Linear Regression Application, Interpolation and Extrapolation Use the data and story to answer the following questions The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. X 11.7 8.6 7.2 3.3 2.5 2.3 2.4 0.9 13.9 11.4 10.2 7 5.9 6.1 6.4 4.8 Y x = thousands of automatic weapons y = murders per 100,000 residents Use your calculator to determine the equation of the regression line. (Round to 2 decimal places) Determine the regression equation in y = ax + b form and write it below. A) How many murders per 100,000 residents can be expected in a state with 3.1 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 4.2 thousand automatic weapons? Answer = Round to 3 decimal places.

Check for accuracy and respond the last questions  2. For this problem, use Chapter 11 Data Set 3. We want to know if urban and rural residents both have the same attitude toward gun control. a. What is the null hypothesis? The null hypothesis concludes that there is no difference in attitudes toward gun control between urban and rural residents. b. What is the research hypothesis? The research hypothesis suggests that there is a difference in attitudes toward gun control between urban and rural residents. c. Will you be conducting a one-tailed or a two-tailed test? Why? In this case I would conduct a two-tailed test because i’m interested in whether there is a difference in attitudes toward gun control between urban and rural residents, regardless of which direction that difference follows.   e.- What is the p-value (hint: it is under “sig” in the output table)?  The P-value is 0.44. Do you reject the null hypothesis or fail to reject the null? What do you conclude about urban and…

Challenge The following box plots show monthly average high temperature from January to December in degrees Fahrenheit for two U.S. cities. Which city should you live in if you want the most variability in temperature? City X City Y 10 15 20 25 40 45 50 55 60 10 15 20 25 30 35 40 45 50 55 60 Degrees Fahrenheit Degrees Fahrenheit Which city should you live in if you want the most variability in temperature? O A. City X and City Y, because they have the same variability in te O B. City Y OC. City X

The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Complete parts (a) through (e) below. У, No. of absences, x 1 2 4 6. 7 8 9. Final grade, y 88.8 85.9 83.0 80.6 77.7 73.3 63.5 68.3 65.4 62.6 (Round to three decimal places as needed.) A. For every unit change in the final grade, the number of days absent falls by days, on average. B. For every day absent, the final grade falls by on average. C. For zero days absent, the final score is predicted to be 88.778 . D. For a final score of zero, the number of days absent is predicted to be days. E. It is not appropriate to interpret the y-intercept. (c) Predict the final grade for a student who misses five class periods and compute the residual. Is the observed final grade above or below average for this number of absences? The predicted final grade is |. This observation has a residual of, which indicates that the final grade is average. (Round to one decimal…