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Question 1. Compute the standard deviation of the stock returns of California REIT and Brown Group during the past 2 years.
I must construct a graph showing the relationship between two variables, X & Y
Which of the following is the best example of "how should goods and services be produced"?
Are there “diminishing returns” to the advertising expenditure, that is, after a certain level of advertising expenditure (the saturation level) it does not pay to advertise? Can you fin
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 (βoˆ and &bet
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 expon
I need 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 which attempt to expla
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 Capit
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 th
If the first unit takes 24 hours to complete and you expect a 90% learning curve, how long will it take to complete the 14th unit? How long will it take all 14 units? If the 3rd unit takes 141 hours
Question 1: Estimate a linear relationship between life insurance (Y) and income (X). Question 2: Discuss the relationship you estimated in (1). In particular:
Under what conditions might the presence of multicollinearity cause problems in the use of this regression equation in designing a marketing plan for appliance sales?
Explain the differences in using these different models. How could CoffeeTime further optimize this model?
Which of the following statements is NOT correct about OLS method? - It finds the line that maximizes the sum of the squared deviation of each data point from the line. - It finds the line that minimi
Multicollinearity refers to the existence of correlation among the independent variables in a multiple regression model. Discuss how multicollinearity can impact your regression analysis.
Suppose Pz = $30. Determine the supply function and inverse supply function for good X. Graph the inverse supply function.
How can you still figure out which is the correct pair of values for beta-0 and beta-1?
F-test measures the statistical significance of each explanatory variable.
Problem 1: Which regression method is most frequently used for short run cost estimates? Problem 2: What are the problems you might encounter? How can you overcome these problems?
Problem: The presence of autocorrelation leads to all of the following undesirable consequences in the regression results except:
Problem: The application of the least-squares procedure to a multiple linear regression equation requires that:
As a natural experiment to determine the effect of education on earnings, a researcher compares the schooling and educational attainment of two groups of people.
According to compensating differential theory: (1) Should a job with health insurance pay more than a job without (holding all else constant)?
You are worried about multicollinearity in your regression model. In particular, you are worried that X2 and X3 are collinear. You compute the correlation coefficient: r(X2,X3) = - 0.82.
(a) Calculate the t-statistics and discuss which variables are statistically significant. (b) What do the estimates imply is the percent wage increase associated with an additional year of schooling?