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    Regression Analysis

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    Multiple regression equation. Given the computer output from a regression analysis, write the regression equation, describe the variables, and decide of some of the variables should be eliminated from the equation.

    Thompson Machine Works purchased several new, highly sophisticated machines. The production department needed some guidance with respect to qualifications needed by an operator. Four variables were listed. X1 = Length of time employee was a machinist X2 = Mechanical aptitude test score X3 = Prior on -the-job rating X4 = A

    Bivariate regression

    Choose the dependent and independent variable. Use Megastat or minitab to obtain the bivariate regression and required graphs. a) Inspect the residual ploot to check for heteroscedeasticity and report your conclusions b) is an autocorrelation test appropiate for your data? If so, perform one or more tests of the residuals (

    Simple linear regression using MegaStat

    Choose the dependent variable and the independent variable. Use Megastat or Minitab to obtain the bivariate regression and required graphs. a) Are the variables cross sectional data or time series data? b) How do you imagine the data was collected? c) Is the sample size sufficient to yield a good estimate? If not do you th

    Statistics on Freethrows

    Regression analysis of free throws by 29 NBA teams during the 2002-2003 season revealed the fitted regression Y = 55.2 + .73X (R2 = .874, Sxy = 53.2) where Y = total free throws made and X = total free throws attempted. The observed range of X was from 1,620 (New York Knicks) to 2,382 (Golden State Warriors). a) Find the expect

    Regression analysis in Minitab Statistics

    Regression Analysis We want to investigate the relationship of several factors to employees' current salaries. Included in the data is a sample of 37 employees. The first column is an ID. The second column is the time, in months, in their current job (VAR 1). The third column is the time, in years of related job experienc

    Interpreting the stepwise regression output

    Please see the attached file. 13.30 A researcher used stepwise regression to create regression models to predict birth rate (births per 1000) using five predictors, life exp (life expectancy in yeras), inform (infant mortality rate), density (population density per square kilometer), GDP cap (Gross domestic product per capita),

    Correlation analysis ...

    1. (a) How does correlation analysis differ from regression analysis? (b) What does a correlation coefficient reveal? (c) State the quick rule for a significant correlation and explain its limitations. (d) What sums are needed to calculate a correlation coefficient? (e) What are the two ways of testing a correlation coefficient

    Determining Regression Equation: Real Estate Example

    Write out the regression equation (Refer to the Real Estate data) which reports information on homes sold in the Denver, and use the selling price of the home as the dependent variable and determine the regression equation with size of the house, and the distance from the center of the city.

    Hypothesis Testing for the slope of a least squares regression line.

    An advertising firm wishes to demonstrate to potential clients the effectiveness of the advertising campaigns it has conducted. The firm is presenting data from recent campaigns, with the data indicating an increase in sales for an increase in the amount of money spent on advertising. In particular, the least-squares regression

    Regression analysis - Least Squares Regression Line

    What is the least squares regression line equation ? What are the slope and the y-intercept? What is the R-squared value? Conclusion make specific comments and give reasons regarding any similarities or differences in the output results. Which regression produces the strongest correlation coefficient result? Why?

    Forecasting: prediction based on Regression equation

    A regional power company has generated the following regression model for forecasting the total amount of electrical power used by its customers(In megawatt hours) each quarter. Yt=162.6+3.25t-16.26Q1-32.52Q2 +65.04Q3 Qi=1 if the data is associated with quarter i Qi=0 otherwise See attached file for the problem.

    Quantitative Research Methods

    Please see the attached file. 1) Help Elaborate Purpose Statement 100-200 words The dependent variable (Cost of the home in $) is determined by independent variables (Square footage, Number of bedrooms and Age) The most important independent variable in this relationship is the Square footage because the Cost of the hom

    Interpreting Regression Coefficients

    A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables y = sales price (in thousands of dollars) x1 = total floor area (in square feet) x2 = number of bedrooms x3 = distance to nea

    Correlation, Causation and Regression

    Question 1: What is correlation? Does correlation prove causation? Why or why not? Explain and provide examples to support your explanation. Questions 2: What are the differences between regression and correlation analysis?

    Home Insulation Manufaturer: Regression Coefficients

    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

    Regression Coefficient Tests and Confidence Intervals

    Please answer the following questions: (a) Explain why a confidence interval for the slope or intercept would be equivalent to a two-tailed hypothesis test. (b) Why is it especially important to test for a zero slope?

    Basic estimation techniques

    Given cellar capacity constraints, The Kalamazoo Brewing Company (KBC) currently sells its microbrews in a seven-state area. The company's marketing department has collected data from its distributors at each state. Data on the quantity and price (per case) of microbrews sold in the state of Ohio, as well as the average incom

    Multiple regression

    See attachment. 7. The following equation was estimated as the demand function for gasoline (number of observations equals 1,682, and standard errors are in parentheses): _lnQ = 3.95 - 0.525lnP - 0.263lnAge + 0.129lnY - 0.211lnPc + 0.796LnD - 0.103U + 0.182R_ (1.51) (0.105) (0.920)

    Statistics - Quantitative Decision

    The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the last 6 months. Develop a regression model to predict selling price based on the square footage, number of bedrooms, and age. Use this to predict the selling price of a 10 year old, 2000 square

    Correlation and Regression - Let x be the age of licensed driver in years. Let y be the percentage of all fatal accidents(for a given age)due to failure to yield the right of way. For example, the first data pair says that 5% pof all fatal accidents involving 37year olds are due to failure to yield the right of way. ...

    Let x be the age of licensed driver in years. Let y be the percentage of all fatal accidents(for a given age)due to failure to yield the right of way. For example, the first data pair says that 5% pof all fatal accidents involving 37year olds are due to failure to yield the right of way. X: 37, 47, 57, 67, 77, 87 Y: 5, 8, 10 ,

    Statistics - Regression Hypothesis..

    Dependent Variable (Y axis): The variable that is being predicted or estimated is the account balance Independent Variable (X axis): A variable that provides the basis for estimation is the number of ATM transactions per month. It is the predictor variable. Now I need to perform a regression hypothesis test on the data.

    Time series analysis& Hypothesis testing

    Homework Assignment Question #1: The Prescott Electric Windings Company, which produces medium-scale electric motors for the fishing industry, is concerned about their number of orders over the past several years. Marty Sturgeon, general manager said, "With this decrease in orders I'm worried that I'm going to have to lay

    Energy Consumption and Temperature

    Energy Consumption and Temperature In Data Set 9, use the 10 average daily temperatures and use the corresponding 10 amounts of energy consumption (kWh). (Use the temperatures for the horizontal scale.) Based on the result, is there a relationship between the average daily temperatures and the amounts of energy consumed? Try

    Linear Regression Equation

    Given the following data: Height 71 70.5 71 72 70 70 66.5 70 71 (in) Weight 125 119 128 128 119 127 105 123 115 (lbs) Find the linear regression equation.

    Confidence Limit - 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 twotailed ... [See the attached questions file.]

    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 twotailed test for zero slope, and use Appendix D to find the critical value at α = .05. (c) What is your conclusion about the slope? (d) Int

    Regression: Performing Regression Analysis

    Perform Regression analysis (1) A ($3.76, $3.80)? B ($3.87, $3.89)? C ($3.85, $3.84)? (2) A ($3.87, $3.89)? B ($3.91, $3.93)? C ($3.95, $4.29)? (3) A ($3.98, $3.99)? B ($4.03, $4.05)? C ($3.99, $4.05)? [Please the attached questions file].