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Normality of the distribution

In the examples in this article, data is generated every time the page loads. If you want to see an example with different values - reload the page.

Some statistical tools assume that the distribution is normal. The algorithm for checking the normality of the distribution will be given below, and also an example in excel.

Distribution law

Checking for compliance with the normal distribution is a special case of solving the problem on finding among the known distribution functions one that describes as accurately as possible this distribution.

First of all, it is necessary to structure the available values, in the article properties distributions it describes how the distribution series is constructed, so here I will omit the details and give source data and processed values:

142 160 170 160 149 150 158 157 142 148
159 160 159 156 147 144 142 157 151 143
165 147 142 154 165 134 159 157 137 142
138 150 148 149 165 143 151 164 148 153
153 162 157 135 160 137 157 145 150 138
141 138 147 156 152 155 147 155 157 159
147 155 141 150 143 170 130 134 147 146
158 154 156 161 148 140 168 133 159 162
157 149 146 159 149 138 144 163 140 144
159 166 142 150 145 143 156 163 165 169
Table 1. Initial data for checking the normality of the distribution
# 12345678910
x258151610161493
pi0.020.050.080.150.160.10.160.140.090.03
Table 2. Number of elements in each interval
Graph 1. Distribution range

Regardless of what we see on the graph, we need to check whether whether the distribution is normal.

The characteristics of a normal distribution are the mean and standard deviation. Let's calculate these values for our distribution:

μ = 151.15
σ = 9.33
The calculation of the mean and standard deviation is described in the article distribution parameters

Normal distribution

The normal distribution curve for μ=151.15 and σ=
Warning: Undefined variable $variation in /var/www/content/ktree/t9n/en/articles/statistics_check_is_normal.php on line 148
:

P(x) = e^[-0.5((x-151.15)/9.33)2] / [9.33√2π] Normal distribution formula
Graph 2. Distribution series and normal distribution, μ = 151.15, σ = 9.33

First approximation

Let's try to invent a criterion of normality, the simplest, what comes to mind is to determine the percentage of compliance the normal curve and the existing distribution.

To do this, add up the absolute values of the differences across all points of the graph, find the area under the normal distribution graph and calculate the deviation of interest, I will call such a criterion "criterion of normality" and I will decide that if the deviation more, let's say 30%, then the distribution is not normal.

diff = Σ|D(X) - P(X)|
S = ΣP(X)
Δ = diff / S
diff = 42.34
S = 57.66
Δ = 73%

The deviation is 73%, therefore, I draw the following conclusion: the distribution is not normal according to the normality criterion.

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