Use exponential regression to fit the following data set. 12 3 4 5 8.8 7.0 5.6 4.5 3.6 model. (Round the values to two decimal places.) x y Give the exponential y = 6.48 x 0.98* Oy = 10.96 x 0.80* Oy = 8.8 x 0.92* y = 3.6 x 1.06* O y = 1.21 x 1.2* X Plot the data along with the model.

The following table of values gives a company's annual profits in millions of dollars.  Rescale the data so that the year 2005 corresponds to  x = 0. Year 2005 2006 2007 2008 2009 2010 Profits (in millions of dollars) 51.8 63.4 66.3 65.8 62.1 63.8 Find the exponential regression model for this data.

Suppose the estimaited OLS regression is: Happiness = a + b*dailychocolates Now use chocolate consumprion per week instead of days. What is the relationship between the old and new units? How would this affect b (i.e. what is bnew in terms of b)?

The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year.  The analyst ran a simple linear regression in SPSS.  The results are shown below.   The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive? Is the regression coefficient statistically significant? How can you tell?

A logistic regression was used to investigate obesity and poor physical health while controlling for the following variables: age, gender, race, income, health status, education, current smoker, and diet/exercise status.  Justify the use of a logistic regression.

Calculate two lines of regression and calculate a linear regression equation to model the data given below:  years  (1980,1985,1990,1995,2000) Enrolment ( 21,25,29,39,47)

I need the next 3 parts pls!

A student used multiple regression analysis to study how family spending (y) is influenced by income (X1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained.

Explain what a residual is and how this relates to the best-fit regression model.

Write out the full linear model including all dummy variables below. Don’t worry about estimating regression coefficients just yet. Feel free to abbreviate variable names so long as they are clearly distinguishable.