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# Regression

### Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following:

Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following: 1) Multiple R = 0.738 2) R-square = 0.546 By using lagged values she came up with the following: 3) Multiple R = 0.755 4) R-square = 0.57

### Estimation of Demand

In a study of the demand for life insurance, Executive Insurers, Inc. is examining the factors that affect the amount of life insurance held by executives. The following data on the amount of insurance and annual incomes of a random sample of 12 executives were collected. Observation Amount of Life Insurance Annual Income

### Nurses' Salary Determination

The Tampa bay (Florida) Area Chamber of Commerce wanted to know whether the mean weekly salary of nurses was larger than that of school teachers. To investigate, they collected the following information on the amounts earned last week by a sample of school teachers and nurses. Questions: Is it reasonable t

### Cellon case help

Cellon, 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. Please

### Possibilities Curve

Plot the relationship between price and quantity demanded in question 4 on a graph. Is the relationship direct or inverse? On the basis of your graph, estimate how much corn is likely to be demanded if the price is (a) \$1.50, (b) \$2.50 and (c) \$3.50. (Question 4: Suppose that the quantity of corn demanded annually by U.S. co

### Omitted bias + f-stat

The following regression model represents the demand for peanut butter: log qt = B1 + B2 logpt + B3log rt + B4logmt + ut where qt is the quantity of peanut butter consumed at time t; pt is the price of peanut butter; rt is the price of jelly; and mt is income per capita. Suppose an analyst estimates the following model:

### Life Insurance Question

1) One member of the management board claims that for every \$1000 increase in income, the amount of life insurance held will go up by \$5000. Choose an alternative hypothesis and explain your choice. Does your estimated relationship support this claim? Use a 5 percent significance level. 2) Test the hypothesis that as income

### Hypothesis testing

1) One member of the management board claims that for every \$1000 increase in income, the amount of life insurance held will go up by \$5000. Choose an alternative hypothesis and explain your choice. Does your estimated relationship support this claim? Use a 5 percent significance level. 2) Test the hypothesis that as income

### Regression Analysis

A life insurance company wishes to examine the relationship between the amount of life insurance held by a family and family income. From a random sample of 20 households, the company collected the data in the file insur.xls. The data are in thousands of dollars. (a) Estimate a linear relationship between life insurance (Y) a

### Engineering Economics: Regression, Learning Curve

7. Identify the formula for the straight line that describes the relationship between the two variables X and Y from the data below. X 4 5 6 7 8 Y 21 24 25 28 8. You have the following historical costs for an item for the last five years. You believe there is a trend that will continue into

### 9950-econ

Please assist me with the attached. There are two documents posted. The .xls has the data and the regression - see tabs at bottom left. The .doc has the actual problem. The question and background is in black, my answers so far are in blue and the questions I need answered are highlighted in yellow ? they are 6,7,8,9. Dema

### using a regression for the purpose of predicting a future value

We have 3 variables X Y Z X = F (Y, Z) Data is 2000-2005. I use OLS to Estimate the model and get a standard result.. for arguments sake I'll say it is X=3.00 -5.00Y +250Z I want to be able to predict the value of X with what I expect the values of both Y and Z to be in the year 2006. I expect Y to be 50 in 2

### Beta using regression analysis

Think about the risks inherent in your Ficticious Company and how to quantify these risks. Download the data provided and calculate the measure of risk for this company (defined as Beta in the Capital Asset Pricing Model - CAPM) and explain why this calculation is a measure of risk. Discuss when this type of calculation is appro

### Time series data of forty years and makes interesting inferences

I am working on a forecasting model and am struggling to source time-series data on anything except consumer expenditure (which cannot be used). I require an intersting dependent variable sourced from a respectable website (ie - UK Office of National Statistics, etc) as well as 2-4 independent variables sourced from sites whi

### Estimating Demands and Residential Property

In order for me to estimate the demand for residential property, and residential property being my dependent variable what independent or explanatory variables should I include in my regression equation? Please see attached.

