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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:

160 148 132 148 171 157 158 140 148 147
146 154 156 154 146 163 152 168 143 155
149 155 149 158 150 148 147 157 166 133
158 145 137 138 154 144 142 169 137 146
171 148 160 148 151 163 147 158 145 157
152 144 139 144 157 161 169 142 147 155
159 138 136 141 168 159 156 150 156 140
155 164 138 143 139 154 163 142 155 145
155 143 145 158 168 134 159 143 157 150
147 146 147 147 138 164 157 151 159 171
Table 1. Initial data for checking the normality of the distribution
# 12345678910
x391018131218635
pi0.030.090.10.180.130.120.180.060.030.05
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 = 151.26
σ = 9.41
The calculation of the mean and standard deviation is described in the article distribution parameters

Normal distribution

The normal distribution curve for μ=151.26 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-151.26)/9.41)2] / [9.41√2π] Normal distribution formula
Graph 2. Distribution series and normal distribution, μ = 151.26, σ = 9.41

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 = 31.65
S = 72.68
Δ = 44%

The deviation is 44%, therefore, I draw the following conclusion: the distribution is not normal according to the normality criterion.

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