Please complete the following problems and show all of your work I Two variables are listed Would you expect collected data on these two variables to have a correlation coefficient which is positive, negative, or near zero Explain 1 height and weight 2 upper body strength and distance in the shot put 3 arm length and softball throw for distance 4 age and body temperature 5 standing long jump and vertical jump test score 6 swimming sprint speed and tennis serving accuracy 7 golf score and number of hours spent practicing 8 school grade point average and hours spent watching TV 9 years after graduation and balance on student loans 10 age and income II Correlation scatter plots Make a scatter plot using the following data sets If the sets are correlated, indicate whether the 2 variables are positively correlated, negatively correlated, or not correlated 1 QUESTION Do winning MLB teams have greater attendance at their games The following are statistics from the 2006 MLB Season WINS HOME ATTENDANCE 6015,000 6015,000 7025,000 7722,500 7727,500 8026,500 8725,000 8735,000 9035 000 9031,500 9222,500 9425,000 9430,000 9555,000 2 QUESTION Do the Winning times in the 100 Meter Summer Olympics Run show that men's inning times are correlated with women's winning times (Do NOT graph the year Just graph the men's finishing time and women's finishing time ) YEAR MEN's WINNING TIME WOMEN's WINNING TIME 192810 80 seconds12 20 seconds 193210 3011 90 193610 3011 50 194810 4011 90 195210 5011 50 195610 5011 50 196010 2011 00 196410 0011 40 19689 9511 00 197210 1411 02 197610 0611 08 198010 2511 60 19849 9910 97 19889 9210 54 19929 9610 82 19969 8410 94 20009 6710 75 20049 8510 93 3 Question The weights (in pounds) of eight vehicles and the variability of theirbraking distances (in feet) when stopping on a dry surface are shown Can you conclude that there is a linear correlation between vehicle weight and variability in braking distance on a dry surface WeightVariability In Braking Distance 59401 78 53401 93 65001 91 51001 59 58501 66 48001 50 56001 61 58901 70

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Please complete the following problems and show all of your work. I.Two variables are listed. Would you expect collected data on these two variables to

Please complete the following problems and show all of your work.

I.Two variables are listed. Would you expect collected data on these two variables to have a correlation coefficient which is positive, negative, or near zero? Explain.

1. height and weight

2. upper body strength and distance in the shot put

3. arm length and softball throw for distance

4. age and body temperature

5. standing long jump and vertical jump test score

6. swimming sprint speed and tennis serving accuracy

7. golf score and number of hours spent practicing

8. school grade point average and hours spent watching TV

9. years after graduation and balance on student loans

10. age and income

II. Correlation scatter plots Make a scatter plot using the following data sets. If the sets are correlated, indicate whether the 2 variables are positively correlated, negatively correlated, or not correlated.

1.QUESTION:Do winning MLB teams have greater attendance at their games? The following are statistics from the 2006 MLB Season:

WINS HOMEATTENDANCE

6015,000

7025,000

7722,500

7727,500

8026,500

8725,000

8735,000

9035.000

9031,500

9222,500

9425,000

9430,000

9555,000

2. QUESTION:Do the Winning times in the 100 Meter Summer Olympics Run show thatmen's inning timesare correlated withwomen's winning times? (Do NOT graph the year. Just graph the men's finishing time and women's finishing time.)

YEAR MEN's WINNING TIME WOMEN's WINNING TIME

192810.80 seconds12.20 seconds

193210.3011.90

193610.3011.50

194810.4011.90

195210.5011.50

195610.5011.50

196010.2011.00

196410:0011:40

19689:9511:00

197210:1411:02

197610:0611:08

198010:2511.60

19849:9910:97

19889:9210:54

19929:9610:82

19969:8410:94

20009:6710:75

20049:8510:93

3. Question:Theweights (in pounds)of eight vehicles and thevariability of theirbraking distances (in feet)when stopping on a dry surface are shown. Can you conclude that there is a linear correlation between vehicle weight and variability in braking distance on a dry surface?

WeightVariability In Braking Distance

59401.78

53401.93

65001.91

51001.59

58501.66

48001.50

56001.61

58901.70