# MS 150 Statistics quiz three 4.4 linear regression • Name:

Evening joggle
LocationTime x (min)Distance y (m)
Dolihner 0.0 0000
Pohnpei campus 9.0 1250
Mesenieng outbound16.72600
Mesenieng inbound 26.64200
Pwunso botanic 35.75300
Dolihner 41.96190

The table contains data from a run on Wednesday evening the sixth of February. While running, the runner juggled three tennis balls. This activity is called joggling.

1. ______________ Does the relationship between distance and time appear to be linear, non-linear, or random?
2. ______________ Determine the slope of the linear regression (best fit line) for the data.
3. ______________ Determine the y-intercept of the linear regression for the data.
4. ______________ Determine the correlation coefficient r.
5. ______________ Is the correlation positive or negative?
6. ______________ Is the correlation none, weak, moderate, strong, or perfect?
7. ______________ Use the slope and intercept above to calculate the predicted distance covered by the runner after 25 minutes.
8. ______________ A typical fun run on Pohnpei is 5000 meters. Use the slope and intercept to solve for the predicted time for the runner to run 5000 meters.
9. ______________ Use the slope and intercept above to calculate the predicted distance covered by the runner after 250 minutes.
10. ______________ Statistically speaking, can we safely predict the distance covered for 250 minutes of running and juggling?
11. Why can we or why can we not safely predict the distance covered for 250 minutes of running and juggling?

Upcoming spring 2008 events, usually starting at 7:00 A.M. from Palm Terrace parking lot. Registration open at 6:30 A.M.

• PNI Rotary Club 5k Fun Run: March 01
• FSM National Fitness 5k Walk/Run: April 12 (maybe earlier)
• Women in Sport 5k: April 25
• COM-FSM 5k: May 03
• STAP 5k: May 24
Linear Regression Functions
Statistic or ParameterMath symbolStat symbolOpenOffice
Slopemb=slope(y-data;x-data)
Interceptba=intercept(y-data;x-data)
Correlation r=correl(y-data;x-data)
Coefficient of Determination r2 =(correl(y-data;x-data))^2