You hypothesize that there is a relationship between an individual’s level of Se
ID: 3334236 • Letter: Y
Question
You hypothesize that there is a relationship between an individual’s level of Self Control as measured by the Grasmick Self Control Scale (Self_Con) and his or her Number of Adult Arrests (ARR). Theory postulates that low self control is associated with higher number of arrests. Use the definitions of the variables contained in the Week One Dataset, reprinted below.
State your null and research hypotheses.
Variables are defined as follows: SELF_CON Grasmick Self-Control Scale Treated as interval-ratio level. A scale measuring self-control developed by Richard Grasmick. Scores may range from 24 to 96, with low scores indicating low self-control. 99 = No data in Record
ARR Number of adult arrests as recorded in court records. An interval-ratio level variable. Since all members of the population have (by definition) been arrested at least once, values will range from 1 to nn 99 = No data
Explain the following results from the SPSS output posted below******
NOTE: You do NOT need to know SPSS or perform any calculations to solve this problem. You do not have to explain any of the SPSS results that were not covered text or lecture.
1. Mean and standard deviation for each variable.
2. The interpretation of the Pearson Correlation Coefficient
3. R square
4. Unstandardized coefficients : (Constant and Self_Con)
5. Calculate the number of arrests for a person with a Self-Con score of 50.
Hypothetical data on the relationship of an inmate’s Grasmick Self Control Score to Adult Arrest History. Selected output from SPSS.
Descriptive Statisticsa
Mean
Std. Deviation
N
ARR
4.00
2.498
100
SELF_CON
41.10
16.114
100
a. Selecting only cases for which GENDER = Female
Correlationsa
ARR
SELF_CON
Pearson Correlation
ARR
1.000
-.252
SELF_CON
-.252
1.000
Sig. (1-tailed)
ARR
.
.006
SELF_CON
.006
.
N
ARR
100
100
SELF_CON
100
100
a. Selecting only cases for which GENDER = Female
Variables Entered/Removeda,b
Model
Variables Entered
Variables Removed
Method
1
SELF_CONc
.
Enter
a. Dependent Variable: ARR
b. Models are based only on cases for which GENDER = Female
c. All requested variables entered.
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
GENDER = Female (Selected)
1
.252a
.063
.054
2.430
a. Predictors: (Constant), SELF_CON
Coefficientsa,b
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
95.0% Confidence Interval for B
B
Std. Error
Beta
Lower Bound
Upper Bound
1
(Constant)
5.605
.669
8.382
.000
4.278
6.932
SELF_CON
-.039
.015
-.252
-2.577
.011
-.069
-.009
a. Dependent Variable: ARR
b. Selecting only cases for which GENDER = Female
Descriptive Statisticsa
Mean
Std. Deviation
N
ARR
4.00
2.498
100
SELF_CON
41.10
16.114
100
a. Selecting only cases for which GENDER = Female
Explanation / Answer
Answer:
1. Mean and standard deviation for each variable.
Descriptive Statisticsa
Mean
Std. Deviation
N
ARR
4.00
2.498
100
SELF_CON
41.10
16.114
100
2. The interpretation of the Pearson Correlation Coefficient
r= -.252
There is negative correlation between level of Self Control and Number of Adult Arrests.
When level of Self Control increases, Number of Adult Arrests decreases.
3. R square = .063
6.3% of variation in Number of Adult Arrests is explained by level of Self Control.
4. Unstandardized coefficients : (Constant and Self_Con)
Model
Unstandardized Coefficients
B
Std. Error
1
(Constant)
5.605
0.669
SELF_CON
-0.039
0.015
When level of Self Control increases by 1, Number of Adult Arrests decreases by 0.039.
When level of Self Control is 0, Number of Adult Arrests is 5.605.
5. Calculate the number of arrests for a person with a Self-Con score of 50.
The regression line is
Number of Adult Arrests = 5.605-0.039* level of Self Control
When level of Self Control = 50,
Predicted Number of Adult Arrests = 5.605-0.039* 50
=3.655
Descriptive Statisticsa
Mean
Std. Deviation
N
ARR
4.00
2.498
100
SELF_CON
41.10
16.114
100
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