Data for Class Activities

The following data represent the number of homeruns per season for each respective player:

Barry Bonds: | 16 | 25 | 24 | 19 | 33 |

25 | 34 | 46 | 37 | 33 | |

42 | 40 | 37 | 34 | 49 | |

73 | 46 | 45 |

Sammy Sosa: | 1 | 7 | 15 | 10 | 8 |

33 | 25 | 36 | 40 | 36 | |

66 | 63 | 50 | 64 | 49 | |

40 |

The following data represent the fuel efficiency (in mpg) of my 1998 Honda Civic for each of the last 20 full tanks:

29.56 | 30.25 | 28.33 | 33.04 | 30.90 | 30.70 | 27.63 | 36.09 | 35.91 | 31.32 |

34.49 | 33.86 | 36.97 | 32.81 | 34.61 | 29.30 | 31.41 | 35.54 | 32.13 | 34.21 |

The following data represent the fuel efficiency (in mpg) of my wife's 2003 Honda Civic for each of the first eight (8) full tanks:

21.94 | 20.86 | 20.28 | 26.96 | 25.26 | 22.17 | 19.65 | 23.91 |

1. The following data represent the scores of the first two rounds of the 2004 NCAA Men's Division I Basketball Tourney
(St. Louis and East Rutherford Brackets):

96 | 76 | 100 | 102 | 58 | 66 | 78 | 53 | 58 | 51 |

65 | 60 | 66 | 72 | 76 | 49 | 75 | 76 | 63 | 78 |

54 | 57 | 91 | 72 | 82 | 59 | 63 | 76 | 73 | 60 |

53 | 75 | 79 | 78 | 76 | 70 | 64 | 53 | 44 | 59 |

55 | 43 | 75 | 56 | 70 | 84 | 65 | 80 |

- Determine if the data is normally distributed.

2. Twenty one-day-old male chicks were fed corn. Here are the weight gains (in grams) after 21 days:

380 | 321 | 366 | 356 | 283 | 349 |

402 | 423 | 356 | 410 | 329 | 399 |

350 | 384 | 316 | 272 | 345 | 360 |

431 | 455 |

- Determine if the data is normally distributed.

3. Here are the number of homeruns hit each year by Joe DiMaggio:

29 | 46 | 32 | 30 | 31 | 30 | 12 |

21 | 25 | 20 | 39 | 14 | 32 |

- Determine if the data is normally distributed.

The yearly increase of CEO compensation and the yearly corporate profits for the largest 350 U.S.
publicly traded firms is given below:

1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | |

CEO compensation | 10.4% | 5.2% | 11.7% | 5.2% | 11.0% | 10.0% | -2.8% | 10.0% | 7.2% | 14.5% |

Corporate Profits | 14.2% | 11.0% | 8.9% | 5.0% | 15.1% | 8.9% | -17.8% | 14.8% | 19.2% | 23.0% |

The following data represents the ages (in years) of seven men and their systolic blood pressures:

Age, x | 16 | 25 | 39 | 45 | 49 | 64 | 70 |

Systolic BP, y | 109 | 122 | 143 | 132 | 199 | 185 | 199 |

- Use the TI-83 to help you construct the scatterplot. Label the graph.
- Describe the overall pattern. Is there a direction to the relationship? If so, what is it? Is there an outlier?
- Suppose the men aged 25, 49 and 64 were smokers and the others were non-smokers. Show this on your scatterplot.
- Can you conclude anything about smokers and their systolic blood pressure? Why or why not.

Adapted from www.mathlab.isot.com/math/Statistics/Statlab4.pdf

i. Guessing Correlations - http://www.stat.uiuc.edu/~stat100/java/GCApplet/GCAppletFrame.html This applet gives you four scatterplots and four correlation coefficients. You match them up.

ii. Correlation/Outliers Applet - http://www.math.tamu.edu/FiniteMath/FinalBuild/Classes/Correlation/ Once applet can provide you with real insight into how to read scatterplots and into how correlation coefficients can be misleading.

iii. Regression by Eye - http://www.ruf.rice.edu/~lane/stat_sim/reg_by_eye/index.html This applet gives you a scatterplot and you can use the mouse to indicate what seems to be the best straight line approximating the data. This is an excellent way to develop a feel for linear regression!

iv. Visual Statistics - http://www.seeingstatistics.com/seeingTour/intro/why3.html This applet graphssome common geometric statistical concepts: data points (black dots), residuals (red lines), error squares (yellow squares), and regression or model line (blue line). Use your mouse to drag the blue line and see how the geometric objects change.

A student wonders if people of similar heights tend to date each other. She measures herself, her dormitory roommate, and the women in the adjoining rooms, then she measures the next man each woman dates. Here are the data (heights in inches):

Women, x | 66 | 64 | 66 | 65 | 70 | 65 |

Men, y | 72 | 68 | 70 | 68 | 71 | 65 |

- Use the TI-83 to help you construct the scatterplot.
- Describe the overall pattern. Is there an outlier?
- Based on the scatterplot, do you expect the correlation to be positive or negative? near ±1 or not?
- Compute the correlation
*r*. - How would
*r*change if all the men were 6 inches shorter than the heights given in the table? - How
*r*would change if the heights are measured in centimeters?