### identifying some independent variables

I am doing a project in which I have to create two forecasts for my dependent variable (Stock: Oracle, ORCL). I need to create one forecast using the regression model and the other using exponential smoothing model. What I need help with is identifying the best independent variables for my project. I need some macro level var

### Prove Math (Without Regression as a Proof)

I can prove this problem using regression, but I don't have an equation for it. Please help, thanks! a.) Suppose you multiply all X1 values by 2 in an equation with one independent variable (X1) and a constant. What will be the effect of this rescaling, if any, on the coefficients (SYMBOL1 and SYMBOL2) and their standard erro

### Interpret Models

Please help with this problem that was given in class, I want to say Model II is a better model because it has a better "perfect fit" but I don't think that is the only reason. See the attached file.

### Multicollinearity

Please help with this problem, I want to say that it deals with multicollinearity. Please help me.

### Chow Test

Please see the attached file.

### Dummy Variable Analysis

Salary and Gender - Testing for Discrimination The starting salary (Y) is related to years of education (X), previous work experience (E) and hiring time (T) for 93 employees of a bank. Suppose that you have been hired by a government agency to investigate whether there has been any salary discrimination on the basis of gender

### Multiple Choice Questions-Review

1. As an objective, the maximization of profits ignores A. the timing of cash flows B. the time value of money concept C. the riskiness of cash flows. D. All of the above. 2. Which of the following is the best example of "how should goods and services be produced"? A. the production of a new manufacturing facili

### Graphing

I must construct a graph showing the relationship between two variables, X & Y x: 0 1 2 3 4 5 6 7 ----------------------- y: 50 39 29 20 12 5 0 In my graph I must do the following: 1.Determine whether the relationship is negative or positive 2.I must calculate the slope of the relationship between x & y when x equa

### Relationship between gross income and tax paid

The gross income and tax paid by a cross-section of 30 companies in 1988 and 1989 is given in the file tax.xls (a) Use these data to estimate the relationship for each of the years 1988 and 1989. TAXt= à?1 + à?2 incomet + et (b) Give brief interpretations of the two estimates of à?2 (c) Give brief interpretation

### Regress Dividend Payments

The first file is the 2 problems; the second file is the data for the first problem; and the third is the data for the second problem. Problems must be completed in SAS, or STATA. See the attached file.

### Three-Variable Regression overview

7.9 A three-variable regression gave the following results {see attachment}. (a) What is the sample size? (b) What is the value of the RSS? (c) What are the d.f of the ESS and RSS? ... *Please see attachment for complete list of questions (including 7.12 and 7.15)

### Adjustment Data in Years

Please only do 5.10, 5.14, 5.16 for 5.10 please use this adjusted data for the years of 1984, 1985, and 1986 1984: 89 114.5 1985: 95 120 1986: 104 170 the other years will use the original data

### Economics: need help with the answers to all of the problems on the attachment

All these are multiple choice questions and very simple. Please help in answering these questions. Please see attachment for the questions.

### Case Study on Capital Asset Pricing Model: Beta Management Company

Please see the two attachments - one outlines the questions and the other is the case study (Beta Management Company). 1. Compute the standard deviation of the stock returns of California REIT and Brown Group during the past 2 years. 2. Suppose that Beta's position had been 99% of equity funds invested in the index fund,

### A.What is the marginal propensity to consume(MPC)- the amount of additional consumption expenditure from an additional dollar's personal disposable income? b. Is the MPC statistically different from 1? show the appropriate testing procedure. c. What is the rationale for the inclusion of the prime rate variable in the model? A priori, would you expect a negative sign for this variable? d. Is b(sub 3) significantly different from zero? Why? e. Test the hypothesis that R^2 = 0. Show work. f. Compute the standard error of each coefficient. Show work.

Based on the U.S data for 1965-IQ to 1983-IQ (n=76), James and Adibi obtained the folowwing regression to explain personal consumption expenditure in the U.S. ^ Y = -10.96 + .93X(sub 2t) - 2.09X(sub 3t) t= (-3.33) (249.06) (-3.09) R^2 = 0.9996 F= 83,753.7 where Y = the PC