Work Commitment Nurses - Assessment 2

This assignment evaluates the intention to leave of nurses using inferential statistics such as t-test, ANOVA and regression analysis. It explores the impact of work-related stress and work competency level on work commitment of nurses. The study finds no significant difference in work commitment across gender and ethnicity. However, work-related stress has a statistically significant impact on the intention to leave of nurses. Work competency level also has a negative correlation with work commitment.

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Running head: WORK COMMITMENT NURSES
WORK COMMITMENT NURSES – Assessment 2
Name of the Student
Name of the University
Author’s Note

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WORK COMMITMENT NURSES
Table of Contents
Introduction......................................................................................................................................2
Work Commitment Varies across Gender.......................................................................................2
Work Commitment Varies across Ethnicity....................................................................................3
Relation of Work Related Stress and Work Commitment...............................................................4
Work Competency Level.................................................................................................................7
Opportunities for Development.....................................................................................................12
Professional Support Received......................................................................................................15
Interpretation..................................................................................................................................19
Final Interpretation........................................................................................................................19
Conclusion.....................................................................................................................................22
References......................................................................................................................................24

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Introduction
In the present assignment we use inferential statistics to evaluate the intention to leave of
the nurses. For the inferential statistics we use t-test, ANOVA and regression analysis.
Work Commitment Varies across Gender
Null Hypothesis: There is no difference in work commitment of nurses across Gender
H0 : μMale =μFemale
Alternate Hypothesis: There are differences in work commitment of nurses across Gender
H0 : μMale ≠ μFemale
Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95
% confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05.
However, if the test statistic value falls within the 95 % confidence interval then null hypothesis
should be rejected and alternate hypothesis should be accepted. It will be interpreted that there
exists enough statistical evidence regarding the fact that work related stress has statistically
significant impact upon the intention to leave off the nurses (Black, 2016).
t-test: To test the hypothesis independent sample t-test is used.

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Table 1: Independent Samples Test
Commitment
Equal variances
assumed
Equal variances
not assumed
Levene's Test for Equality of
Variances
F 1.462
Sig. .228
t-test for Equality of Means T .808 .755
Df 184 69.016
Sig. (2-tailed) .420 .453
Mean Difference 2.282 2.282
Std. Error Difference 2.824 3.023
95% Confidence Interval of
the Difference
Lower -3.289 -3.748
Upper 7.854 8.313
Interpretation: From table 1 it is found that t(184) = 0.808, p-value = 0.420. Since p-value
(0.420) is more than the significance level (0.05) hence we do not reject the Null Hypothesis.
Discussion: Thus it can be inferred that there is no significant difference in intention to leave
between male and female nurses.
Work Commitment Varies across Ethnicity
Null Hypothesis: There is no difference in work commitment of nurses across Ethnicity
Alternate Hypothesis: There are differences in work commitment of nurses across Ethnicity
Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95
% confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05.
However, if the test statistic value falls within the 95 % confidence interval then null hypothesis
should be rejected and alternate hypothesis should be accepted. It will be interpreted that there
exists enough statistical evidence regarding the fact that work related stress has statistically
significant impact upon the intention to leave off the nurses.
One-way ANOVA : To test the hypothesis one-way ANOVA is used.

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Table 2: ANOVA
Commitment
Sum of Squares df Mean Square F Sig.
Between Groups 354.463 3 118.154 .425 .735
Within Groups 50626.276 182 278.166
Total 50980.739 185
Interpretation: From table 2 it is found that F(3,182) = 0.425, p-value = 0.735. Since p-value
(0.735) is more than the significance level (0.05) hence we do not reject the Null Hypothesis.
Discussion: Thus it can be interpreted that there is no significant difference in intention to leave
between ethnicity of nurses.
Relation of Work Related Stress and Work Commitment
Research Questions: The research question is concerns with the ability of work related stress to
influence the intention to leave of the nurses. Thus the relevant research question can be
highlighted as follows:
1) To what extent work related stress renders impact upon the intention to leave of the
nurses?
Null Hypothesis (H0) = Work related stress renders significant impact upon the intention to leave
of the nurses.
Alternate Hypothesis (H1) = Work related stress has no impact upon the intention to leave of the
nurses.
Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95
% confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05.
However, if the test statistic value falls within the 95 % confidence interval then null hypothesis
should be rejected and alternate hypothesis should be accepted. It will be interpreted that there

