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Created: Nov 15, 2017
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Inferential statistics report
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I.  Introduction :

Group 1 conducted a survey to determine if different levels of nursing education effected the hours that were worked by that nurse in a week and if it effected the type of work they do, such as working directly in patient care. We also wanted to know the ages between the varying levels of education.  The population we sampled was working nurses. We obtained responses by surveying randomly selected nurses we work with, know, or have come across. The sample consists of 135 responses.

 The following were the answered survey questions:

1. In a typical week, how many hours do you work?  _____hours

2. How many years of experience do you have as a nurse? ______years

3. Do you spend a majority of your time providing direct patient care? Select one:   Yes     No

4. What is your education level? Select one:  LVN/LPN   ADN   BSN   MSN   DNP   other

 

II. Looking at a Categorical  Variable

a.       Collected responses to the question “Do you spend the majority of your time providing direct patient care?” is displayed in the pie chart below.

 

 

Result 1: Pie Chart project 4   [Info]
Right click to copy

We are able to determine that out of the 135 responses 112 nurses, or 82.96%, do work directly with patients while 23, or 17.04%, do not.

b.     

     

Result 2: One sample proportion summary confidence interval project 4   [Info]
One sample proportion summary confidence interval:
p : Proportion of successes
Method: Standard-Wald

95% confidence interval results:
ProportionCountTotalSample Prop.Std. Err.L. LimitU. Limit
p1121350.829629630.03235730.766210490.89304877

      Confidence interval use a range of values  from the sample to determine the true population parameter. We can see  our proportion summary  results in the chart above determined by  a 95% confidence interval for the surveyed group that answered “yes- they do work directly with patient care".  With a sample size n=135 we can interpret that we are 95% confident that the interval from 0.766 to 0.893 contains the population proportion p and 95% of selected samples will also contain the population proportion p.

 

III. Looking at a Numerical Variable

a. Looking at the question “ how many years’ experience do you have” we can analyze the results      by the histogram and summary statistics below.

Result 3: Histogram project 4   [Info]
Right click to copy

Result 4: Summary Stats project 4   [Info]
Summary statistics:
ColumnnMeanVarianceStd. dev.MedianRangeMinMaxQ1Q3Mode
yrs experience1359.8111111109.1823410.4490355500503125

            b.  When developing a confidence interval for a population mean, the results based on our sanoke                    are as shown below.

 

 

Result 5: One sample T confidence interval project 4 mean   [Info]
One sample T confidence interval:
μ : Mean of variable

95% confidence interval results:
VariableSample MeanStd. Err.DFL. LimitU. Limit
yrs experience9.81111110.899309771348.032433111.589789

Based upon the results shown, we can conclude that we are 95% confident that  the results  of our sample contains the true proportion mean; we are 95% confident that the average nurse has between 8 and 11 years’ experience. a T- interval was used based upon the fact that the population standard deviation was not known. 

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<A href="https://www.statcrunch.com/5.0/viewreport.php?reportid=73856">Inferential statistics report</A>

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