Problem

College protests of labor exploitation. Refer to the Journal of World-Systems Research (Wi...

College protests of labor exploitation. Refer to the Journal of World-Systems Research (Winter 2004) study of college student “sit-ins,” presented in Exercise 9.21 (p. 498). The data in the SITIN file was used to estimate the straight-line model relating number of arrests (y) to duration of sit-in (x).

a. Give the values of SSE, s2, and s, shown on the SPSS printout below.

b. Give a practical interpretation of the value of s.

Exercise 9.21

College protests of labor exploitation. Refer to the Journal of World-Systems Research (Winter 2004) study of student “sit-ins” for a “sweat-free campus” at universities, presented in Exercise 2.145 (p. 93). Recall that the SIT1N file contains data on the duration (in days) of each sit-in, as well as the number of student arrests. The data for 5 sit-ins in which there was at least one arrest are shown in the accompanying table. Let y = number of arrests and x = duration.

a. Give the equation of a straight-line model relating y to x.

b. SPSS was used to fit the model to the data for the 5 sit-ins. The SPSS printout is shown at the bottom of the page. Give the least squares prediction equation.

c. Interpret the estimates of β0 and β1 in the context of the problem.

Sit-In

University

Duration

(days)

Number of Arrests

12

Wisconsin

4

54

14

SUNY Albany

1

11

15

Oregon

3

14

17

Iowa

4

16

18

Kentucky

1

12

Source: Ross, R. J. S. “From antisweatshop to global justice to antiwar: How the new new left is the same and different from the old new left,” Journal of Word-Systems Research, Vol. X, No. 1, Winter 2004 (Tables 1 and 3).

Exercise 2.145

College protests of labor exploitation. Refer to the Journal of World-Systems Research (Winter 2004) study of 14 student sit-ins for a “sweat-free campus” at universities in 1999 and 2000, presented in Exercise 2.35 (p. 47). The SITIN file contains data on the duration (in days) of each sit-in, as well as data on the number of student arrests.

a. Use a scatterplot to graph the relationship between duration and number of arrests. Do you detect a trend?

b. Repeat part a, but graph only the data for sit-ins in which there was at least one arrest. Do you detect a trend?

c. Comment on the reliability of the trend you detected in part b.

Exercise 2.35

College protests of labor exploitation. The United Students Against Sweatshops (USAS) was formed by students on US. and Canadian college campuses in 1999 to protest labor exploitation in the apparel industry. Clark University sociologist Robert Ross analyzed the USAS movement in the Journal of World-Systems Research (Winter 2004). Between 1999 and 2000, there were 18 student “sit-ins” for a “sweat-free campus” organized at several universities. The following table gives the duration (in days) of each sit-in, as well as the number of student arrests:

SITIN

Sit-in

Year

University

Duration

(days)

Number of Arrests

Tier

Ranking

1

1999

Duke

1

0

1st

2

1999

Georgetown

4

0

1st

3

1999

Wisconsin

1

0

1st

4

1999

Michigan

1

0

1st

5

1999

Fairfield

1

0

1st

6

1999

North Carolina

1

0

1st

7

1999

Arizona

10

0

1st

8

2000

Toronto

11

0

1st

9

2000

Pennsylvania

9

0

1st

10

2000

Macalester

2

0

1st

11

2000

Michigan

3

0

1st

12

2000

Wisconsin

4

54

1st

13

2000

Tulane

12

0

1st

14

2000

SUNY Albany

1

11

2nd

15

2000

Oregon

3

14

2nd

16

2000

Purdue

12

0

2nd

17

2000

Iowa

4

16

2nd

18

2000

Kentucky

1

12

2nd

Source: Ross, R. J. S.“From antisweatshop to global justice to antiwar: How the new new left is the same and different from the old new left.” Journal of World-Systems Research, Vol. X, No. 1,Winter 2004 (Tables 1 and 3).

a. Use a stem-and-leaf display to summarize the data on sit-in duration.

b. Highlight (or circle) the leaves in the display that correspond to sit-ins during which at least one arrest was made. Does the pattern revealed support the theory that sit-ins of longer duration are more likely to lead to arrests?

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