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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:

147 156 158 135 142 141 155 153 146 153
143 147 152 156 154 154 153 148 151 146
148 127 159 163 155 148 166 138 148 139
146 152 142 137 151 140 153 152 166 170
141 154 144 155 133 141 137 144 147 151
155 148 156 164 142 153 154 157 139 153
158 149 160 165 140 146 138 148 146 146
164 147 153 155 150 143 135 156 152 152
147 148 154 149 129 161 151 143 144 153
153 157 135 147 169 150 140 145 148 159
Table 1. Initial data for checking the normality of the distribution
# 12345678910
x24615211325643
pi0.020.040.060.150.210.130.250.060.040.03
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 = 149.43
σ = 8.42
The calculation of the mean and standard deviation is described in the article distribution parameters

Normal distribution

The normal distribution curve for μ=149.43 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-149.43)/8.42)2] / [8.42√2π] Normal distribution formula
Graph 2. Distribution series and normal distribution, μ = 149.43, σ = 8.42

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 = 37.15
S = 64.16
Δ = 58%

The deviation is 58%, therefore, I draw the following conclusion: the distribution is not normal according to the normality criterion.

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