How do the ticket times of newly hired Panera Bread employees during lunch and dinner rush compare to the ticket times of experienced Panera Bread employees? Do the ticket times improve?
For this experiment, in two different cafes, the average ticket times for lunch rush(11am-3pm) and dinner rush(5pm-7pm) are recorded. One café has new employees, the other has only experienced employees. The first variable being the new employees, and the second one is the experienced employees. The outcome is the ticket times. However there are hidden variables such as the amount of food people ordered and if there are any special orders that would take extra time to make. My assumption for the results is that in the beginning of the experiment, the experienced employees will have faster ticket times but as the data is collected they will start to even out.



times


Experienced Employees Scatter Plot

New Employees Scatter Plot


New Employees
Correlation between var2 and var1 is:
-0.8068619

Experienced Employees
Correlation between var2 and var1 is:
-0.5347956

New Employees:
Simple linear regression results:
Dependent Variable: var1
Independent Variable: var2
var1 = 16.977882 - 1.4291438 var2
Sample size: 30
R (correlation coefficient) = -0.8069
R-sq = 0.65102607
Estimate of error standard deviation: 2.6418703

Parameter estimates:
Parameter
Estimate
Std. Err.
Alternative
DF
T-Stat
P-Value
Intercept
16.977882
1.3325595
≠ 9.93
28
5.288981
<0.0001
Slope
-1.4291438
0.19773987
≠ -0.46
28
-4.901105
<0.0001


Analysis of variance table for regression model:
Source
DF
SS
MS
F-stat
P-value
Model
1
364.5746
364.5746
52.235214
<0.0001
Error
28
195.42542
6.979479


Total
29
560












Experienced Employees:
Simple linear regression results:
Dependent Variable: var1
Independent Variable: var2
var1 = 14.551828 - 1.388982 var2
Sample size: 30
R (correlation coefficient) = -0.5348
R-sq = 0.2860063
Estimate of error standard deviation: 3.778872

Parameter estimates:
Parameter
Estimate
Std. Err.
Alternative
DF
T-Stat
P-Value
Intercept
14.551828
2.0744245
≠ 6.36
28
3.9489646
0.0005
Slope
-1.388982
0.41474104
≠ -0.21
28
-2.8426945
0.0083


Analysis of variance table for regression model:
Source
DF
SS
MS
F-stat
P-value
Model
1
160.16353
160.16353
11.216032
0.0023
Error
28
399.8365
14.279874


Total
29
560











After doing the experiment and recording the ticket times of each set of employees for 15 lunches and 15 dinners, you can see that at the beginning, the experienced employees did have the better ticket times. As the number of lunches and dinners went by, the new employees started to better there times and were closer to those of the experienced employees. The ticket times of new employees do improve over time.