Sheet1 Price (X)Quantity demanded (Y) 56637 23967 43908 56797 76728 76891 92884 91615 32876 85824 74678 32925 50878 96612 55905 85710 32891 86734 96894 69922 11908 82644 65798...

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Sheet1 Price (X)Quantity demanded (Y) 56637 23967 43908 56797 76728 76891 92884 91615 32876 85824 74678 32925 50878 96612 55905 85710 32891 86734 96894 69922 11908 82644 65798 94940 94741 54828 82560 91660 59766 89730 63903 59506 90618 50847 86816 85805 12659 12777 77777 73899 65553 85553 75767 76720 74849 71551 90627 63967 65528 89829 86553 74774 96655 54602 84756 91720 60725 87532 63932 65591 OpenIntro Here is OpenIntro’s RLab for Chapter 8: http://htmlpreview.github.io/?https://github.com/andrewpbray/oiLabs-base-R/blob/master/simple_regression/simple_regression.html Record and turn in your answers for the On Your Own section. · In questions that ask for a number, give the numerical answer along with what that number describes. Be specific. · In questions that ask for your code input, give the code and also describe what R returns. · In questions that ask for explanation or analysis, provide a reasonably detailed response with evidence supporting your claims. Supplemental Questions The idea of these supplemental questions is for you to run through the mechanics of the above lab with the data sets you chose for WH08. Repeat these steps for each data set. To import your data set into R, save your data sets as .csv files on your desktop or documents folder. Use the file browser in the bottom right corner to locate your file and import it. If you are in RStudio Cloud, you can upload the csv file. Once it is imported you can give a short-hand name to your data set if it has a long name. ::Click here for pictures of these steps:: 1. Create a scatterplot of your two variables with plot(y~x). 2. Generate the line of best fit with model 3. Add a this line to your scatterplot with abline(model). 4. Create a new data set that measures the residuals with residuals 5. Investigate the linearity of your data set: e. Create a scatterplot of your residuals with plot(model$residuals ~ data$x). e. Create a histogram of your residuals with hist(model$residuals). e. Create a qqplot of your residuals with qqnorm(model$residuals). e. Comment on what these graphics tell you about the linearity of your data. 1. Compute the correlation of your data with cor(data$y$, data$x). 1. How do these computations relate to your estimates from WH08?