CEO compensation: http://www.industryweek.com/PrintArticle.aspx?ArticleID=10387

The following data represent my weight (in #) since starting my low-card diet:

1/12/04 | 1/19/04 | 1/26/04 | 2/2/04 | 2/9/04 | 2/16/04 | 2/23/04 | 3/1/04 | 3/8/04 | 3/15/04 |

187 | 185 | 182 | 179 | 176 | 174 | 172 | 170 | 171 | 170 |

3/22/04 | 3/29/04 | 4/5/04 | 4/12/04 | 4/19/04 | 4/26/04 | 4/30/04 | 5/10/04 | 5/17/04 | |

169 | 166 | 167 | 163 | 164 | 164 | 163 | 164 | 163 |

- Use the TI-83 to help you construct a scatterplot of my weight. Label the graph.
- Describe the overall pattern. Is there a direction to the relationship? If so, what is it? Is there an outlier?
- Based on the scatterplot, do you expect the correlation to be positive or negative? near ±1 or not?
- Compute the correlation r.

The following data represent the grade for Quiz 3 and the grade for Test I for students in one of my classes:

Student: | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |

Quiz: | 8 | 5 | 9 | 9 | 3 | 10 | 9 | 5 | 6 | 5 | 8 |

Test: | 74 | 88 | 99 | 90 | 63 | 91 | 91 | 84 | 83 | 98 | 90 |

Student: | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 |

Quiz: | 9 | 10 | 5 | 8 | 5 | 10 | 8 | 8 | 8 | 9 | 8 |

Test: | 83 | 60 | 80 | 96 | 56 | 97 | 87 | 79 | 82 | 92 | 85 |

- Use the TI-83 to help you construct a scatterplot of quiz grades vs. test grades. Label the graph.
- Describe the overall pattern. Is there a direction to the relationship? If so, what is it? Is there an outlier?
- Based on the scatterplot, do you expect the correlation to be positive or negative? near ±1 or not?
- Compute the correlation r.

Below are the students in one of my statistics classes:

Beth | Brandon | |||

Lisa | Lacey | |||

Julie | Suzanne | |||

Joanna | Kelly | |||

Danielle | Hollie | |||

Marissa | Shavonne | |||

Benjamin | Krissie | |||

Christina | Anthony | |||

Kevin | Brian | |||

Dobrinka | Tanya | |||

Ashleigh | Takang | |||

Kim | Joanne |

The famous "The Monte Hall Problem" comes from the game show Let's Make A Deal. Suppose you're on a game show, and you're given the choice of three doors: Behind one door is a $1,000,000.00 and behind the others, goats. The host knows behind which door is the good prize (for me it's the $1,000,000.00). You pick a door, say door number 1, and the host shows you what's behind one of the other doors that hides the goat. Then he gives you a chance to stay with your initial choice or to change your choice. Do you switch your choice of doors? Explain.

Would you switch if there were four(4) doors?

The following data are from 20 small packets of M&Ms:

sample | red | orange | yellow | green | blue | brown | total |

1 | 10 | 8 | 6 | 8 | 12 | 13 | 57 |

2 | 10 | 12 | 4 | 8 | 17 | 8 | 59 |

3 | 7 | 11 | 6 | 13 | 12 | 7 | 56 |

4 | 11 | 10 | 5 | 11 | 7 | 14 | 58 |

5 | 7 | 13 | 2 | 11 | 7 | 16 | 56 |

6 | 13 | 11 | 9 | 9 | 9 | 7 | 58 |

7 | 9 | 10 | 2 | 13 | 9 | 14 | 57 |

8 | 14 | 8 | 5 | 11 | 8 | 11 | 57 |

9 | 9 | 10 | 6 | 9 | 12 | 10 | 56 |

10 | 8 | 15 | 7 | 13 | 7 | 5 | 55 |

11 | 8 | 11 | 7 | 12 | 10 | 9 | 57 |

12 | 9 | 14 | 4 | 14 | 9 | 9 | 59 |

13 | 2 | 9 | 8 | 7 | 9 | 22 | 57 |

14 | 9 | 10 | 3 | 10 | 12 | 13 | 57 |

15 | 6 | 8 | 7 | 15 | 7 | 16 | 59 |

16 | 9 | 10 | 2 | 13 | 13 | 10 | 57 |

17 | 8 | 10 | 6 | 14 | 9 | 11 | 58 |

18 | 9 | 11 | 2 | 8 | 15 | 16 | 61 |

19 | 7 | 18 | 4 | 7 | 12 | 10 | 58 |

20 | 8 | 12 | 2 | 11 | 11 | 11 | 55 |

Data is from http://mathforum.org/epigone/ap-stat/clubangcroi.

Online Resources:

- Sampling Distributions [and Central Limit Theorem] - http://www.ruf.rice.edu/~lane/stat_sim/sampling_dist/

This java applet lets you explore various aspects of sampling distributions. - Proof of the Central Limit Theorem - http://mathworld.wolfram.com/CentralLimitTheorem.html

The proof of this theorem is beyond the scope of the course. It is included here in case you are interested!