DOES R OWN
OR RENT HOME? * RESPONDENTS SEX Crosstabulation
RESPONDENTS
SEX
Total
MALE
FEMALE
DOES R OWN OR RENT HOME?
OWN OR IS BUYING
Count
464
571
1035
% within RESPONDENTS SEX
61.9%
62.0%
62.0%
PAYS RENT
Count
274
336
610
% within RESPONDENTS SEX
36.6%
36.5%
36.5%
OTHER
Count
11
14
25
% within RESPONDENTS SEX
1.5%
1.5%
1.5%
Total
Count
749
921
1670
% within RESPONDENTS SEX
100.0%
100.0%
100.0%
Chi-Square
Tests
Value
df
Asymp.
Sig. (2-sided)
Pearson Chi-Square
.009a
2
.996
Likelihood Ratio
.009
2
.996
Linear-by-Linear Association
.000
1
.999
N of Valid Cases
1670
a. 0 cells (0.0%) have expected count less than 5. The minimum
expected count is 11.21.
Symmetric
Measures
Value
Approx.
Sig.
Nominal by Nominal
Phi
.002
.996
Cramer’s V
.002
.996
N of Valid Cases
1670
What is your research question? Can we determine
the relationship between respondents’ sex and the question of whether
respondents own or rent home?
What is the null hypothesis for your question?
Given all applicable data, there is no relationship between respondents’ sex
and their question of whether respondents own or rent home.
What research design would align with this
question? My research design is a comparative design of methodology. In social
sciences, this type of research design is purposed to compare correlation or
relationships among variables (Cantrell, 2011).
What dependent variable was used and how is it
measured? My dependent variable is does respondents Own or Rent home? It is
measured using descriptive statistics and selecting crosstabs, under Rows space
to calculate relationship between the two variables.
What independent variable is used and how is it
measured? My independent variable is the respondents’ sex. It is measured using
descriptive statistics while selecting crosstabs, under column space to
calculate relationship between the two variables.
If you found significance, what is the strength
of the effect? Using the Cramer’s V correlation, we can determine the strength
of the effect. A value of 0 indicates no
relationship whatsoever, and a value of 1.0 indicates high correlation or
perfect relationship (Laureate Education, 2016a). Our value of 0.002 indicate
an almost perfect relationship, thereby reject the null hypothesis.
Explain your results for a lay audience and
further explain what the answer is to your research question. Using the case
processing table above, we can see a valid number of 1670 and those who either
refused to answer the question or were not available were 868, with a total of
2538. The crosstabulation table tells us the number or percentages of male
respondents who either own or is buying home, or pays rent and/or others. This
percentages applies the same analysis with Female. For example, the percentage
of male respondents who pays rent is 36.6%. The table also tells us that there
is relationship between the variables due to unequal percentages between the
dependent variables. To statistically test the relationship, we can review
chi-square table. We can see a Pearson Chi-square of 0.009. However the p-value
is given 0.996, which is above the conventional threshold of 0.05. Controlling
other assumptions of the resulted data, Chi-square tells us there is no
relationship between the two variables, thereby accepting the null hypothesis.
Reference
Cantrell, M. A.
(2011). Demystifying the research process: Understanding a descriptive
comparative research design. Pediatric
Nursing, 37(4), 188-9.
