Exploring Characteristics of Normal Distribution

This video tutorial covers the characteristics of normal distribution, including the use of mean and standard deviation to describe it. It explains normal curves, inflection points, and the 68-95-99.7 rule. The tutorial uses examples like batting averages to illustrate these concepts and demonstrates how to calculate Z-scores. The video concludes with a summary and practice exercises.

What are the characteristics of a normal distribution?

• Symmetrical, unimodal, and bell-shaped

• Asymmetrical, bimodal, and skewed

• Symmetrical, bimodal, and uniform

• Asymmetrical, unimodal, and bell-shaped

What is a normal curve?

• A curve that is always concave down

• A density curve that is symmetrical and bell-shaped

• A curve that is always concave up

• A curve that has no inflection points

What are inflection points on a normal curve?

• Points where the curve is at its lowest

• Points where the curve is at its peak

• Points where the curve changes from concave up to concave down

• Points where the curve is symmetrical

What is the mean batting average for the St. Louis Cardinals from 1964 to 2013?

• 0.2925

• 0.2349

• 0.096

• 0.2637

How do you determine the scale when drawing a normal curve?

• By using the mean and standard deviation

• By using the range of the data

• By using the median value

• By using the mode value

According to the 68-95-99.7 rule, what percentage of data lies within one standard deviation of the mean?

• 68%

• 95%

• 34%

• 99.7%

What percentage of data lies within two standard deviations of the mean in a normal distribution?

• 34%

• 99.7%

• 95%

• 68%

What is the Z-score formula?

• (X - mean) / standard deviation

• (X + mean) / standard deviation

• (mean + X) / standard deviation

• (mean - X) / standard deviation

What does a Z-score of 0.55 indicate?

• 99.7% of the data lies below the mean

• 7.88% of the data lies below the mean

• 55% of the data lies below the mean

• 70.88% of the data lies below the mean

Why can't we simply average two values together to find the area under a normal curve?

• Because the curve is not a triangle

• Because the curve is not a straight line

• Because the curve is not a rectangle

• Because the curve is not symmetrical