1. No category

CORRELATION ANALYSIS (SAMPLE ASSIGNMENT)
Objective:
Identify the correlation and association of smoking habits and the life behaviours. Smoking
habits is the dependent variable and qualification, unit drinks etc are independent variables.
We want to test the association between the independent variables and the dependent
variable.
Independent Variable
Dependent Variable
1.1 Whether ever smoked
Categori al
1.3 Number of Cigarrette/week
Scale
1.4 Cigarette smoking
2.2 Any qualification
Scale
4.1 House hold tenure
3.1 Whether currently drink
2.1 Age when ended F-T
4.3 receiving i ncome support
3.2 No. of uni t of beer drunk in a week
3.3 No. of uni t of spirit drunk in a week
3.4 No. of uni t of wine drunk in a week
3.5 No. of unit drunk in a week
6.1 number of adul t i n HH
6.2 Number of chil dren in HH
5.1 whether father smoked
5.2 whether mother smoked
Table no. 1
1. Hypothesis 1
In hypothesis testing the box plot is un-necessary because the variable whether ever
smoked is categorical variable and it has only two options.
The bar chart is used to analyze the whether ever smoked. The bar chart shows that
about 1025 persons replied yes and 433 replied no.
2. Hypothesis 2
In hypothesis 2
H0: There is no association between the currently drinks and ever smoked.
H1: There is an association between the currently drinks and ever smoked.
Hypothesis 4
H0:
There is no association between the CigarettesPerWeek and QuantityWine in a
week.
H1:
There is association between the CigarettesPerWeek and QuantityWine in a week.
(D) Number of cigarettes per week * (D) No. units of wine drunk in a week Crosstabulation
Count
(D) No. units of wine drunk in a week
Medium
Low drink drink
Total
671
24
102
1070
118
5
14
194
101-200 cigarettes a 59
week
99
1
9
168
201-300 cigarettes a 6
week
11
0
2
19
>300
week
4
0
0
7
903
30
127
1458
(D)
Number
of Non Smoker
cigarettes per week 1-100 cigarettes
week
None
Drink
Very
drink
273
a 57
cigarettes
a3
Total
398
low
The above output shows that 273 numbers of respondents are non-smoker and they
never drink in any week. The association shows that the people who smoked fewer
cigarettes also drink low or very low.
Chi-Square Tests
Value
df
Asymp. Sig.
(2-sided)
Pearson Chi-Square
13.425a 12
.339
Likelihood Ratio
15.194
12
.231
Linear-by-Linear
Association
9.652
1
.002
N of Valid Cases
1458
a. 8 cells (40.0%) have expected count less than 5.
The minimum expected count is .14.
The chi-square value is 13.425 and the p value is 0.339 which shows that we fail to
reject the null hypothesis because the p value is greater than the alpha. It is
concluded that there is no association between the two variables.
Symmetric Measures
Value
Asymp. Std. Approx.
Errora
Tb
Approx.
Sig.
Interval
Interval
by Pearson's R
-.081
.024
-3.116
.002c
Ordinal
Ordinal
by Spearman
Correlation
-.083
.026
-3.161
.002c
N of Valid Cases
1458
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.
The correlation matrix is measured to analyze the relationship between the two
variables. The pearson’s R correlation is calculated between the number of
cigarettes smoked in a week and the unit of wine drunk in a week. The
correlation(r=-0.081) which is weak and it is not significant so we fail to reject the null
hypothesis and there is no association between the two variables.
H5:
H0:
The number of years education gain cannot affect the smoking habits (number
of cigarettes smoked in a week).
H1:
The number of years education gain can affect the smoking habits (number of
cigarettes smoked in a week).
Model Summary
Model R
1
.081a
Adjusted
R Square Square
.007
.006
R Std. Error of
the Estimate
.77906
a. Predictors: (Constant), Age when ended F-T
education
Coefficientsa
Model
1
(Constant)
Unstandardized
Coefficients
Standardize
d
Coefficients
B
Std. Error
Beta
.598
.060
Age when ended F-T -.036
education
.011
-.081
t
Sig.
9.930
.000
-3.113
.002
a. Dependent Variable: (D) Number of cigarettes per week
The regression equation is y=0.598-0.036*x
Where y= number of cigarettes smoked in a week and x is the age when ended F-T
education.
The association is negative because the educated people have fewer tendencies to
smoke but the association is not significant.
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