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exists enough statistical evidence regarding the fact that work related stress has statistically
significant impact upon the intention to leave off the nurses (Anderson et al., 2017).
Analysis:
Table 3: Descriptive Statistics
Mean Std. Deviation N
Commitment 66.07 16.600 186
Work Related
Stress
15.92 4.363 186
The statistical valuations incorporate the fact that mean values of work related stress is
15.92 and the mean of 66.07. While the respective standard deviation is 4.363 and 16.600. The
total number of sample population 186.
Table 4: Correlations
Commitment Work Related Stress
Pearson Correlation Commitment 1.000 -.206
Work Related Stress -.206 1.000
Sig. (1-tailed) Commitment . .002
Work Related Stress .002 .
N Commitment 186 186
Work Related Stress 186 186
From the correlation table it is seen that the Pearson correlation between work
related stress and that of work commitment is -0.206. This reflects the fact that the correlation
that exists between work commitment and work related stress is negatively and moderately
correlated.

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Based on the sample population there is statistically significant evidence that shows that
the 1 tailed significance is 0.002 which is lower than the alpha level of the p value taken under
consideration which is 0.05. Due to the reason that 0.002 < 0.05 hence, the correlation between
work commitment and that of work related stress is - 0.206 which shows that the correlation is
negative and the correlation is statistically significant as there exists enough evidence that
supports the fact that there is prevalence of significant correlation between work related stress
and work commitment within the nurses.
Table 5: Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
1 .206a .042 .037 16.289
a. Predictors: (Constant), Work Related Stress
The R square value represent the percentage of variation of the dependent variable that is
explainable by the independent or explanatory variable which is the work related stress. R square
is thus considered as the coefficient of determination and the correlation measurement is
considered to be the goodness of fit. It is been seen that the value of R square is 0.042 and hence
nearby 4.2 % of work commitment is predictable by the work related stress. Thus about 4.2 % of
variation in the work commitment is due to the work related stress.

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Table 6: ANOVA
Model Sum of Squares df Mean Square F Sig.
1
Regression 2160.626 1 2160.626 8.143 .005b
Residual 48820.113 184 265.327
Total 50980.739 185
a. Dependent Variable: Commitment
Table 7: Coefficients
Model
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) 78.538 4.530 17.338 .000
WorkRelatedStress -.783 .274 -.206 -2.854 .005
a. Dependent Variable: Commitment
Based on the values the regression equation can be formulated as follows:
 Y = 78.538 – 0.783*Work Related Stress
Where the coefficient is – 0.783 and the intercept is 78.538. -0.783 is the slope of the line and
78.538 is the intercept.
Work Competency Level
Research Questions
The research question is concerns with the ability of Work competency level to influence
the intention to leave of the nurses. Based on the purpose of the research, the research questions
are incorporated in order to predict the variation and impact upon nurses’ work commitment by

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one of the parametric factors of intention to leave which is Work competency level. Thus the
relevant research question can be highlighted as follows:
1) To what extent Work competency level renders impact upon the intention to leave of the
nurses?
Null Hypothesis
The null and the alternate hypothesis are:
Null Hypothesis (H0) = Work competency level renders significant impact upon the intention to
leave/work commitment of the nurses.
Alternate Hypothesis (H1) = Work competency level has no impact upon the intention to leave/
work commitment of the nurses.
Decision Rule
Based on the null and alternate hypotheses, the respective decision rule can be reflected
as follows:
Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95
% confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05.
However, if the test statistic value falls within the 95 % confidence interval then null hypothesis
should be rejected and alternate hypothesis should be accepted. It will be interpreted that there
exists enough statistical evidence regarding the fact that Work competency level has statistically
significant impact upon the intention to leave off the nurses.

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Table 8: Descriptive Statistics
Mean Std. Deviation N
Commitment 66.07 16.600 186
Work Competency Level 20.85 5.144 186
The statistical valuations incorporates the fact that mean values of Work competency
level is 20.85 and the mean of 66.07. While the respective standard deviation is 5.144 and
16.600. The total number of sample population 186.
Table 9: Correlations
Commitment Work Competency Level
Pearson Correlation
Commitment 1.000 -.151
Work Competency Level -.151 1.000
Sig. (1-tailed)
Commitment . .020
Work Competency Level .020 .
N
Commitment 186 186
Work Competency Level 186 186
From the correlation table it is seen that the correlation coefficient in case of
Work competency level and that of work commitment is - 0.151. This reflects the fact that the
correlation that exists between work commitment and Work competency level is negatively and
moderately correlated.
Based on the sample population there is statistically significant evidence that shows that
the 1 tailed significance is 0.02 which is lower than the alpha level of the p value taken under

