## 
##  Pearson's product-moment correlation
## 
## data:  satisfaction_level and last_evaluation
## t = 12.933, df = 14997, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.08916727 0.12082195
## sample estimates:
##       cor 
## 0.1050212
## `geom_smooth()` using formula = 'y ~ x'

p-value interpretation: The p-value is below my threshold of 0.1, therefore the correlation between last evaluation and satisfaction level is significant.

correlation estimate interpretation: The correlation is positive and small.

non-technical interpretation: The higher last evaluation, higher satisfaction level.

## 
##  Pearson's product-moment correlation
## 
## data:  satisfaction_level and average_montly_hours
## t = -2.4556, df = 14997, p-value = 0.01408
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.036040356 -0.004045605
## sample estimates:
##         cor 
## -0.02004811
## `geom_smooth()` using formula = 'y ~ x'

p-value interpretation: The p-value is above my p-threshold of 0.1, therefore the correlation between satisfaction level and average monthly hours is insignificant.

correlation estimate interpretation: There is no correlation.

non-technical interpretation: No relation between average monthly hours and satisfaction level.

## 
##  Pearson's product-moment correlation
## 
## data:  number_project and average_montly_hours
## t = 56.219, df = 14997, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.4039037 0.4303411
## sample estimates:
##       cor 
## 0.4172106
## `geom_smooth()` using formula = 'y ~ x'

p-value interpretation: The p-value is below my p-threshold of 0.1, therefore the correlation between number project and average monthly hours is significant.

correlation estimate interpretation: The correlation is positive and moderate.

non-technical interpretation: The higher number project, higher average monthly hours.

## 
##  Pearson's product-moment correlation
## 
## data:  satisfaction_level and time_spend_company
## t = -12.416, df = 14997, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.11668153 -0.08499948
## sample estimates:
##        cor 
## -0.1008661
## `geom_smooth()` using formula = 'y ~ x'

p-value interpretation: The p-value is below my p-threshold of 0.1, therefore the correlation between time spend company and satisfaction level is significant.

correlation estimate interpretation: The correlation is negative and small.

non-technical interpretation: The higher time spend company, lower satisfaction level.