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Regression Analysis

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

Regression Equations of Real World Value

Please help me with these questions: 1. What is the real world value of the y-intercept and slope in a regression equation? 2. Other than statistics problems, why should I care? 3. I know how to calculate, but what does it really mean when you apply it in a business setting? 4. When you use them in forecasting, how

Business Statistics and Multiple Regression

Using the database (attached file), complete the followings: a) 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. Comment on your analysis (Rsq, Rsq adj, etc). You are to provide not on

Interpreting Regression Analysis Output from EViews

I need to be able to critically assess a regression analysis printout from EViews (sample attached) and be able to identify possible issues - i.e.: - potential heteroskedasticity - potential autocorrelation - potential multicollinearity problem prior to running the specific tool which provides further analysis for one of

Regression: ANOVA

An experiment was conducted to investigate the effect of four treatments, A, B, C and D on the yield of penicillin in a manufacturing process. It was necessary to use a different blend for each application if the four treatments. The results of the yields for this randomised block experiment are given in the table below.

Statistics Problem: Multiple Regression Model

a) 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. Comment on your analysis (Rsq, Rsq adj, etc). You are to provide not only the output of the regression procedure but also the model equ

OLS Regression

Comment briefly what these two boxplots reveal: Dependent variable: log (w) w: wage (earnings per hour) Independent variables: female, union member, non-white, years of schooling, years of experience, experience squared. *(Please see attachment for graphs)

Regression Analysis-Short Essay type

A: What is the significance of the error term in the regression equation? B: What does zero correlation tell you? C: How would you use a histogram to chart residuals? What would this tell you? D: How do you identify outliers in your data? How do they impact your regression equation?

Least Squares Regression

1. A radio disc jockey track of the number of request for songs by a certain artist and the time of day the request calls were made. The data is displayed. Request: 9 0 10 0 5 0 9 5 Time of day: 2p.m. 3p.m. 4p.m.

WHich statistical test

I have a simple question, I think, I just cant remember my stats classes: I need to know which tests to use for the analysis of the following data I have a graph with species of malaria contracted along the x-axis. The y-axis is patient frequency (ie number of patients who contracted that particular species). The patient popu

Linear regression and correlation

4.6 Air Conditioning Repairs. Richard's Heating and Cooling in Prescott, Arizona, charges $55 per hour plus a $30 service charge. Let x denote the number of hours required for a job and let y denote the total cost to customer. a) Obtain the equation that express y in terms of x b) Find b0 and b. c) Construct a table for the

Identify equations for a regression analysis

Our analysis reviews faculty salaries to see if there is in fact a substantial salary difference based upon gender. We have collected data from 1,446 random institutions across the United States. We have obtained salary information for both men and women faculty members, separately, within public, private and church-related in

Develop time-series analysis to confirm or reject the firm's recommendation

U.S. Virgin Islands is a popular tourist destination, particularly during winter months. Tourists come from all over the world. Majority of these tourists typically stay 3- 5 nights in hotels, and spend significant amount of money on a variety of activities including playing golf, scuba diving, snorkeling, and just enjoying th

Marketing Research - Statistics

Problem: We are using a linear regression model (time series) to predict sales of our "WW" brand. Historically, sales of this product for the period 1982 to date (1982 through summer 2003; assume 1982 was year one) have been approximated by the following data (in thousdands of units): Y = 3.984X + 2.994 Sy = .677 r2 (R s

Regression & Least Squares

1. Given the number of contacts and sales made by a company over two months, compare the numbers each month and determine the regression equation and the estimated sales if 40 contacts are made. Also, determine the standard of error estimate ... *(Please see attachment for complete problem and problem #2)

Use the formulas for a regression line to solve the following

Use the formulas for a regression line to solve the following: The following are times in minutes between the duration of an eruption and the length of time before the next eruption at Yellowstone. Predict the interval for the next eruption if the duration of the last one was 2.82 minutes; explain conclusion - Answer is 67.7 but

Interpolation and extrapolation in a linear regression model

The following data has been collected for two variables, X and Y. X Y 5 30 10 41 15 53 20 62 25 67 A simple linear regression model has been constructed using the data in the table and is being used to predict values for the variably Y Of 3, 7, 18 and 35, how do I determine which for variable X would lead to

Regression Equations

I need to figure out the regression equation, the value of Y when X is 7, the slope of the regression equation, the Y-intercept of the regression equation, the coefficient of correlation, and the coefficient of determination.