The video begins with the explanation of a normal distribution using students' heights as an example.

• Visited a school to measure student heights, which ranged from 0.9 to 2.1 meters.
• Heights marked at intervals of 0.2 meters, with the number of students plotted on the y-axis showing a peak at 1.5 meters.
• The distribution is symmetric around the central value of 1.5 meters, resembling a bell curve.

Income distribution in a particular region is used to illustrate positive skewness.

• Graphed annual income ranging from $10,000 to $100,000, with most earnings between $20,000 and $50,000.
• The central value of the income data was around $50,000, with a long tail on the right-hand side indicating positive skewness.

The video provides an example of negative skewness using the distribution of test scores.

• Collected data on student test scores, which ranged from 20 to 80.
• Most students scored between 50 and 80, showing a distribution with a tail on the left side of the central value, indicative of negative skewness.

The video concludes by comparing normal, positively skewed, and negatively skewed distributions.

• Normal distribution is symmetric around the central value, while skewed distributions are not.
• Positive skewness has a tail on the right side of the central value, while negative skewness has it on the left.