Calculating relative errors
The size of the sample you take affects how accurately the point estimates reflect the corresponding population parameter. For example, when you calculate a sample mean, you want it to be close to the population mean. However, if your sample is too small, this might not be the case.
The most common metric for assessing accuracy is relative error. This is the absolute difference between the population parameter and the point estimate, all divided by the population parameter. It is sometimes expressed as a percentage.
attrition_pop and mean_attrition_pop (the mean of the Attrition column of attrition_pop) are available; pandas is loaded as pd.
This exercise is part of the course
Sampling in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Generate a simple random sample of 50 rows, with seed 2022
attrition_srs50 = ____
# Calculate the mean employee attrition in the sample
mean_attrition_srs50 = ____
# Calculate the relative error percentage
rel_error_pct50 = ____
# Print rel_error_pct50
print(rel_error_pct50)