4.0 INTRODUCTION

This chapter presents the summary of the findings of the study, the relevant discussions, conclusions and appropriate recommendations.

4.1 SOCIO DEMOGRAPHIC DESCRIPTIVE ANALYSIS

4.1.1 Gender

Table 4.1. 1: Frequency table for gender of the respondents

Gender Total Percentage CumSum
Female 187 53.4% 187
Male 163 46.6% 350

4.1.2 Age

Summary statistics of of age.

Min. 1st Qu. Median Mean 3rd Qu. Max.
19 23 26 27.95429 30 55

4.1.3 Marital Status

Table 4.1.2: Frequency table for marital status of the respondents

Marital Status Total Percentage CumSum
Married 97 27.7% 97
Separated 14 4.0% 111
Single 235 67.1% 346
Widowed 4 1.1% 350

Most of the individuals who participated in the study were single, 235 (67%). Widowed individuals who took part in the study were the least, 4 (1.1%). Figure above is a pie chart representing marital status of the respondents.

4.1.4 Education Level

Table 4.1.2: Frequency table for Education Level of the respondents

Level Of Education Total Percentage Cum.Sum
Degree 189 54.00% 189
Diploma 90 25.71% 279
Masters 7 2.00% 286
PhD 6 1.71% 292
Secondary 58 16.57% 350

Higher number of participants who were participated in the study had a degree, 189 (54%). Those who had PhD are the least, 6, (1.71%).

4.1.5 Employment Status

Table 4.1.2: Frequency table for Employment Status of the respondents

Employment Status Total Percentage Cum.Sum
Employed 164 46.9% 164
Unemployed 186 53.1% 350

About 47% of the respondents were employed while about 53% of the respondents were unemployed.

4.1.6 Type of Employment.

Table 4.1.2: Frequency table for type of Employment Status of the employed respondents respondents

Type of Employment Total Percentage Cum.Sum
Contract 34 20.7% 34
Fulltime 86 52.4% 120
Parttime 13 7.9% 133
Self 31 18.9% 164

About 52% of employed respondents were on full time jobs, about 21% on contract, 19% on self employment and about 8% were on the part time job

4.2 Test for Proportions

We wish to test the following hypothesis

  • H0: The proportion of the unemployed people was the same as the proportion of the employed.
  • H1: The proportion of the unemployed people was not the same.

4.2.1 One sample proportion test of Employment status

## 
##  1-sample proportions test with continuity correction
## 
## data:  table(employment_status), null probability 0.5
## X-squared = 1.26, df = 1, p-value = 0.2617
## alternative hypothesis: true p is not equal to 0.5
## 95 percent confidence interval:
##  0.4155138 0.5223300
## sample estimates:
##         p 
## 0.4685714

The p-value of 0.2617 is greater than significance level of \(\alpha = 0.05\). This indicates that the difference in proportions of the employment status is not statistically significant. We fail to reject the null hypothesis. The proportion of the unemployed people who participated in the study is the same as the proportion of the employed individuals who took part in the study.

4.2.2 Proportions of employment status across gender

## 
##  2-sample test for equality of proportions with continuity correction
## 
## data:  table(gender, employment_status)
## X-squared = 30.878, df = 1, p-value = 2.748e-08
## alternative hypothesis: two.sided
## 95 percent confidence interval:
##  0.1976350 0.4081194
## sample estimates:
##    prop 1    prop 2 
## 0.6096257 0.3067485

The p-value of 2.748e-08 is less than significance level of \(\alpha = 0.05\). This indicates that the difference in proportions of the employment status is statistically significant between male and female. We reject the null hypothesis. The proportion of the employment status of male is different from that of female who took part in the study.

4.2.3 Proportions of employment status across marital status.

Employed Unemployed
Married 68 29
Separated 14 0
Single 78 157
Widowed 4 0 
## 
##  4-sample test for equality of proportions without continuity
##  correction
## 
## data:  tableMS
## X-squared = 59.088, df = 3, p-value = 9.204e-13
## alternative hypothesis: two.sided
## sample estimates:
##    prop 1    prop 2    prop 3    prop 4 
## 0.7010309 1.0000000 0.3319149 1.0000000

The p-value of 9.204e-13 is less than significance level of \(\alpha = 0.05\). This indicates that the difference in proportions of the employment status is statistically significant across marital status. We reject the null hypothesis. The proportion sof the employment status across marital status of individuals who took part in the study are different.

4.2.4 Proportions of employment status across education level

## 
##  5-sample test for equality of proportions without continuity
##  correction
## 
## data:  tableEd
## X-squared = 40.079, df = 4, p-value = 4.169e-08
## alternative hypothesis: two.sided
## sample estimates:
##    prop 1    prop 2    prop 3    prop 4    prop 5 
## 0.4021164 0.7000000 0.5714286 1.0000000 0.2586207

The p-value of 4.169e-08 is less than significance level of \(\alpha = 0.05\). This indicates that the difference in proportions of the employment status is statistically significant across education level. We reject the null hypothesis. The proportions of the employment status across education level of individuals who took part in the study are different.

4.2.5 Proportions of employment status across type of employment.

## 
## Contract Fulltime Parttime     Self 
##       34       86       13       31

Most of the people who were employed in this study were under a full time type of employment (N=100). Only 13 out of the total participants were in part time employment plan. The group recorded as none are those people in the study who were not employed as shown in figure 4 and table 4 above.

