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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:

149 141 149 159 150 164 151 128 137 144
147 144 142 143 146 127 151 132 135 145
148 131 146 147 139 146 158 174 154 139
138 146 144 154 141 163 161 150 127 151
157 146 149 164 162 154 152 161 161 164
143 143 152 144 145 166 150 139 153 166
145 160 146 142 159 157 157 134 145 158
140 139 146 148 147 145 150 141 165 140
162 146 132 147 150 138 135 148 164 149
156 147 142 178 165 158 161 134 153 163
Table 1. Initial data for checking the normality of the distribution
# 12345678910
x651425179121001
pi0.060.050.140.250.170.090.120.100.01
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 = 149.04
σ = 10.26
The calculation of the mean and standard deviation is described in the article distribution parameters

Normal distribution

The normal distribution curve for μ=149.04 and σ=
Warning: Undefined variable $variation in /home/c/cg79187/public_html/content/ktree/t9n/en/articles/statistics_check_is_normal.php on line 148
:

P(x) = e^[-0.5((x-149.04)/10.26)2] / [10.26√2π] Normal distribution formula
Graph 2. Distribution series and normal distribution, μ = 149.04, σ = 10.26

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 = 49.42
S = 53.05
Δ = 93%

The deviation is 93%, therefore, I draw the following conclusion: the distribution is not normal according to the normality criterion.

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