02.04 Normal distribution curve

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Overview

1. Normal Distribution Curve-Also alled a Gaussian Distribution (as it was discovered by Carl Gauss)
1. Bell curve around the mean.
2. Examples
1. Height- estimate mean height is 67.95, and the estimate standard deviation for height is 1.94.
2. Blood pressure
3. IQ
4. Measurement Error
5. Male Foot lengths
3. Common Properties of Normal Distribution
1. Symmetrical around the mean
2. Unimodal- One peak
3. Asymptotic- approaching a value or curve abititrarily close.
4. Men, median and mode are all equal
5. Total area under the curve equals 1

Video Transcript

Today we’re going to be talking about normal distribution.

Normal distribution is also known as Guassian distribution named after its discoverer Carl Gauss. Data that is said to be of normal distribution will form a bell curve around the meanwhen the data is plotted on a graph.

So some examples of some data sets that have form a normal distribution curve is human height. The mean is 67.95 and the ST DEV is 1.94. Human blood pressure in the US has a Systolic mean of 120 and diastolic of 75.The length of a male foot in the US is 26.3 cm. So each of these data set variables form this bell shaped curve.

We can consider some common Properties of a Normal Distribution Curve. Number one, the data is Symmetrical around the average/mean. That means to the left of the mean and to the right of the mean is a mirror image. Secondly the graph is Unimodal meaning it forms just one major peak. Third, the data set is asymptotic- meaning it is approaching a value or line arbitrarily close. number 4, the mean, median and mode for the data set are all equal. and the 5th common property is that the Total area under the curve equals 1.

In summary, a normal distribution curve is also called a Gaussian distribution. Normally distributed data form a symmetrical bell curve. It consists of only one major peak, its mean, median and mode are equal and the total value of everything under the curve equals 1.

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