k-tree
E-learning book

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:

134 136 149 139 157 137 155 150 139 142
145 151 133 139 147 152 160 139 142 143
152 140 156 140 144 152 149 155 137 144
146 139 165 135 151 164 127 155 161 145
158 149 152 161 150 147 146 148 153 148
157 146 162 157 148 155 162 143 164 161
164 149 155 132 170 147 142 148 153 165
146 144 147 149 150 148 149 140 164 160
148 145 162 148 138 148 151 126 165 148
167 164 149 154 152 153 142 162 140 141
Table 1. Initial data for checking the normality of the distribution
# 12345678910
x2310111427109121
pi0.020.030.10.110.140.270.10.090.120.01
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 = 149.38
σ = 9.23
The calculation of the mean and standard deviation is described in the article distribution parameters

Normal distribution

The normal distribution curve for μ=149.38 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-149.38)/9.23)2] / [9.23√2π] Normal distribution formula
Graph 2. Distribution series and normal distribution, μ = 149.38, σ = 9.23

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 = 48.34
S = 141.34
Δ = 34%

The deviation is 34%, therefore, I draw the following conclusion: the distribution is not normal according to the normality criterion.

Download article in PDF format.

Do you find this article curious? /

Seen: 4 813


Read the following
Analysis of variance