Back to Work Employment Program Data Analysis and Outcome Report

This report presents a data analysis of back-to-work employment programs, specifically the Mpower and JobQuest initiatives. The analysis focuses on the relationship between program participation and the employment status of individuals. The methodology involves cross-tabulation and the application of SPSS to analyze survey data from 20 respondents. The report formulates and tests hypotheses using the Chi-square test to determine the association between program success and employment status. The findings indicate no significant association between the programs and employment outcomes. The report includes case processing summaries, crosstabulations, and Chi-square tests, along with interpretations of Phi and Cramer's V for measuring the strength of association between variables. The conclusion reiterates the lack of a significant relationship and highlights the use of categorical data analysis techniques.

DATA ANALYSIS AND
REPORT

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
Hypothesis formation for Mpower program...........................................................................1
Hypothesis for JobQuest program..........................................................................................4
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................7

INTRODUCTION
Data analysis is elaborated as process of cleansing, transforming, modeling and
inspecting data with aim of discovering the important information, framing conclusion and to
support decision making. The present report will discuss about back to work employment
program outcome survey. It will reflect association among success of each program with context
of employment status of any individual. In this report, data will be analysed through cross
tabulation with application of SPSS.
Hypothesis formation for Mpower program
H0: Null hypothesis - There is no association between relative success of Mpower program with
employment status of individual (Bayless and et.al., 2016).
H1: Alternative hypothesis - There is association between relative success of Mpower program
with employment status of individual.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Employementstatus *
Programstatus 11 100.0% 0 0.0% 11 100.0%
With reference to back to work employment program there is outcome of 11 respondents
who were surveys and completed one to back to work Mpower program. The above table is
reflecting summary of case and total 20 respondents which are 100%.
Employementstatus * Programstatus Crosstabulation
Programstatu
s
Total
Completed
Mpower
Program
Employementstatu
s
Employed/Self-
employed
Count 3 3
% within
Employementstatus 100.0% 100.0%
% within Programstatus 27.3% 27.3%
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% of Total 27.3% 27.3%
Unemployed - Looking
for work
Count 6 6
% within
Employementstatus 100.0% 100.0%
% within Programstatus 54.5% 54.5%
% of Total 54.5% 54.5%
Unemployed - Not
Looking for work
Count 2 2
% within
Employementstatus 100.0% 100.0%
% within Programstatus 18.2% 18.2%
% of Total 18.2% 18.2%
Total
Count 11 11
% within
Employementstatus 100.0% 100.0%
% within Programstatus 100.0% 100.0%
% of Total 100.0% 100.0%
Programstatus * Employmentstatus Crosstabulation
Employmentstatus Total
Employed/
Self-
employed
Unemployed
- Looking for
work
Unemployed
- Not looking
for work
Programstatus
Completed Mpower
Program 3 6 2 11
Completed JobQuest
Program 4 5 0 9
Total 7 11 2 20
The above table is stating frequency of association among program and employment
status with context of cross tabulation. There is categorization of three employment status which
are employed/ self employed, unemployed or looking for work and unemployed but not looking
for work. The one who completed Mpower program status are 11 but in which 27.30% are self
employed, 54.50% are unemployed and looking for work and 18.20% respondents are
unemployed and not looking for work as well. In the similar aspect, the respondents who had
completed Job quest program are in total 9 where 44.40% are self employed and rest 55.60% are
unemployed and looking for work (Test, 2015). Furthermore, in these 20 respondents 35% are
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employed or self employed, 55% are unemployed and looking for work and remaining 10% are
unemployed and not looking for work as well.
Chi-Square Tests
Value
Pearson Chi-Square .a
N of Valid Cases 11
a. No statistics are computed because Programstatus is a constant.
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 2.054a 2 .358
Likelihood Ratio 2.807 2 .246
Linear-by-Linear Association 1.517 1 .218
N of Valid Cases 20
a. 5 cells (83.3%) have expected count less than 5. The minimum expected count is .90.
The above table is reflecting perason's chi square test which is statistical test applied
through multiple sets of categorical data and used for evaluating about observed difference
among sets rose through chance. The degree of freedom is 2 with value of 2.054 within 20
respondents. the criteria for selecting null or alternative hypothesis is if significance value is less
than 0.05 then there will be acceptance of alternative hypothesis and it is more than 0.05 then
acceptance of null hypothesis (Hess and Hess, 2017). In the above scenario, its significance
value is .358 which is greater than 0.05, then null hypothesis will be accepted. In simple words, it
could be elaborated that there is no association among employment status of individual with
reference to program status. In the similar aspect, there is presentation of likelihood ratio which
is statistical test used for purpose of comparing the goodness of fit with these two hypothesis null
and alternative as its value is .246 with degree of freedom as 2.
In nutshell:
Null hypothesis accepted because of more than value from 0.05 as .358.
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Symmetric Measures
Value
Nominal by Nominal Phi .a
N of Valid Cases 11
a. No statistics are computed because Programstatus is a constant.
The above table is considered as systematic measure with application of Phi and Cramer's
V. In this aspect, Phi is used for measuring strength of association among two variables with
context of category. In the above scenario, Phi coefficient is .358 which is positive as it indicates
that numerous data is present in diagonal cells. It has not assumed null hypothesis as with
application of asymptotic standard error with assumption of null hypothesis. The Cramer's V is
replicated as method of extracting calculation of correlation in tables as it has more than 2 rows
and column. As it is performed post test because it determines strengths of association after
application of Chi-square test by determining significance in all nominal variables. The outcome
of Cramer's V in this scenario is .358 which is close to 0 then it shows weak correlation among
nominal variables.
Hypothesis for JobQuest program
H0: Null hypothesis - There is no association between relative success of JobQuest program
with employment status of individual (Bayless and et.al., 2016).
H1: Alternative hypothesis - There is association between relative success of JobQuestprogram
with employment status of individual.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Employementstatus *
Programstatus 11 100.0% 0 0.0% 11 100.0%
Employementstatus * Programstatus Crosstabulation
4

