This work focuses on checking some of the factors that affect number of hours worked. The study uses number of hours worked as the dependent variable. This variable is measured in a continuous scale. Three independent variables were used to check on their relationship with the dependent variable. The independent variables are: Age, Gender (Sex) and highest degree obtained. Age is a continuous variable, whereas sex and highest degree obtained have been measure on the ordinal scale. Data from 1490 respondent were used in this study.
To check on the relationship of the variables, data analysis was performed and the results presented in form of demographic characteristics, correlation analysis and regression analysis. The results are presented in tables and charts as shown below.
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Table 1 :
Descriptive Statistics for Number of Hours Worked
|
N |
Range |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
|---|---|---|---|---|---|---|
| NUMBER OF HOURS WORKED LAST WEEK |
895 |
88 |
1 |
89 |
41.47 |
15.039 |
From the descriptive analysis of number of hours worked above, it is evident that the mean number of hours was 41.47 hours, with a standard deviation of 15.039 hours. The minimum number of hours worked was 1 hour, the maximum number of hours were 89 hours and a range of 88 hours.
Table 2 :
Descriptive Statistics for Age
|
N |
Range |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
|---|---|---|---|---|---|---|
| AGE OF RESPONDENT |
1490 |
71 |
18 |
89 |
50.12 |
17.073 |
The descriptive analysis on age, as indicated in table 2 revealed that the mean age was 50.12 years, with a standard deviation of 170.013 years. The minimum age was 18 years, maximum age was 89 years and a range of 71 years.
Table 3 :
Frequency of Highest Degree Obtained
|
Frequency |
Percent |
|
|
LT HIGH SCHOOL HIGH SCHOOL JUNIOR COLLEGE BACHELOR GRADUATE Total |
177 |
11.8 |
|
737 |
49.1 |
|
|
118 |
7.9 |
|
|
292 |
19.5 |
|
|
176 |
11.7 |
|
|
1500 |
100.0 |
Findings in table 3 above revealed that majority of the respondents (49.1%), were high school graduates, while the least number of respondents (7.9%) were junior college graduates.
Figure 1 : Highest Degree Obtained
Findings in figure 1 above confirm the results obtained in table 3. That is: majority of the respondents (49.1%), were high school graduates, while the least number of respondents (7.9%) were junior college graduates.
Table 4 :
Frequencies of Gender
|
Frequency |
Percent |
|
|
MALE FEMALE Total |
672 |
44.8 |
|
828 |
55.2 |
|
|
1500 |
100.0 |
Findings in table 4 revealed that 44.8% of the respondents were male, while 55.2% (the majority) were females.
Figure 2 : Gender of Respondents
Results in figure 2 confirm the results obtained in table 4 that, majority of the respondents were females (55.2%), while 44.8% were males.
Table 5 :
Correlation of variables
NUMBER OF HOURS WORKED LAST WEEK |
AGE OF RESPONDENT |
RS HIGHEST DEGREE |
RESPONDENTS SEX |
|
|---|---|---|---|---|
| NUMBER OF HOURS WORKED LAST WEEK |
1 |
-.065 |
.097 |
-.166 |
| AGE OF RESPONDENT |
-.065 |
1 |
.032 |
.026 |
| RS HIGHEST DEGREE |
.097 |
.032 |
1 |
-.019 |
| RESPONDENTS SEX |
-.166 |
.026 |
-.019 |
1 |
The findings in table 5 above sow the correlations between the variables selected for this study. To understand the results, we consider correlations between each independent variable and the dependent variable. From the results, age and the number of hours worked had a correlation of -0.065 (-6.5%). This implies that a unit increase in age, led to a decrease in the number of hours worked by 6.5%. Highest degree obtained and number of hours worked had a correlation of 0.097 (9.7%). This implies a unit increase in highest degree led to a unit increase in the number of hours worked by 9.7%. Correlation between gender and number of hours worked is -0.166 (-16.6%). From additional checks, it is confirmed that women worked approximately -16.6% less hours than men.
Table 6 :
Analysis of Variance (ANOVA)
| Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|---|---|---|---|---|---|
|
Regression Residual Total |
8469.165 |
3 |
2823.055 |
12.986 |
.000 a |
|
192827.921 |
887 |
217.393 |
|||
|
201297.086 |
890 |
||||
|
a. Predictors: (Constant), RESPONDENTS SEX, AGE OF RESPONDENT, RS HIGHEST DEGREE b. Dependent Variable: NUMBER OF HOURS WORKED LAST WEEK |
|||||
Using the selected independent variables and the dependent variables, a multiple regression analysis of variance was performed. Age, gender and highest degree obtained were the independent variables while number of hours worked was the dependent variable. From the ANOVA results, it is evident that the model was significant in checking the relationship between the variables, F = 12.986, p < 0.0001.
Table 7 :
Model Coefficients
| Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
|
|---|---|---|---|---|---|
|
B |
Std. Error |
Beta |
|||
|
(Constant) AGE OF RESPONDENT RS HIGHEST DEGREE RESPONDENTS SEX |
50.345 |
2.361 |
21.328 |
.000 |
|
|
-.083 |
.037 |
-.074 |
-2.258 |
.024 |
|
|
1.244 |
.406 |
.101 |
3.061 |
.002 |
|
|
-4.979 |
.988 |
-.166 |
-5.039 |
.000 |
|
| a. Dependent Variable: NUMBER OF HOURS WORKED LAST WEEK | |||||
The model coefficient results confirm that all the independent variables are significant predictors of number of hours worked, considering their t and p values. Age ( t = -2.258, p = 0.024); Highest degree ( t = 3.061, p = 0.002); respondents’ sex ( t = -5.039, p < 0.0001). Additionally, the table give the model coefficients (‘B’ column). The model is as given below:
Number of hours worked = 50.345 – 0.083 (Age) + 1.244 (Degree) – 4.979 (Gender)
Conclusions
From the data analysis performed, the results confirmed that the selected independent variables are significant predictors of the dependent variables. Therefore age, gender and highest degree obtained are all significant factors that affect the number of hours worked.