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consideration which is 0.05. Due to the reason that 0.02 < 0.05 hence, the correlation between
work commitment and that of Work competency level is - 0.151 which shows that the correlation
is negative and the correlation is statistically significant as there exists enough evidence that
supports the fact that there is prevalence of significant correlation between Work competency
level and work commitment within the nurses.
The dependent variable in the analysis is the work commitment and hence the impact of
the Work competency level upon that of the work commitment of the nurses is being evaluated.
Hence the response variable is work commitment and the explanatory variable is Work
competency level.
Table 10: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .151a .023 .018 16.454
a. Predictors: (Constant), Work Competency Level
The R square value represent the percentage of variation of the dependent variable that is
explainable by the independent or explanatory variable which is the Work competency level. R
square is thus considered as the coefficient of determination and the correlation measurement is
considered to be the goodness of fit. It is been seen that the value of R square is 0.023 and hence
nearby 2.3 % of work commitment is predictable by the Work competency level. Thus about 2.3
% of variation in the work commitment is due to the Work competency level.

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Table 11: ANOVA
Model Sum of Squares df Mean Square F Sig.
1
Regression 1166.111 1 1166.111 4.307 .039b
Residual 49814.628 184 270.732
Total 50980.739 185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Work Competency Level
Table 12: Coefficients
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 76.244 5.049 15.100 .000
Work Competency Level -.488 .235 -.151 -2.075 .039
a. Dependent Variable: Commitment
Based on the values the regression equation can be formulated as follows:
 Y = 76.244 – 0.488* Work Competency Level
Where the coefficient is -0.488 and the intercept is 76.244.

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Opportunities for Development
Research Questions
The research question is concerns with the ability of Opportunities for development to
influence the intention to leave of the nurses. Based on the purpose of the research, the research
questions are incorporated in order to predict the variation and impact upon nurses’ work
commitment by one of the parametric factors of intention to leave which is Opportunities for
development. Thus the relevant research question can be highlighted as follows:
1) To what extent Opportunities for development renders impact upon the intention to leave
of the nurses?
Null Hypothesis
The null and the alternate hypothesis are:
Null Hypothesis (H0) = Opportunities for development renders significant impact upon the
intention to leave/work commitment of the nurses.
Alternate Hypothesis (H1) = Opportunities for development has no impact upon the intention to
leave/work commitment of the nurses.
Decision Rule
Based on the null and alternate hypotheses, the respective decision rule can be reflected
as follows:
Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95
% confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05.
However, if the test statistic value falls within the 95 % confidence interval then null hypothesis
should be rejected and alternate hypothesis should be accepted. However, if it be found to have
its presence within the 5 % level of significance then null hypothesis will be accepted and the

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alternative hypothesis will be accepted. It will be interpreted that there exists enough statistical
evidence regarding the fact that Opportunities for development has statistically significant
impact upon the intention to leave off the nurses.
Univariate Data Analysis
Table 13: Descriptive Statistics
Mean Std. Deviation N
Commitment 66.07 16.600 186
Opportunities for Development 18.51 4.843 186
The statistical valuations incorporates the fact that mean values of Opportunities for
development is 18.51 and the mean of 66.07. While the respective standard deviation is 4.843
and 16.600. The total number of sample population 186.
Table 14: Correlations
Commitment Opportunities for
Development
Pearson Correlation Commitment 1.000 -.088
Opportunities for Development -.088 1.000
Sig. (1-tailed) Commitment . .115
Opportunities for Development .115 .
N Commitment 186 186
Opportunities for Development 186 186
The value of the correlation coefficient in case of Opportunities for development
and that of work commitment is -0.088. This reflects the fact that the correlation that exists
between work commitment and Opportunities for development is negatively and moderately
correlated.

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Based on the sample population there is statistically significant evidence that shows that
the 1 tailed significance is 0.115 which is higher than the alpha level of the p value taken under
consideration which is 0.05. Due to the reason that 0.115 > 0.05 hence, the correlation between
work commitment and that of Opportunities for development is - 0.115 which shows that the
correlation is negative and the correlation is statistically insignificant as there does not exists
enough evidence that supports the fact that there is prevalence of significant correlation between
Opportunities for development and work commitment within the nurses.
The dependent variable in the analysis is the work commitment and hence the impact of
the Opportunities for development upon that of the work commitment of the nurses is being
evaluated. Hence the response variable is work commitment and the explanatory variable is
Opportunities for development.
Table 15: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .088a .008 .002 16.580
a. Predictors: (Constant), Opportunities for Development
The R square value represent the percentage of variation of the dependent variable that is
explainable by the independent or explanatory variable which is the Opportunities for
development. R square is thus considered as the coefficient of determination and the correlation
measurement is considered to be the goodness of fit. It is been seen that the value of R square is
0.008 and hence nearby 0.8 % of work commitment is predictable by the Opportunities for
development. Thus about 0.8 % of variation in the work commitment is due to the Opportunities
for development.

