describe your dataset: where did you get the data from? what is the dependent variable? what is the unit of measure? what are the independent variables? what are the units of measure? what are your guesses about the correlation coefficients? do you expect them to be positive or negative (test the relationship between the dependent variable and each of the independent variables separately) ? 2. build a simple regression model based on your dataset. run a simple regression with the ols method in excel and calculate the intercept and the slope of the regression (interpret each of them). include the model (the regression equation), the scatterplot and the regression output in your submission file. what is the correlation coefficient? does it match your expectations? 3. what are the sst, ssr, sse values from the anova table of your excel output? what is the coefficient of determination r squared? interpret it. 4. calculate a point estimate for y, a confidence interval for an average value of y, and a prediction interval for a specific value of y based on a chosen value of x (choose any x-value on your own, should be from your data range, to avoid extrapolation). 5. test the significance of the slope coefficient b1 of the regression equation, and find a confidence interval for the regression slope. interpret it.