Reference no: EM13583688

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.