Programstatu
s
Total
Completed
Mpower
Program
Employementstatu
s
Employed/Self-
employed
Count 3 3
% within
Employementstatus 100.0% 100.0%
% within Programstatus 27.3% 27.3%
% of Total 27.3% 27.3%
Unemployed - Looking
for work
Count 6 6
% within
Employementstatus 100.0% 100.0%
% within Programstatus 54.5% 54.5%
% of Total 54.5% 54.5%
Unemployed - Not
Looking for work
Count 2 2
% within
Employementstatus 100.0% 100.0%
% within Programstatus 18.2% 18.2%
% of Total 18.2% 18.2%
Total
Count 11 11
% within
Employementstatus 100.0% 100.0%
% within Programstatus 100.0% 100.0%
% of Total 100.0% 100.0%
Chi-Square Tests
Value
Pearson Chi-Square .a
N of Valid Cases 11
a. No statistics are computed because Programstatus is a constant.
Symmetric Measures
Value
Nominal by Nominal Phi .a
5

N of Valid Cases 11
a. No statistics are computed because Programstatus is a constant.
CONCLUSION
On basis of above report, it had been concluded that there is no significant association
among relative success of every program with employment status of individual. In the same
series, this outcome has been evaluated with application of cross tabulation performed through
Chi square test. It has shown that this test helps in utilizing a contingency table for purpose of
analysing any data. There are outcome by undertaking survey from 20 respondents in which 7
are self employed, 11 are looking for work and unemployed and remaining 2 respondents are
unemployed and not looking for work as well. As this data is considered as categorical data
where with application of Chi square test, it could be concluded that there is absence of
significant association among program and employment status.
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REFERENCES
Books and Journals
Bayless, N. L. and et.al., 2016. Zika virus infection induces cranial neural crest cells to produce
cytokines at levels detrimental for neurogenesis. Cell host & microbe. 20(4). pp.423-428.
Hess, A. S. and Hess, J. R., 2017. Understanding tests of the association of categorical variables:
the Pearson chi‐square test and Fisher's exact test. Transfusion. 57(4). pp.877-879.
Test, O., 2015. Your chi-square test is statistically significant±now what. Pract Assess Res
Eval. 20(8). pp.2-10.
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