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Table 16: ANOVA
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 398.994 1 398.994 1.451 .230b
Residual 50581.745 184 274.901
Total 50980.739 185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Opportunities for Development
Table 17: Coefficients
Coefficients
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 71.682 4.816 14.886 .000
Opportunities for
Development -.303 .252 -.088 -1.205 .230
a. Dependent Variable: Commitment
Based on the values the regression equation can be formulated as follows:
 Y = 71.682 – 0.303*Opportunities for Development
Where the coefficient is – 0.303 and the intercept is 71.682.
-0.303 is the slope of the line and 71.682 is the intercept.
Professional Support Received
Research Questions
The research question is concerns with the ability of Professional support received to
influence the intention to leave of the nurses. Based on the purpose of the research, the research
questions are incorporated in order to predict the variation and impact upon nurses’ work

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commitment by one of the parametric factors of intention to leave which is Professional support
received. Thus the relevant research question can be highlighted as follows:
1) To what extent Professional support received renders impact upon the work commitment/
intention to leave of the nurses?
Null Hypothesis
The null and the alternate hypothesis are:
Null Hypothesis (H0) = Professional support received renders significant impact upon the work
commitment/ intention to leave of the nurses.
Alternate Hypothesis (H1) = Professional support received has no impact upon the work
commitment/intention to leave of the nurses.
Decision Rule
Based on the null and alternate hypotheses, the respective decision rule can be reflected
as follows:
Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95
% confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05.
However, if the test statistic value falls within the 95 % confidence interval then null hypothesis
should be rejected and alternate hypothesis should be accepted. It will be interpreted that there
exists enough statistical evidence regarding the fact that Professional support received has
statistically significant impact upon the intention to leave off the nurses.

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Univariate Data Analysis
Table 18: Descriptive Statistics
Mean Std. Deviation N
Commitment 66.07 16.600 186
Professional Support Received 21.26 4.874 186
The statistical valuations incorporates the fact that mean values of Professional support
received is 21.26 and the mean of 66.07. While the respective standard deviation is 4.874 and
16.600. The total number of sample population 186.
Table 19: Correlations
Correlations
Commitment Professional Support
Received
Pearson Correlation Commitment 1.000 -.138
Professional Support Received -.138 1.000
Sig. (1-tailed) Commitment . .030
Professional Support Received .030 .
N Commitment 186 186
Professional Support Received 186 186
The value of the correlation coefficient in case of Professional support received and that
of work commitment is -0.138. This reflects the fact that the correlation that exists between work
commitment and Professional support received is negatively and moderately correlated.
Based on the sample population there is statistically significant evidence that shows that
the 1 tailed significance is 0.03 which is lower than the alpha level of the p value taken under
consideration which is 0.05. Due to the reason that 0.03 < 0.05 hence, the correlation between
work commitment and that of Professional support received is - 0.138 which shows that the
correlation is negative and the correlation is statistically significant as there exists enough

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evidence that supports the fact that there is prevalence of significant correlation between
Professional support received and work commitment within the nurses.
The dependent variable in the analysis is the work commitment and hence the impact of
the Professional support received upon that of the work commitment of the nurses is being
evaluated. Hence the response variable is work commitment and the explanatory variable is
Professional support received.
Table 20: Model Summary
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .138a .019 .014 16.485
a. Predictors: (Constant), Professional Support Received
The R square value represent the percentage of variation of the dependent variable that is
explainable by the independent or explanatory variable which is the Professional support
received. R square is thus considered as the coefficient of determination and the correlation
measurement is considered to be the goodness of fit. It is been seen that the value of R square is
0.019 and hence nearby 1.9 % of work commitment is predictable by the Professional support
received. Thus about 1.9 % of variation in the work commitment is due to the Professional
support received.
Table 21: ANOVA
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 977.255 1 977.255 3.596 .059b
Residual 50003.484 184 271.758
Total 50980.739 185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Professional Support Received

