Statistics Analysis

Statistics Analysis

Construct a table (similar to Table 1 that you would see in an article) that provides the descriptive statistics for the following variables: age, gender, education, years as a registered nurse, job satisfaction (as measured by the total score on the job satisfaction scale) and self-determination and autonomy (as measured by DPB-tot).

Table 1

In Statistics, descriptive summary is n affluent method that describes the nature of data. In the above table, the highest mean value has noticed in Job satisfaction and self determination and autonomy scale because the majority of the respondents has provided their responses in these questions. However, low average value has observed in gender and education because mostly participants have avoided that question. The standard deviation value has varies according to the average values of the given variables. The variance defines the difference in the data set.

Answer the following questions to examine the association between years as a registered nurse and job satisfaction (using variable named JSS_tot).

Correlation is used to examine the association between these two variables. State the null and alternative hypotheses for this particular review.

Hypothesis

HO: There is an association between nursing years and job satisfaction.

HA: There is no association between nursing years and job satisfaction.

Based on Pearson correlation coefficient seen above, how would you explain the association between years as RN and job satisfaction in words, including its direction and strength?

The correlation table is representing the positive correlation between the nursing years and job satisfaction. The relationship between the two conditions has positive value that is 0.193, which describes that the chances of probability in these two variables are totally correlated with each other. The more experience in nursing, the more job satisfaction she faced with her work.

Describe what this p-value means and make your conclusion about whether to reject or not to reject your null hypothesis as stated above.

The p-value or level of significance describes the probability of accepting or reject the null hypothesis that stated by researchers before analyzed a data. If the p value is less that significance value which is a, then the null hypothesis is true, otherwise it will false. In the above table, the p value is 0.0006 which is less than significance value. The result helps to determine that the null hypothesis is true and fails to accept the alternative hypothesis. With the accepting of the null hypothesis, it's clearly stated as; there is an association between nursing years and job satisfaction.

Based on the question above, state your independent and dependent variables?

Dependent Variable

For the study, nursing years is the dependent variable.

Independent Variable

Moreover, job satisfaction scale is the independent variable.

Interpret specifically the meaning of these two beta coefficients.

The constant beta coefficients remain constant in the model as it's not highly efficient with the change of independent and dependent variables. However, the beta of years nursing is defining the positive relationship with the targeted two ...