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Inferential Stats and Interpretation

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Inferential Stats and Interpretation

PhoenixDrone

QNT/561

June 15, 2015

Inferential Statistics and Findings The team individually did an excellent job in interpreting the findings from their prospective. What would have been helpful is if we had used the same data sets to reach our conclusion. The team collaboration was completed after some of the individual papers had been completed and therefore the needed data was not used. The team agreed that null hypothesis would be the best approach to reaching a conclusion to answer the RQ.

(a) RQ: Is there a relationship between employee satisfaction (IV) and selected shifts and/or patient wait times (DV)?

b) Survey: eight questions were asked in the survey, from a population of 500, 386 answered the survey questions (n=386). The first three questions of preferred shifts to work, the majority was satisfied with the shifts they worked. The majority of employees did not admit to sometimes sleeping at work, overwhelmingly they strongly disagreed. The next question indicated there is a strong negative correlation with job satisfaction and appropriate staffing for adequate patient management as well as feeling appreciated at work.
The Hypothesis Statement:

H0} There is no correlation between employee satisfaction (IV) and selected shifts and/or patient wait times (DV)?

H1} There is correlation between employee satisfaction (IV) and selected shifts and/or patient wait times (DV)?

(c) The Hypothesis Statement: Testing the null hypothesis there is no relationship between the variables, and the alternative is there is a relationship between the variables. The level of significance used for rejecting the null hypothesis is set at .05, risking 5% chance of being wrong (McClave, 2011, p.319).

The null hypothesis is

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