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Owner: annakmcg
Created: Jun 20, 2019
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Sleep Patterns of Night Shift Workers Impact on Energy Level When On-the-Job
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Sleep Patterns of Night Shift Workers Impact on Energy Level When On-the-Job

The purpose of our survey was to gather data of the sleep habits of individuals working the night shift and the impact it had on their energy level while at work.

The population was American adults. Our sample included nurses working the night shift. Individuals surveyed answered four questions (two numeric, two categorical) regarding their sleep patterns when working the night shift and the impact it seemed to have on their energy level while working.

The sampling was obtained in several ways, including in person, by telephone, text messaging, online by email. Because it was not random, it would be considered a convenience sample and those who participated, did so voluntarily.

The four questions included:

Do you prefer to work night shift? (Select one): Yes/No

How many hours do you sleep prior to your shift? (Enter a numeric response)

How many hours do you sleep when you are not working? (Enter a numeric response)

Describe how you feel while you are at work: Extremely tired, Moderately tired, Somewhat tired, Full of energy. Somewhat tired.

Looking at a Categorical Variable, the surveyed described their energy level at work. This is illustrated in Result 1 (pie chart) below.

What stood out immediately was that 77.85% of nurses working the night shift were tired to some degree. Having done it myself for 10 years, I will testify. I didn’t realize that I was in the (suffering in silence) majority, though.

In order to see if the C2 responses differ according to C1, I graphed Result 2 (bar plot).

Well this result speaks volumes…do what you love? There seems to be a definite correlation between preferring to work the night shift and an increase in energy level. Those who didn’t like working the night shift claimed a higher level of fatigue with fewest being ‘full of energy’.

Looking at a Numerical Variable, I chose to histogram, boxplot and provide summary statistics for the question: how many hours of sleep to you get before work? Result 3, 4 and 5. They follow below.

The histogram exhibits left-skewed distribution with most of the data appearing between 4 and 8 hours, with a gap for 1 hour of sleep prior to work.

The boxplot reveals left skewed data as well, with an outlier of 0 hours way beyond the left fence. (like out by the monuments at Yankee Stadium!)

Summary statistics:

Column

n

Mean

Variance

Std. dev.

Median

Range

Min

Max

Q1

Q3

Hours prior to working

86

5.4418605

4.0142271

2.0035536

6

9

0

9

4.5

7

There wasn’t much variability in responses, except for the Zombie outliers, who didn’t sleep at all prior to work. The median was slightly larger than the mean, and thus the left-skewed distribution. Even with the 0 hour of non-sleepers, the range was only 9, which is not a huge spread.

Result 6, the scatterplot of N1 vs N2 (hours of sleep prior to vs. hours of sleep after work) was quite scattered. I thought I graphed it wrong, perhaps I did. However, this was the result after a few tries. If I squint, perhaps an ever so slight downward trend can be noted.

Correlation between Hours prior to working and Hours when not working is:
-0.27958475

Result 1: Pie Chart With Data (Alertness at Work)   [Info]
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Result 2: Bar Plot With Data C2 vs C1 Correlation   [Info]
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Result 3: Histogram Hours Slept Prior to Work   [Info]
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Result 4: Boxplot Hours Slept Prior to Work   [Info]
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Result 5: Scatter Plot Hours of Sleep Prior to vs After Work   [Info]
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Data set 1. Responses_to_Night_shift_sleeping (1).csv   [Info]
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