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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:

143 134 151 166 147 137 154 156 147 144
141 145 134 148 163 153 143 159 155 134
160 167 132 160 150 165 145 134 146 155
160 140 147 148 148 143 145 161 171 159
144 170 147 147 157 138 167 161 143 148
138 138 163 139 149 143 130 154 137 138
142 139 149 154 145 140 136 170 160 161
165 155 163 142 157 132 148 142 157 158
156 130 139 154 143 139 153 137 149 138
136 150 148 130 162 153 159 148 167 146
Table 1. Initial data for checking the normality of the distribution
# 12345678910
x910101417891165
pi0.090.10.10.140.170.080.090.110.060.05
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 = 148.93
σ = 10.41
The calculation of the mean and standard deviation is described in the article distribution parameters

Normal distribution

The normal distribution curve for μ=148.93 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-148.93)/10.41)2] / [10.41√2π] Normal distribution formula
Graph 2. Distribution series and normal distribution, μ = 148.93, σ = 10.41

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 = 48.04
S = 51.96
Δ = 92%

The deviation is 92%, therefore, I draw the following conclusion: the distribution is not normal according to the normality criterion.

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