Question:
| C1-T |
INTERNET |
GDP |
CO2 |
CELLULAR |
FERTILITY |
LITERACY |
| Algeria |
0.65 |
6.09 |
3 |
0.3 |
2.8 |
58.3 |
| Argentina |
10.08 |
11.32 |
3.8 |
19.3 |
2.4 |
96.9 |
| Australia |
37.14 |
25.37 |
18.2 |
57.4 |
1.7 |
100 |
| Austria |
38.7 |
26.73 |
7.6 |
81.7 |
1.3 |
100 |
| Belgium |
31.04 |
25.52 |
10.2 |
74.7 |
1.7 |
100 |
| Brazil |
4.66 |
7.36 |
1.8 |
16.7 |
2.2 |
87.2 |
| Canada |
46.66 |
27.13 |
14.4 |
36.2 |
1.5 |
100 |
| Chile |
20.14 |
9.19 |
4.2 |
34.2 |
2.4 |
95.7 |
| China |
2.57 |
4.02 |
2.3 |
11 |
1.8 |
78.7 |
| Denmark |
42.95 |
29 |
9.3 |
74 |
1.8 |
100 |
| Egypt |
0.93 |
3.52 |
2 |
4.3 |
3.3 |
44.8 |
| Finland |
43.03 |
24.43 |
11.3 |
80.4 |
1.7 |
100 |
| France |
26.38 |
23.99 |
6.1 |
60.5 |
1.9 |
100 |
| Germany |
37.36 |
25.35 |
9.7 |
68.2 |
1.4 |
100 |
| Greece |
13.21 |
17.44 |
8.2 |
75.1 |
1.3 |
96.1 |
| India |
0.68 |
2.84 |
1.1 |
0.6 |
3 |
46.4 |
| Iran |
1.56 |
6 |
4.8 |
3.2 |
2.3 |
70.2 |
| Ireland |
23.31 |
32.41 |
10.8 |
77.4 |
1.9 |
100 |
| Israel |
27.66 |
19.79 |
10 |
90.7 |
2.7 |
93.1 |
| Japan |
38.42 |
25.13 |
9.1 |
58.8 |
1.3 |
100 |
| Malaysia |
27.31 |
8.75 |
5.4 |
31.4 |
2.9 |
84 |
| Mexico |
3.62 |
8.43 |
3.9 |
21.7 |
2.5 |
89.5 |
| Netherlands |
49.05 |
27.19 |
8.5 |
76.7 |
1.7 |
100 |
| New Zealand |
46.12 |
19.16 |
8.1 |
59.9 |
2 |
100 |
| Nigeria |
0.1 |
0.85 |
0.3 |
0.3 |
5.4 |
57.7 |
| Norway |
46.38 |
29.62 |
8.7 |
81.5 |
1.8 |
100 |
| Pakistan |
0.34 |
1.89 |
0.7 |
0.6 |
5.1 |
28.8 |
| Philippines |
2.56 |
3.84 |
1 |
15 |
3.2 |
95 |
| Russia |
2.93 |
7.1 |
9.8 |
5.3 |
1.1 |
99.4 |
| Saudi Arabia |
1.34 |
13.33 |
11.7 |
11.3 |
4.5 |
68.2 |
| South Africa |
6.49 |
11.29 |
7.9 |
24.2 |
2.6 |
85 |
| Spain |
18.27 |
20.15 |
6.8 |
73.4 |
1.2 |
96.9 |
| Sweden |
51.63 |
24.18 |
5.3 |
79 |
1.6 |
100 |
| Switzerland |
30.7 |
28.1 |
5.7 |
72.8 |
1.4 |
100 |
| Turkey |
6.04 |
5.89 |
3.1 |
29.5 |
2.4 |
77.2 |
| United Kingdom |
32.96 |
24.16 |
9.2 |
77 |
1.6 |
100 |
| United States |
50.15 |
34.32 |
19.7 |
45.1 |
2.1 |
100 |
| Vietnam |
1.24 |
2.07 |
0.6 |
1.5 |
2.3 |
90.9 |
| Yemen |
0.09 |
0.79 |
1.1 |
0.8 |
7 |
26.9 |
Using data provided from theUS Statewide Crime data set, construct a scatterplot using Excel or any software (SPSS or Minitab) between the variables "murder rate" and "poverty". Provide an appropriate title for the chart as well as labels for both axes.
a. There seems to be a problem caused by the presence of an outlier. Identify the outlier and delete it (simply erase its value, do not replace with zero).
- Show the new scatterplot.
- Describethe pattern that emerges. What might this relationship imply? Be careful not to infer cause and effect.
b. Compute the correlation coefficient between the two variables and interpret this correlation. Refer to both the strength and direction of the correlation in your interpretation. Also interpret the correlation in terms of r-squared (coefficient of determination).
c. Conduct a regression to predict murder from poverty (when the observation for DC is removed from the data set) and interpret the results.
d. What is the predicted value for a state with a poverty rate of 13.4?
e. Interpret the value of the R-squared for the regression model.