- In the R programming language, we would like to use the dataset called iris to build a simple linear regression model topredict
Sepal.Length based onPetal.Length.
- Calculate the least squares regression line to predictSepal.Length based on Petal.Length. Interpret the slope of the linein the context of the problem. Remember that both variables aremeasured in centimeters.
- Plot the regression line in a scatterplot of Sepal.Length vs.Petal.Length.
- Test H1: ??1 ≠0 at ?? = 0.05 using both a??-test and an ??-test. Report the test statistics and interpretthe results.
- Visually check the normality assumption. Does it seemreasonable here?
- Visually check the constant variance assumption. Does it seemreasonable here?
- Interpret this regression model’s ??2.
- Using the regression line, what would you predict as theSepal.Length for an iris with a Petal.Length of 3.4 cm?
- We would expect approximately 95% of the irises to have aSepal.Length within ± (fill in the blank)  cm of theirpredicted values from the regression line.
Answers should be in the form of R code on how to accomplisheach part and include the correct statistical explanation for thosethat require it in the question. Please be as thorough as possible.Thank you so much!!!
