research. Name a variable from this study and one from the workplace that might prove to provide a correlational relationship and explain why you woul

    regression analysis to forecast the number of apartments rented

    Please see attach spreadsheet and use the information in table one to complete questions 1 through 5. Thank you in advance for you assistance. 1. Perform a simple regression analysis to forecast the number of apartments rented, based only on students. 2. Perform a simple regression analysis to forecast the number of apa

    Simple and Multiple Linear Regression

    Download the data file ex1.XLS. It contains a variety of aircraft operating cost data and statistics by aircraft type. All figures are averages for all aircraft operated by US carriers, taken from 2003 Form 41 data. Use the data in this file to perform the analysis of operating costs described below: (A) Use Excel to esti

    Time Series and Forecasting: Example Problem

    Do time series models rely heavily on cause and effect relationships between variables in order to ensure accurate predictions? My understanding is that time series models assume that the future will behave like the past. Is this true? Are they different?

    Multiple regression model testing

    I need to use my attached database to develop a multiple regression model with the dependent variable being the overall job satisfaction. Use gender, age, department, position and tenure with company as the independent variables. I need to provide output of the regression procedure but also the model equation. Also, I

    Correlation and Regression in National Research Institute

    The director of a national research institute belives that more comprehensive institutions have lighter teaching responsibility is and more time for research and scholarship. He develops a measure of institutional comprehensiveness and scholarly productivity for psychology departments. He selects 18 colleges and univ. and these

    Interpreting integrity tests data on a regression analysis

    I need someone to critically assess the relative merits/weaknesses of a economic modeling equation and the subsequent integrity tests performed on the 40 year time series data. Attached is a word document with screenshots of various EViews results/tests/diagrams, etc and an excel file with the associated data. Also attached is t

    Linear regression analysis and correlation: Using this information, construct 95% confidence intervals for the regression parameters b0 and b1 . At .05 level of significance, test the null hypothesis that the population correlation coefficient is 0.

    1. A computer company wants to study the relationship between the number of microcomputers in use in different areas and the number of software packages the company sells in the areas. A simple linear regression analysis of 21 geographical regions reveals the following: b0=12.43, b1= 1.076, s(b0)=13.65, s(b1)=0.083 , SSE (sum of