STRAIGHT STATISTICS

Normal Distribution

The normal distribution is said to be the most popular probability distribution. There are two types of probability distribution; the discrete and continuous.

Importance of Normal Distribution in Statistics

1. It has some properties that make it applicable to a great many situations in which is necessary to make inferences by taking samples.
2. The normal distribution comes close to fitting the actual human characteristics outputs from physical process and other measures of interest to managers in both the public and private sectors.

Characteristics of the Normal Distribution:

• The curve has a bell-shaped appearance. It has a single peak; thus, it is unimodal.
• The curve is symmetric at x = median.
• The mean, median and the mode are of the same value.
• The curve is asymptotic to the x-axis, i.e., the curve never touches the x-axis.
• The total area under the curve above the x-axis is equal to 1 or 100%.
• These measurements satisfy the empirical rule:

1. Approximately 68% of the observations will be within one standard deviation of the mean.
2. Approximately 95% of the measurements will be within two standard deviation of the mean.
3. Approximately 99.7% of the measurements will be within three standard deviation of the mean.

By: Lera Gay Bacay