The topic for this paper primarily revolves around crime. The focus of the paper is how crime is caused and how it can be decreased in the long run through the use of government spending on the law enforcement agencies. The paper focuses on the elaboration model and the relationship between variables.
Elaboration Model
There is a gender difference in attitudes toward spending too much money on halting crime rate.
There is a gender difference in attitudes toward spending too much money on law enforcement.
There is a direct relationship between amount spend on halting crime rate and amount spent on law enforcement.
There is a gender differencet in attitudes toward spending too much money on halting crime rate that is directly moderated by amount spent on law enforcement.
Control Variable Question
100) We are faced with many problems in this country, none of which can be solved easily or inexpensively. I'm going to name some of these problems, and for each one I'd like you to tell me whether you think we're spending too much money on it, too little money, or about the right amount. E. Law enforcement (NATCRIMY).
QUESTION 3 -- Please refer respective chart and table
Table 3-1: Descriptive Table
Statistics
NATCRIMY
N
Valid
Missing
Std. Error of Mean
.01648
Std. Deviation
1.15403
Range
9.00
Minimum
.00
Maximum
9.00
Table 3-2: Frequency Table For NATCRIMY
NATCRIMY
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
.00
49.4
49.4
49.4
1.00
25.1
25.1
74.5
2.00
19.4
19.4
94.0
3.00
5.1
5.1
99.1
8.00
43
.9
.9
9.00
2
.0
.0
Total
b.
A histogram (interval or ratio interval) that graphically shows the distributions
Chart 3.-1: Histogram Graph For NATCRIMY
QUESTION 4 -- RECODE NATCRIMY
In order to have a meaningful representation those "Inapplicable, Don't Know and No Answer" had been recode to 4 and 5. Because of this, now the observation dispersion is scattered among 5 conditions from 6 conditions.
Table 4-1: Descriptive Statistics
Recode NATCRIMY
N
Valid
Missing
0
Mean
3.30
Median
4.00
Mode
5
Std. Deviation
1.759
Range
4
Minimum
1
Maximum
5
Table 4-2: Frequency Recode NATCRIMY
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
1
25.1
25.1
25.1
2
19.4
19.4
44.6
3
5.1
5.1
49.7
4
45
.9
.9
50.6
5
49.4
49.4
Total
Chart 4 -- 1: Histogram Chart For Recode NATCRIMY
QUESTION 5
Table 5-1: DESCRIPTIVESTATISTICS
NATCRIMY
Recode NATCRIMY
N
Valid
Missing
0
0
Mean
.8674
3.30
Median
1.0000
4.00
Mode
.00
5
Std. Deviation
1.15403
1.759
Range
9.00
4
Minimum
.00
1
Maximum
9.00
5
TABLE 5- 2: FREQUENCY TABLE FOR NATCRIMY
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
.00
49.4
49.4
49.4
1.00
25.1
25.1
74.5
2.00
19.4
19.4
94.0
3.00
5.1
5.1
99.1
8.00
43
.9
.9
9.00
2
.0
.0
Total
TABLE 5-3: FREQUENCY TABLE FOR RECODE NATCRIMY
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
1
25.1
25.1
25.1
2
19.4
19.4
44.6
3
5.1
5.1
49.7
4
45
.9
.9
50.6
5
49.4
49.4
Total
a.
In term of levels of measurement, mode, standard deviation and range had shown a significant difference with Mode, measurement shows a significant change from 0.0 to 5. Since most of the "Inapplicable, Don't Know and No Answer" had been recoded to 4 and 5, the Range for variables before and after recode is represented by a difference of 5 (which explains why Mode is 5).
Chart 5-1: Histogram Table For NATCRIMY
CHART 5-2: HISTOGRAM TABLE FOR RECODE NATCRIMY
b.
In terms of frequency of distribution, since 50% of the results were recoded, frequency for each response also drops by 50%. This is evidence in term of cumulative percentage. For example Categories 1 for NATCRIMY before recode cumulative percentage is 74.5 but after recode 25.1.
c.
mode, median and mean had shown a significant difference after recode. Mode measurement showed a significance change from 0 to 5 as mentioned earlier. Mean for before recode is shown as 0.8 but after recode mean is 3.0. This indicates that categories 4 and 5 which had been recorded contributes toward 3 times the whole mean of population.
d.
Standard deviation recode is recorded at 1.2 but after recode close to 1. This indicates the dispersion of the finding had been spread further as a result of regrouping certain observation under new observation categories.
QUESTION 6
a.
Cross-tabulation between Independent Variable vs. Dependent Variable.
