An aerobic exercise instructor remembers the data given in the following table, which shows the recommended maximum exercise heart rates for individuals of the given ages. (A graphing calculator is recommended.) Age (x years) 20 40 60 Maximum heart rate (y beats per minute) 173 158 143 (a) Find the linear correlation coefficient for the data. (Round your answer to two decimal places.) -1 (b) What is the significance of the value found in part (a)? O The slope of the regression is about half of what the expected value is. O The graph of the regression points passes through none of the data points. O The graph of the regression points passes through all three data points. O The linear correlation coefficient should always be positive. O One of the data points is the y-intercept. (c) Find the equation of the least-squares regression line. (Round your answers to two decimal places.) -0.85x + 187 (d) Use the equation of the least-squares line from part (c) to predict the maximum exercise heart rate for a person who is 69. (Round your answer to the nearest whole number.) 128 x beats per minute (e) Is the procedure in part (d) an example of interpolation or extrapolation? O interpolation

The accompanying data table includes the engine size (in liters) and horsepower (HP) of 20 types of cars sold last year. Engine_Size Horsepower 3.6 246 6.2 501 6.0 435 3.4 262 3.0 258 3.5 243 3.8 321 4.0 309 4.2 362 1.4 142 1.5 124 3.6 308 1.6 155 1.8 167 5.3 422 2.0 157 2.3 185 2.4 227 2.5 183 2.8 259 (b) Estimate the linear equation using least squares. Interpret the fitted intercept and slope. Be sure to include their units. Note if either…

Use the same scales to construct boxplots for the pulse rates of males and females from the accompanying data sets. Use the boxplots to compare the two data sets. Click the icon to view the data sets. 40 50 60 70 80 90 100110 40 50 60 70 80 90 100110 OC. D. 40 50 60 70 80 90 100110 40 50 60 70 80 90 100110 Determine the boxplot for the women's boxplot data. A. В. 40 50 60 70 80 90 100110 40 50 60 70 80 90 100110 OC. OD. 40 50 60 70 80 90 100110 40 50 60 70 80 90 100110

During one shift, the express lane clerk recorded how many times customers violated the "10 items or less" rule for his lane. In particular, he recorded how many items over the limit each violator placed on the conveyor belt. This data is summarized in the histogram below. NOTE: The last class actually represents "7 or more items," not just 7 items. Frequency 12+ 298 ans = 10- a 2 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 # items over 10 What is the frequency of times the limit was exceeded by at least 3 items?

A bike sharing program recorded meteorological factors as part of efforts to understand factors related to bike usage on Sundays. The bike usage and the average temperature (Temp below, in degrees Celsius) on 12 consecutive Sundays is provided below. Usage Temp 2586 6.2 2886 5.3 3850 10.3 7.2 9.8 9.3 17.6 14.7 15.4 3352 3842 3665 4592 4409 4562 <

Find the five-number summary for the following set of data. Data 2 7 9 10 12 12 16 17 21 21 25 Min=Q1=  Q2=  Q3=  Max=

Please answer all sub-parts   A doctor wanted to determine whether there is a relation between a male’s age and his HDL (so-called good cholesterol).  He randomly selected 9 of his patients and determined their HDL cholesterol.  The data is reported in the table below: Age (Yrs) HDL (?μmol/L) 38 57 42 54 46 34 32 56 55 35 52 40 61 42 61 38 26 47      a) Compute the regression equation for HDL as a function of age.    b)Interpret the meaning of the regression parameters.    c) Compute r and r2. Interpret these statistics.    d) What is your opinion of the usefulness of using age as a predictor of HDL?

The mean GPA for a 127 residents of the local apartment complex is 1.6. What is the best point estimate for the mean GPA for all the residents of the local apartment complex?

The data used is from college campuses. The variables used in the analysis below include: crime, total campus crime; enroll, total enrollment; police, employed officers. Use the estimated OLS models to answer the questions below: Model A: In(crime) = -6.631 + 1.270ln(enroll), (1.034) (.110) n = 97; R² = .5804 Model B: In(crime) = -4.794 + .923ln(enroll) (.144) (1.112) n = 97; R² = .632 +.516ln(police), (.149) Using Model A, test the null hypothesis that elasticity of crime with respect to enrollment is unit elastic, i.e. equal to one (against a two-sided alternative). Calculate the t-statistic.

The mean GPA for 102 residents of the local apartment complex is 1.8 What is the best point estimate for the mean GPA for all residents of the local apartment complex?