A company would like to know if efficiency can be improved through a training course for employees. A sample of employees is taken. The time taken for an employee to complete a task before training and after training is observed. Mean Variance Observations Hypothesized Mean Difference df t Stat P(T<=t) one-tail t Critical one-tail P(T<=t) two-tail t Critical two-tail Confidence Level n= Ex: 9 Before 33.1 16.81 30 Degrees of freedom: df = 0 29 -2.282 0.051 -1.699 0.025 -2.045 95% After 31.7 12.25 30 P = Ex: 1.234 -3 -2 -1 t = Ex: 1.234 Point estimate for before training: before Ex: 1.234 Point estimate for after training: after 0 2 3

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 2AGP
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A company would like to know if efficiency can be improved through a training course for employees. A sample of
employees is taken. The time taken for an employee to complete a task before training and after training is observed.
31.7
12.25
30
HA
P = Ex: 1.234
-3 -2 -1
t = Ex: 1.234
Mean
Variance
Observations
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail
Confidence Level
n = Ex: 9
Before After
33.1
16.81
30
29
-2.282
0.051
-1.699
0.025
-2.045
Degrees of freedom: df =
95%
Point estimate for before training: before Ex: 1.234
Point estimate for after training: after
2
Transcribed Image Text:A company would like to know if efficiency can be improved through a training course for employees. A sample of employees is taken. The time taken for an employee to complete a task before training and after training is observed. 31.7 12.25 30 HA P = Ex: 1.234 -3 -2 -1 t = Ex: 1.234 Mean Variance Observations Hypothesized Mean Difference df t Stat P(T<=t) one-tail t Critical one-tail P(T<=t) two-tail t Critical two-tail Confidence Level n = Ex: 9 Before After 33.1 16.81 30 29 -2.282 0.051 -1.699 0.025 -2.045 Degrees of freedom: df = 95% Point estimate for before training: before Ex: 1.234 Point estimate for after training: after 2
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