The table shows the percentage P of an employee's annual salary S, in thousands of dollars, spent on the process of recruiting and training a replacement.    S=annual salary in thousands P=percentage of salary for recruiting 20 14 30 16 40 19 60 46 70 50   Find the equation of the regression line P(S). (Round regression line parameters to two decimal places.

Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion).  Use the horizontal axis for the customer age to graph.  Find the linear regression line that models the data by each type of customer.  Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales.  What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y  / Change in x

Use the data in the table below to complete parts (a) through (d). 39 33 40 47 42 50 59 56 51 24 22 27 32 30 31 31 27 29 Click the icon to view details on how to construct and interpret residual plots. (a) Find the equation of the regression line. (Round to three decimal places as needed.) (b) Construct a scatter plot of the data and draw the regression line. Plot the x-values on the horizontal axis and the y-values on the vertical axis. Choose the correct graph below. OA. В. Oc. OD. 34 70, (c) Construct a residual plot. Plot the x-values on the horizontal axis and the residuals on the vertical axis. Choose the correct graph below. O A. Ов. Oc. OD. (d) Determine if there are any patterns in the residual plot and explain what they suggest about the relationship between the variables. The residual plot a pattern because the residuals about 0. This implies the regression line a good representation of the relationship between the variables.

Cheick is investigating how long his phone's battery lasts (in hours) for various brightness levels (on a scale of 0-100). His data is displayed in the table and graph below. Brightness Level (x) Hours (y) 23 6.7 27 5.9 30 7.3 36 7.2 71 3.8 72 3.6 85 3.1 94 1.9   (a)  Use the Corr/Regression to find the equation for the line of best fit. Round your answers to two decimal places.      ˆy = 8.74 + -0.07x (b)  Interpret the slope in context.  Cheick expects the battery life to go down by 0.07 hours for each increase of 1 in the brightness level. Cheick expects the brightness to decrease by 0.07 for every hour that goes by. Cheick expects his phone battery to last 0.07 hours if he keeps the brightness level at 0. Cheick expects his phone battery to last 8.74 hours if he keeps the brightness level at 0. Correct   (c)  What does the equation predict for the number of hours the phone will last at a brightness level of 36?       6.2 hours    Round your answer to…

Data Set: {(-3, 4), (-2, 3), (–1,3), (0, 7), (1, 5), (2, 6), (3, 1)} 1. The regression line is: y = when the 2. Based on the regression line, we would expect the value of response variable to be explanatory variable is 0. 3. For each increase of 1 in of the explanatory variable, we can expect a(n) in the response variable. 4. If x = -3.5, the y = This is an example of 5. The correlation coefficient is r = (Round to the nearest hundredth.) Check of

Grades on Midterm    Grades on Final79    8464    7676    8385    9170    7586    7960    7975    8781    8263    63 The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x . Round the slope and y-intercept to the nearest thousandth.