2a. Interpret the results in technical terms.
The p-value is less than 0.05, therefore indicates a statistically
significant correlation between satisfaction level and last evaluation
score.
3a. Interpret the results in non-technical terms.
Higher satisfaction level is associated with a higher last
evaluation score
4a. Create a plot that helps visualize the correlation.

2b. Interpret the results in technical terms.
The p-value is less than 0.05, therefore indicates a statistically
significant correlation between last evaluation and average monthly
hours.
3b. Interpret the results in non-technical terms.
Employees who work more hours tend to have higher evaluation
scores.
4b. Create a plot that helps visualize the correlation.

2c. Interpret the results in technical terms.
The p-value is less than 0.05, therefore indicates a statistically
significant correlation between time spent at the company and average
monthly hours
3c. Interpret the results in non-technical terms.
Employees who have been with the company longer tend to work more
hours per month.
4c. Create a plot that helps visualize the correlation.

2d. Interpret the results in technical terms.
The p-value is less than 0.05, therefore indicates a statistically
significant correlation between time spent at the company and
satisfaction level.
3d. Interpret the results in non-technical terms.
Employees who have been with the company longer tend to have
slightly lower satisfaction levels.
4d. Create a plot that helps visualize the correlation.