Case Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
Recode NATCRIME * SEX
0
0.0%
Recode NATCRIME * SEX Cross tabulation
Count
SEX
Total
1.00
2.00
Recode NATCRIME
1
2
3
94
59
4
21
45
66
5
Total
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
61.392a
4
.000
Likelihood Ratio
61.090
4
.000
Linear-by-Linear Association
10.196
1
.001
N of Valid Cases
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 28.70.
Symmetric Measures
Value
Approx. Sig.
Nominal by Nominal
Phi
.112
.000
Cramer's V
.112
.000
N of Valid Cases
b.
Cross-tabulation between Independent Variable vs. Control Variable.
Case Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
Recode NATCRIMY * SEX
0
0.0%
Recode NATCRIMY * SEX Cross tabulation
Count
SEX
Total
1.00
2.00
Recode NATCRIMY
1
2
3
4
11
34
45
5
Total
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
59.156a
4
.000
Likelihood Ratio
60.170
4
.000
Linear-by-Linear Association
30.173
1
.000
N of Valid Cases
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 19.57.
Symmetric Measures
Value
Approx. Sig.
Nominal by Nominal
Phi
.110
.000
Cramer's V
.110
.000
N of Valid Cases
c.
Cross-tabulation between Control Variable vs. Dependent Variable.
Case Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
Recode NATCRIME * Recode NATCRIMY
0
0.0%
Recode NATCRIME * Recode NATCRIMY Cross tabulation
Count
Recode NATCRIMY
Total
1
2
3
4
5
Recode NATCRIME
1
0
0
0
0
2
0
0
0
0
3
0
0
0
0
4
0
0
0
0
66
66
5
45
0
Total
45
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
16
.000
Likelihood Ratio
16
.000
Linear-by-Linear Association
1
.000
N of Valid Cases
a. 3 cells (12.0%) have expected count less than 5. The minimum expected count is .61.
Symmetric Measures
Value
Approx. Sig.
Nominal by Nominal
Phi
1.000
.000
Cramer's V
.500
.000
N of Valid Cases
d.
Cross-tabulation between Independent Variable vs. Dependent Variable vs. Control Variable.
Case Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
Recode NATCRIME * SEX * Recode NATCRIMY
0
0.0%
Recode NATCRIME * SEX * Recode NATCRIMY Cross tabulation
Count
Recode NATCRIMY
SEX
Total
1.00
2.00
1
Recode NATCRIME
5
Total
2
Recode NATCRIME
5
Total
3
Recode NATCRIME
5
Total
4
Recode NATCRIME
5
11
34
45
Total
11
34
45
5
Recode NATCRIME
1
2
3
94
59
4
21
45
66
Total
Total
Recode NATCRIME
1
2
3
94
59
4
21
45
66
5
Total
Chi-Square Tests
Recode NATCRIMY
Value
df
Asymp. Sig. (2-sided)
1
Pearson Chi-Square
.b
N of Valid Cases
2
Pearson Chi-Square
.b
N of Valid Cases
3
Pearson Chi-Square
.b
N of Valid Cases
4
Pearson Chi-Square
.b
N of Valid Cases
45
5
Pearson Chi-Square
41.515c
3
.000
Likelihood Ratio
41.728
3
.000
Linear-by-Linear Association
12.636
1
.000
N of Valid Cases
Total
Pearson Chi-Square
61.392a
4
.000
Likelihood Ratio
61.090
4
.000
Linear-by-Linear Association
10.196
1
.001
N of Valid Cases
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 28.70.
b. No statistics are computed because Recode NATCRIME is a constant.
c. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 30.78.
Symmetric Measures
Recode NATCRIMY
Value
Approx. Sig.
1
Nominal by Nominal
Phi
.c
N of Valid Cases
2
Nominal by Nominal
Phi
.c
N of Valid Cases
3
Nominal by Nominal
Phi
.c
N of Valid Cases
4
Nominal by Nominal
Phi
.c
N of Valid Cases
45
5
Nominal by Nominal
Phi
.131
.000
Cramer's V
.131
.000
N of Valid Cases
Total
Nominal by Nominal
Phi
.112
.000
Cramer's V
.112
.000
N of Valid Cases
c. No statistics are computed because Recode NATCRIME is a constant.
QUESTION 7
a.
The amount difference between IV vs. DV is considered insignificant. Chi-square vs. likelihood ratio only differ by 0.302 (61.392-61.090) which is less than 5.
b.
The value column = 0.112, this indicates a slight relation between sex (gender) and amount spent in fighting crime. The significance level = 0.0001, which is highly significant (p< 0.05) that also means the relationship is generalizable to the populations. We could conclude, there is a gender difference in opinion toward increasing amount of money spent in halting crime rate. Women (56.5%) were more likely to agree with the statement than men (43.5%)
QUESTION 8
a.
The amount difference between IV vs. CV is considered insignificant. Chi-square vs. likelihood ratio only differs by 1.0140 (60.170-59.156) which is still less than 5.
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