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# Regression Analysis

### 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

### 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 Analysis: Estimation of a regression model and Hypothesis Testing of regression coefficients.

A. Determine the regression equation. b. What is the value of R-squared? Comment on the value. c. Conduct a global hypothesis test to determine whether any of the independent variables are different from zero. d. Conduct individual hypothesis tests to determine whether any of the independent variables can be dropped. e. If

### 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

### 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

### 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

### Problems on Coefficeint of Determination , Coefficient of Correlation

There are 4 different problems on Scatter Diagram , Coefficeint of Determination , Coefficient of Correlation , Regression Equation , Regrssion Coefficients

### 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

### 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

### Regression Equation Negative y-intercept

What does it mean when you have a negative y-intercept in your regression equation? How do you interpert the negative number?

### Evaluating a Regression Equation

Question: What do the slope and y-intercept represent in the regression equation?

### 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

### 1) Tukey stem-and-leaf diagram 2) Analysis of Variance (ANOVA) 3) Least-squares regression line

Question A1: The smoke concentration (in mgm-3) is monitored over a northern industrial region every day at 16.00 hours for 75 consecutive weekdays. The results are tabulated below. Smoke Concentration (mgm-3) 71 85 95 84 65 89 87 73 67 72 96 87 69 42 56 100 68 56 92 65 71 86 6

### 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

### Problems on Confidence Intervals, Statistical Test of Hypothesis, ANOVA, Regression and Forecasting Calculate a 99 percent confidence interval for the mean debt-to-equity ratio. Using the Excel descriptive statistics output given below, find a 95 percent confidence interval for the mean of all possible yields obtained using catalyst XA-100. For each of the following situations, indicate whether an error has occurred and, if so, indicate what kind of error (Type I or Type II) has occurred. For each of the following sample results, determine whether the power plant should be shut down and the cooling system repaired. Define the null and alternate hypotheses using the treatment means M1, M2, and M3 to represent each group. Then test for statistically significant differences between these treatment means. Write the regression equation for the LaborCost (y) and BatchSize (x). What type of seasonal variation do you see in the sales data?

Q1 The bad debt ratio for a financial institution is defined to be the dollar value of loans defaulted divided by the total dollar value of all loans made. Suppose a random sample of seven Ohio banks is selected and that the bad debt ratios (written as percentages) for these banks are 7 percent, 4 percent, 6 percent, 7 percent,

### 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.

### 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

### 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