Posted: September 16th, 2022

Q1. In a study on speed control, it was found that the main reasons for regulations were to make traffic flow more efficient and to minimize the risk of danger. An area that was focused on in the study was the distance required to completely stop a vehicle at various speeds. Use the following table to answer the questions.
Assume MPH is going to be used to predict stopping distance.
1. Which of the two variables is the independent variable?   2. Which is the dependent variable?   3. What type of variable is the independent variable?   4. What type of variable is the dependent variable?   5. Construct a scatter plot for the data.   6. Is there a linear relationship between the two variables?   7. Redraw the scatter plot, and change the distances between the independent-variable numbers. Does
the relationship look different?   8. Is the relationship positive or negative?   9. Can braking distance be accurately predicted from MPH?   10. List some other variables that affect braking distance.   11. Compute the value of r.   12. Is r significant at α= 0.05?   13. How well the independent variable is able to predict dependent variable? 14. Explore predictive ability of the model.
Q2. Compute r for the following data and test the hypothesis H0: r 0. Draw the scatter plot; then explain the results.
Q3. Use the data collected on cloud computing. Test the claim that there is a significant relationship between Compatibility and intention to adopt cloud computing.
1. Which of the two variables is the independent variable?   2. Which is the dependent variable?   3. What type of variable is the independent variable?   4. What type of variable is the dependent variable?   5. Construct a scatter plot for the data. 6. Is there a linear relationship between the two variables?
7. Is the relationship positive or negative?  8. Calculate b1and b0 and derive the prediction equation 9. Test the hypothesis for the regression model at α= .05 10. What the values of coefficient of determination ( R2) and multiple correlation coefficient
(r). Interpret the two values. 11. Test hypothesis for the slope at .05

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