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
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
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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
Transcribed Image Text:### Efficiency Improvement Analysis Through Training
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.
#### Data Summary
| | Before | After |
|------------------|--------|-------|
| **Mean** | 33.1 | 31.7 |
| **Variance** | 16.81 | 12.25 |
| **Observations** | 30 | 30 |
- **Hypothesized Mean Difference:** 0
- **Degrees of Freedom (df):** 29
- **t Statistic:** -2.282
- **P(T < t) one-tail:** 0.051
- **t Critical one-tail:** -1.699
- **P(T < t) two-tail:** 0.025
- **t Critical two-tail:** -2.045
- **Confidence Level:** 95%
#### Graph Explanation
The graph displays a standard bell curve representing the t-distribution, with labels for `p = Ex: 1.234` and `t = Ex: 1.234`.
#### Calculations
- **Sample Size (n):** \( n = \text{Ex: 9} \)
- **Point Estimate for Before Training (\( \bar{x}_{\text{before}} \)):** 33.1
- **Point Estimate for After Training (\( \bar{x}_{\text{after}} \))**: 31.7
### Key Terms Explained
- **Degrees of Freedom (df):** The number of values in a calculation that are free to vary.
- **t Statistic:** A ratio used in hypothesis testing.
- **P-Value:** Measures the probability that the observed data would occur by chance.
- **Confidence Level:** Indicates the reliability of the estimate.
This analysis demonstrates the statistical approach to evaluate the effectiveness of training on employee efficiency using samples, hypothesis testing, and t-distribution.
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