1.)The dataset above represents average height and weights for female babies at certain ages. For the dataset above, write the R code, that would do the following: a.) Create a multilinear regression model that predicts a female baby's age based on both their weight and length. b.)Gives a summary of the main features of your linear regression model which includes RSE, equation of regression line, R^2 and adj(R^2) values and plots the residuals. c.) Predicts a female baby's age who weighs 20 pounds and is 28 inches long.

***PLEASE INCLUDE EXCEL OUTPUT WITH YOUR RESPONSE

You have gathered data from a random sample of fast-food sandwiches in order to better understand how the amount of fat in these sandwiches relates to the amount of carbohydrates in the sandwiches. Your ultimate goal is to construct a regression equation to predict amount of carbohydrates based on amount of fat. If this is your goal, which variable should you put on the vertical axis (or y-axis) of a scatterplot of this data? O When conducting a regression analysis, it makes no difference which variable is on which axis. O Amount of fat, because it is the explanatory variable. O Amount of carbohydrates, because it is the explanatory variable. Amount of carbohydrates, because it is the response variable. O Amount of fat, because it is the response variable.

Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995

The table shows the number of goals allowed and the total points earned (2 polnts for a win, and 1 point for an overtme or shootout loss) by 14 lce hockey teams over the course of a season The equation of the regression line is (a) Find the coefficient of determination,, and interpret the result (b) Find the standard error of the estimate, and interpret the resut Goals Allowed, x Points, y -0.560x 218.067 Use he data to answer the folowing questions 217 213 221 229 260 262 277 205 216 20s 217 208 257 246 66 70 105 105 0 83 47106 103 97 9182 91 88 Inco (a) r-O (Round to three decimal places as noeded.)

The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). Which regression equation is best for predicting city fuel consumption? Why? E Click the icon to view the table of regression equations. Choose the correct answer below. O A. The equation CITY = 6.65 - 0.00161WT + 0.675HWY is best because it has a low P-value and the highest adjusted value of R2. O B. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it has a low P-value and the highest value of R?. OC. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it uses all of the available predictor variables. O D. The equation CITY = - 3.14 + 0.823HWY is best because it has a low P-value and its R2 and adjusted R? values are comparable to…

An oceanographer measured the length, in meters, of a deepwater wave and its speed, in meters per second. The results are shown in the following table. (a) Find the equation of a linear regression line for the data where wave length is the independent variable, x, and speed is the dependent variable. (Round your numerical values to two decimal places.) y= ? (b) Using the equation from part (a), estimate the speed (in meters per second) of a wave that is 200 m long. (Round your answer to one decimal place.) ? m/s