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The objective of this assignment is to enable you to develop knowledge and skills in the following areas of competency: create an SPSS Statistics data file complete with variable definitions; input data from the sample dataset into the SPSS Statistics data file created under

Prepare the SPSS Statistics data file for descriptive and exploratory data analysis; and under take a reliability analysis to determine the internal consistency of the scale items.

Inferential Statistics and Hypotheses

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.

Null Hypothesis: There is no difference in work commitment of nurses across Gender

Alternate Hypothesis: There are differences in work commitment of nurses across Gender

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.

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.

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.

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.

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:

  • To what extent work related stress renders impact upon the intention to leave of the nurses?

t-test results

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 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.

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.

ANOVA results

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.

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 one of the parametric factors of intention to leave which is Work competency level. Thus the relevant research question can be highlighted as follows:

  • 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.

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 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.

Correlation analysis

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.

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.

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:

  • 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 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.

Regression analysis

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.

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.

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.

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 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:

  • To what extent Professional support received renders impact upon the work commitment/ intention to leave of the nurses?

Impact of Work Competency Level

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.

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 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.

Conclusion

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


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.

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.

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.

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


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 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.

 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. 

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.

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