Statistics for Data Science and Business Analysis - The Standard Normal Distribution

The video tutorial explains the process of standardizing distributions, transforming a variable to have a mean of zero and a standard deviation of one. It introduces the concept of a standard normal distribution, denoted by Z, and provides an example using a data set. The tutorial walks through the steps of subtracting the mean and dividing by the standard deviation to achieve standardization. It concludes by highlighting the benefits of using standardized data for predictions and inference.

What is the result called when a normal distribution is standardized?

• Standard deviation

• Standard normal distribution

• Standard mean

• Standard variance

In the example provided, what is the mean of the new data set after subtracting the original mean?

• 1

• 0

• 3

• 1.22

What happens to the standard deviation of a data set when you subtract the mean from each data point?

• It remains unchanged

• It doubles

• It halves

• It becomes zero

After dividing each data point by the standard deviation, what is the new standard deviation of the data set?

• 1.22

• 0

• 1

• 3

Why is using a standard normal distribution beneficial?

• It makes data collection easier

• It simplifies predictions and inference

• It increases the mean

• It decreases the variance