what slope represents the linear regression

Compute the least-squares regression line for predicting the price of milk from the price of eggs. Round the slope and -intercept to at least four decimal places.

Finally, the researcher considers using regression analysis to establish a linear relationship between the two variables – hours worked per week and yearly income. (a) Estimate a simple linear regression model and present the estimated linear equation. Display the regression summary table and interpret the intercept and slope coefficient estimates of the linear model. (b) Display and interpret the value of the coefficient of determination, R-squared (R2).   Data Hours Per Week Yearly Income ('000's) Class  18 43.8   13 44.5   18 44.8   25.5 46.0   11.5 41.2   18 43.3   16 43.6   27 46.2   27.5 46.8   30.5 48.2   24.5 49.3   32.5 53.8   25 53.9   23.5 54.2   30.5 50.5   27.5 51.2   28 51.5   26 52.6   25.5 52.8   26.5 52.9   33 49.5   15 49.8   27.5 50.3   36 54.3   27 55.1   34.5 55.3   39 61.7   37 62.3   31.5 63.4   37 63.7   24.5 55.5   28 55.6   19 55.7   38.5 58.2   37.5 58.3   18.5 58.4   32 59.2   35…

The age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150