Use the dataset gradesTV in the package openintro.

(a) Describe the variables in the dataset - what units are used. (you can use the h command).
(b) Fit a linear model of Grades on TV plot the data with the regression line.
(c) Plot the standardized residual plot and comment on the validity of the assumptions.
(d) Identify possible outliers, explain why you think they are outliers.
(e) Fit the model to the data without the outliers. Describe the difference between the i model and the original model.
(f) Do you think it is legitimate to remove these outliers?

Find and simplify the difference of the golden ratio and its multiplicative inverse

I'll give brainliest if you answer right : )

The table shows population statistics for the ages of best actor and best supporting actor winners at an awards ceremony. the distributions of the ages are approximately bell-shaped. compare the z-scores for the actors in the following situation. best actor best supporting actor muequals42.0 muequals49.0 sigmaequals7.3 sigmaequals15 in a particular year, the best actor was 59 years old and the best supporting actor was 45 years old. determine the z-scores for each. best actor: z equals best supporting actor: z equals (round to two decimal places as needed.) interpret the z-scores. the best actor was (more than 2 standard deviations above more than 1 standard deviation above less than 1 standard deviation above less than 2 standard deviations below) the mean, which (is not, is) unusual. the best supporting actor was (less than 1 standard deviation below more than 1 standard deviation above more than 2 standard deviations below more than 1 standard deviation below) the mean, which (is is not) unusual.