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# Regression Analysis

### Correlation and regression

In your own words, tell me what is the major difference between correlation and regression. There are a couple of differences, but one really stands out however, there are some concepts which could use clarification.

### Regression

Is this regression significant? How do you know? Please see the attached file.

### Regression Questions

Please see the attached file for complete questions. 1. The following results were obtained as part of a simple linear regression analysis. We wish to test Ho: &#946; = 0. The computed value of the test statistics is ________ 2. The following results were obtained as part of a simple linear regression analysis. For

### THE NASDAQ stock market includes small-and medium-sized companies, many of which are in high-tech industries.

THE NASDAQ stock market includes small-and medium-sized companies, many of which are in high-tech industries. Because of the nature of these companies, the NASDAQ tends to be more volatile than the Dow Jones Industrial Average or the S&P 500. The weekly values for the NASDAQ during the first 20 weeks of 2006 are listed in the d

### Regression

What are the requirements that must be met for a regression analysis? What happens if these requirements are violated? Why is analysis of residuals important? Examples would be great.

### The table above gives the average U.S. credit card debt (in dollars) per household.

Please see the attached file. 8. Consumer Debt Credit card debt has risen steadily over the years. The table above gives the average U.S. credit card debt (in dollars) per household. Years are represented as the number of years since 1900. (The table above includes all credit cards and U.S. households with at least one credi

### The Acme corp. wished to predict maintenance costs per year on its factory equipment by knowledge of the equipment's age.

The Acme corp. wished to predict maintenance costs per year on its factory equipment by knowledge of the equipment's age. The following data was collected which yielded the regression equation: (see the printout attached) Age Maintenance Costs 6 920 7 1810 1 230 3 400 6 1260 a) What is the point estimate of maintenanc

### Regression analysis was applied between demand for a product

Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained. Y = 130 - 20 X Based on the above estimated regression equation, if the price is increased by 2 units, then demand is expected to decrease by 90 units i

### Scatterplot and Trendline

13. The following data are prices for custom homes comparing square feet (given in hundreds) and price (in thousands). Square Feet Price 26 259 27 274 32 315 29 296 29 325 34 380 32 359 40 523 22 215

### Sample regression coefficients

Find the following: (a) Compute the sample regression coefficients bo and b1. (b) Compute the estimated variance of the regression. (c) Compute the standard error of the regression. (d) Compute the estimated variance of b1. (e) Compute the standard error of b1. Year y = book value per share x = earning per share 1980

### Regression Model Relating

A regression model relating x, number of sales persons at a branch office, to y, annual sales at the office (\$1000s), has been developed. The computer output from a regression analysis of the data follows. The regression equation is Y = 80.0 + 50.0X Predictor Coef Stdev t-ratio Constant 80.0 11.333 7.

### Regression

The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of the time it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time, in hours,is stored in the file INVOICE.xls(see attachment).

### Model to Predict the Assessed Value of Houses

Please see the attached file. You want to develop a model to predict the assessed value of houses, based on heating area. A sample of 15 single-family houses is selected in a city. The assessed value (in thousand of dollars) and the heating area of the houses (in thousands of square feet) are recorded, with the following res

### Various Regression Questions

Please help with the attached questions. 12. 48 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 two tailed test for zero slope, and use Appendix D to find the critical value at &#945; = .05.

### Multiple regression analysis and hypothesis testing problems

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 indi-cates the number of client contacts last month, and th

### Multiple Regression for DJIA

Consider the following regression model: ? D = percent change in DJIA (Dow Jones Ind. Avg.); ? O = per barrel price of oil; ? I = interest rates (in real number percentages: 6%, etc); ? E = corporate earnings growth rate; ? G = GDP growth rate. ? R2 = 0.8500 ? F = 24 ? F(Se) = 1.0 ? D = 2.0 - 3.0I + 1.5E - 1

### You are the general marketing manager of Ford Motor company.

You are the general marketing manager of Ford Motor company. The CEO of the company asked you to assess the viability of producing alternative fuel automobiles (ex, ethanol). What types of forecasting techniques would you use to forecast sales? Should you determine that regression analysis may be beneficial in addressing this qu

### Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.

3. Bi-lo Appliance Stores has outlets in several large metropolitan areas. The general sales manager plans to air a commercial for a digital camera on selected local TV stations prior to a sale starting on Saturday and ending Sunday. She plans to get the information for Saturday-Sunday digital camera sales at the various outlets

### Linear Regression Analysis and Hypothesis Testing

I need your assistance with a linear regression analysis and a regression hypothesis test on my data. My hypotheis statement is: "Is there a difference in earnings between women with a two-year or four-year college degree?" Ho, they are the same and Ha, is equal to or greater than Ho. This is my data, 2 year degree earnings are

### Tree diagram: A. Perform a decision tree analysis of Steeley Associates' decision situation using expected value, and indicate the appropriate decision with these criteria. B. Indicate the decision you would make, and explain your reasons.

Case Problem #2 Steeley Associates, Inc. a property development firm, property development firm purchased an old house near the town square in Concord Falls, where State University is located. The old house was built in the mid-1800s, and Steeley Associates restored it. For almost a decade, Steeley has leased it to the univer

### Correlation, Regression Analysis, Coefficient of Correlation

(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

### Time-Series Analysis in Excel

Make an Excel graph of the data on U.S. online advertising spending. (b) Discuss the underlying causes that might explain the trend or pattern. (c) Use Excel, MegaStat, or MINITAB to fit three trends (linear, quadratic, exponential) to the time-series. (d) Which trend model do you think is best to make forecasts for the next 3 y

### Bivariate Regression in Excel

(a) Make an Excel scatter plot. What does it suggest about the population correlation between X and Y? (b) Make an Excel worksheet to calculate SSxx , SSyy , and SSxy. Use these sums to calculate the sample correlation coefficient. Check your work by using Excel's function =CORREL(array1,array2). Find t.05 for a two-tailed tes

### Scatterplot and regression

Please see attachment! Use the data from Exercise #12.3 below. (a) Plot a scatter diagram, (b) Show the equation on the plot using the trendline option of Excel, (c) State the value of the slope, and (d) State the value of the intercept. Use the data from Exercise #14.1 (see below) and (a) Plot a scatter dia

### Forecasting - Linear Regression

I'm working on linear regression and I'm stuck on the equation because I'm coming up with a negative number which I don't think is an accurate forecast. The problem also asks for error tests, which I think I have the correct formulas for and will work once the first part is done. Please help! Full details and questions attached

### Regression analysis between work fatalities and unemployment

A highway employee performed a regression analysis of the relationship between the number of construction work-zone fatalities and the number of unemployed people in a state. The regression equation is Fatalities _ 12.7 _ 0.000114 (Unemp). Some additional output is: Predictor Coef SE Coef T P Constant 12.726 8.115 1.57 0.134

### What is the "up-and-down" variation, the periods of prosperity followed by recession that occurs over extended periods of time?

Need help on some questions and answers. What is the "up-and-down" variation, the periods of prosperity followed by recession that occurs over extended periods of time? a. secular trend b. seasonal variation c. cyclical variation d. irregular variation What is the variation within a year called? This is variation, s

### Regression and Linear Trend Equations

1. I would like to a use the regression equation: Y'= a + bX Please present the calculations and results and ANOVA Graphs using a scatter diagram

### Statistics Questions

Please see the attached file. 15.2 Teenagers make up a large percentage of the market for clothing. Below are data on running shoe ownership in four world regions (excluding China). Research question: At &#945; = .01, does this sample show that teenage running shoe ownership depends on world region? (See J. Paul Peter and Jer