¶ … Corresponding Table
A1.) The number of people I see at my workplace.
A2.) The number of phone calls I make.
A3.) The number of phone calls I receive.
A4.) The number of times I interact directly with a coworker.
A5.) The number of times I get up from my desk.
A6.) The number of times I use the water cooler.
A7.) The number of sheets of paper I write on with a pen.
A8.) The number of customers I speak with.
A9.) The number of work-related emails I receive.
A10.) The number of work-related emails I send.
A11.) The number of breaks I take outside the building.
A12.) The number of times I speak to my direct superior.
A13.) The number of questions I am asked regarding our company.
A14.) The number of times I go to the bathroom.
A15.) The number of snacks I have in the office.
A16.) The number of staples I use.
A17.) The number of hours spent doing data input.
A18.) The number of post-its I write on.
A19.) The number of mistakes I make while typing on the computer.
Representative Data Coordinates
AM
PM
A1
Aug. 10
A2
Aug. 10
A3
Aug. 11
A4
Aug. 11
A5
Aug. 12
A6
Aug. 12
A7
Aug. 13
A8
Aug. 13
A9
Aug. 14
A10
Aug. 14
A11
Aug. 15
A12
Aug. 15
A13
Aug. 16
A14
Aug. 16
A15
Aug. 17
A16
Aug. 17
A17
Aug. 18
A18
Aug. 18
3
1
A19
Aug. 19
7
4
Aug. 19
4
2
All figures are rounded off to 2 decimal places
Working table
(X-M) 2
E (x-M) 2 =1428.9 Ex = 179 N = 20
Ex = 179
N = 20
Mode = 5
Median = 6.5 ( 6 + 7/2)
Mean = 179/20 = 8.95
E (x-M) 2= 1428.9
S2 = 1428.9 / 20 = 71.45
S = 8.45
The mean is a bit higher than expected given the data. Looking at the frequency distribution above we see that there is an extreme score (42). The data therefore has a positive skew. The median may best describe the lifestyle measures as there is an outlier in the data which inflates the value of the mean.
The standard deviation is also a bit higher than expected due to the outlier (42) which inflates the variance somewhat.
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