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Table 22: Coefficients
Coefficients
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 76.092 5.422 14.034 .000
Professional Support
Received -.472 .249 -.138 -1.896 .059
a. Dependent Variable: Commitment
Based on the values the regression equation can be formulated as follows:
 Y = 76.092 – 0.472 * Professional Support Received
Where the coefficient is – 0.472 and the intercept is 76.092. -0.472 is the slope of the line and
76.092 is the intercept.
Interpretation
Moreover, the p value reflects that beyond 95 % confidence interval and 5 % level of
significance the p value of Professional support received is 0.059 which is more than 0.05.
Hence, the null hypothesis is rejected that Professional support received possess weak impact
upon the work commitment and the relationship that exists between professional supports
received and work commitment of the nurses is insignificant.
Final Interpretation

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Multivariate Data Analysis
Table 23: Descriptive Statistics
Mean Std. Deviation N
Commitment 66.07 16.600 186
Work Related Stress 15.92 4.363 186
Work Competency Level 20.85 5.144 186
Opportunities for Development 18.51 4.843 186
Professional Support Received 21.26 4.874 186
It is been seen that the lowest standard deviation from mean is observed in case of work
related stress where the value is 4.363.
Table 24: Model Summaru
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .231a .053 .033 16.328
a. Predictors: (Constant), Professional Support Received, Work Related Stress, Work Competency Level,
Opportunities for Development
The R square value represent the percentage of variation of the dependent variable that is
explainable by the independent or explanatory variable. R square is thus considered as the
coefficient of determination and the correlation measurement is considered to be the goodness of
fit. It is been seen that the value of R square is 0.53 and hence nearby 53 % of work commitment
is predictable by the Opportunities for development. Thus about 53 % of variation in the work
commitment is due to the explanatory variables. The adjusted R square is a more reliable test
statistic since it takes under consideration the population sample size which interprets the fact
that about 33 % of the variation in the work commitment. The standard error measures the
variability of the actual work commitment from the predicted value of the work commitment
whose value came out to be 16.328.

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Table 25: ANOVA
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 2724.501 4 681.125 2.555 .041b
Residual 48256.238 181 266.609
Total 50980.739 185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Professional Support Received, Work Related Stress, Work Competency Level,
Opportunities for Development
Table 26: Coefficients
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 78.957 5.652 13.971 .000
Work Related Stress -.886 .412 -.233 -2.152 .033
Work Competency Level -.246 .407 -.076 -.604 .547
Opportunities for
Development .636 .441 .186 1.444 .150
Professional Support
Received -.256 .396 -.075 -.646 .519
a. Dependent Variable: Commitment
Based on the values the regression equation can be formulated as follows:
 Commitment = 78.957 – 0.886*Work Related Stress – 0.246 *Work Competency Level –
0.636*Opportunities for Development – 0.256*Professional Support Received
Interpretation
Thus the test is has passed. Moreover, the p value reflects that beyond 95 % confidence
interval and 5 % level of significance the p value of work related stress is 0.033 which is less
than 0.05. Hence, the null hypothesis is accepted that work related possess strong impact upon

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the work commitment and the relationship that exists between works related stress and work
commitment of the nurses is strongly significant.
Conclusion
In order to understand the relation between Commitment to work and Work Related
Stress, Work Competency Level, Opportunities for Development and Professional Support
Received both univariate as well multivariate regression analysis was used. In addition,
correlation analysis was also used.
The correlation analysis shows that all the four factors Work Related Stress, Work
Competency Level, Opportunities for Development and Professional Support Received are
negatively correlated with commitment. Moreover, all the four variables are weekly correlated.
The relation of work related stress with commitment shows that with increase in stress,
there is a decrease in commitment towards work. Moreover, the coefficient of work related stress
is statistically significant. In addition, the predictability of commitment from work related stress
is also very weak.
The relation of work competency level with commitment shows that with increase in
competency level, there is a decrease in commitment towards work. Moreover, the coefficient of
work competency level is statistically significant. In addition, the predictability of commitment
from work competency level is also very weak.
The relation of opportunities for development with commitment shows that with increase
in opportunities, there is a decrease in commitment towards work. Moreover, the coefficient of
opportunities for development is statistically not significant. In addition, the predictability of
commitment from opportunities for development is negligible.

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The relation of professional support received with commitment shows that with increase
in professional support, there is a decrease in commitment towards work. Moreover, the
coefficient for professional support received is statistically not significant. In addition, the
predictability of commitment from professional support received is negligible.
The multivariate analysis shows that four variables can significantly predict commitment.
However, the coefficients of Work Competency Level, Opportunities for Development and
Professional Support Received are not statistically significant. Moreover, the predictability of
commitment from the four variables is also poor.

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References
Black, K. (2016). Business statistics: for contemporary decision making. 9th Edition. John Wiley
& Sons.
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2017).
Essentials of Modern Business Statistics With Microsoft Excel.. South–Western Pub.