4.2.6 Proportions of employment status between young and old.

##        
##         Employed Unemployed
##   Old         54          4
##   Young      110        182
## 
##  2-sample test for equality of proportions with continuity correction
## 
## data:  tableAge
## X-squared = 57.505, df = 1, p-value = 3.372e-14
## alternative hypothesis: two.sided
## 95 percent confidence interval:
##  0.4583056 0.6503387
## sample estimates:
##    prop 1    prop 2 
## 0.9310345 0.3767123

The p-value of 3.372e-14 is less than significance level of \(\alpha = 0.05\). This indicates that the difference in proportions of the employment status is statistically significant between young and old. We reject the null hypothesis. The proportions of the employment status between young and old individuals who took part in the study are different.

4.3. Investigating the factors associated with unemployment.

We wish to test the hypothesis that

  • H0: There are no factors associated with unemployment.
  • H1: There are factors associated with unemployment.

4.3.1 Association between gender and employment status

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tableGe
## X-squared = 30.878, df = 1, p-value = 2.748e-08

The p-value of 2.748e-08 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that gender is independent of the employment status.

4.3.2 Age group and employment status

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tableAge
## X-squared = 57.505, df = 1, p-value = 3.372e-14

The p-value of 3.372e-14 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that age is independent of the employment status.

4.3.3 Marital status and employment status

## 
##  Pearson's Chi-squared test
## 
## data:  tableMS
## X-squared = 59.088, df = 3, p-value = 9.204e-13

The p-value of 9.204e-13 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that Marital status is independent of the employment status.

4.3.4 Education Level and employment

## 
##  Pearson's Chi-squared test
## 
## data:  tableEdu
## X-squared = 40.079, df = 4, p-value = 4.169e-08

The p-value of 4.169e-08 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that Education Level is independent of the employment status.

4.3.5 Type of employment and employment status

## 
##  Pearson's Chi-squared test
## 
## data:  tableTe
## X-squared = 350, df = 4, p-value < 2.2e-16

The p-value of 2.2e-16 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that Type of employment is independent of the employment status.

4.3.6 Qualifications and employment status

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tableQu
## X-squared = 3.9337, df = 1, p-value = 0.04733

The p-value of 0.04733 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that Qualifications is independent of the employment status.

4.3.7 Opportunities and employment status

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tableOp
## X-squared = 5, df = 1, p-value = 0.02535

The p-value of 0.02535 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that Opportunities is independent of the employment status.

4.3.8 Inexperience and employment status

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tableIne
## X-squared = 6.031, df = 1, p-value = 0.01406

The p-value of 0.01406 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that having experience is independent of the employment status.

4.3.9 Working for free and employment status

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tableWf
## X-squared = 0.011601, df = 1, p-value = 0.9142

4.3.10 Discrimination and employment status

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tableDiscr
## X-squared = 7.8465, df = 1, p-value = 0.005092

The p-value of 0.005092 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that discrimination is independent of the employment status.

4.3.11 Skill gap and employment status.

## 
##  Pearson's Chi-squared test
## 
## data:  tableSg
## X-squared = 2.8793, df = 2, p-value = 0.237

The p-value of 0.237 is greater than significance level of \(\alpha = 0.05\), we fail to reject the null hypothesis that skill gap is independent of the employment status.

4.3.12 Disability and employment status

## 
##  Pearson's Chi-squared test
## 
## data:  tableDs
## X-squared = 24.153, df = 2, p-value = 5.692e-06

The p-value of 5.692e-06 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that disability is independent of the employment status.

4.4. Investigating the effects of unemployment.

We wish to test the hypothesis that

  • H0: There were no effects associated with unemployment.
  • H1: There were effects associated with unemployment.

4.4.1 Crime rate and employment status

## 
##  Pearson's Chi-squared test
## 
## data:  tableCr
## X-squared = 27.006, df = 4, p-value = 1.982e-05

The p-value of 1.982e-05 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that crime rate is not associated with employment status.

4.4.2 Family wrangles and employment status

## 
##  Pearson's Chi-squared test
## 
## data:  tableFw
## X-squared = 16.334, df = 4, p-value = 0.002602

The p-value of 0.002602 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that employment status is not associated with family wrangles.

4.4.3 Drug abuse and employment

## 
##  Pearson's Chi-squared test
## 
## data:  tableDr
## X-squared = 19.642, df = 4, p-value = 0.0005875

The p-value of 0.0005875 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that employment status is not associated with drug abuse.

4.4.4 Psychological problems and employment

## 
##  Pearson's Chi-squared test
## 
## data:  tablePsy
## X-squared = 9.0236, df = 4, p-value = 0.06051

The p-value of 0.06051 is greater than significance level of \(\alpha = 0.05\), we fail to reject the null hypothesis that employment status is not associated with psychological problems.

4.4.5 Corruption and employment

## 
##  Pearson's Chi-squared test
## 
## data:  tableCor
## X-squared = 24.26, df = 3, p-value = 2.205e-05

The p-value of 2.205e-05 is less than significance level of \(\alpha = 0.05\), we reject the null hypothesis that employment status is not associated with corruption.