Анализ данных в Statgraphics.

1)Выборка:

18,9141
20,7026
18,9174
19,9372
18,9678
21,1771
18,4972
19,208
15,9393
20,3087
17,6722
16,388
20,2339
18,9226
19,7789
17,4023
20,1476
18,3071
16,7852
18,835
21,6077
19,0824
19,7563
17,7349
19,3174
21,5386
18,7929
20,4599
18,8361
17,3142
17,8107
19,5773
17,6973
20,7187
19,5645
19,1582
18,9302
19,2241
20,3843
19,0893
18,8797
18,9749
19,4469
17,7077
17,1609
19,489
17,9211
19,0949
19,0387
20,2081

2) Числовые характеристики.

Summary Statistics for Col_1

Count	50
Average	19,0312
Median	19,0605
Mode
Variance	1,57741
Standard deviation	1,25595
Coeff. of variation	6,59942%
Minimum	15,9393
Maximum	21,6077
Range	5,6684
Skewness	-0,234833
Stnd. skewness	-0,677903
Kurtosis	0,0349062
Stnd. kurtosis	0,0503828

3) Доверительный интервал:

Confidence Intervals for Col_1

95,0% confidence interval for mean: 19,0312 +/- 0,356937 [18,6742; 19,3881]

95,0% confidence interval for standard deviation: [1,04914; 1,56508]

4)Гистограмма:

5)График «ящик с усами»:

6)Плотность распределения:

7)Проверка независимости наблюдений (случайности выборки):

Tests for Randomness of Col_1

(1) Runs above and below median

Median = 19,0605

Number of runs above and below median = 36

Expected number of runs = 26,0

Large sample test statistic z = 2,71485

P-value = 0,00663064

(2) Runs up and down

Number of runs up and down = 37

Expected number of runs = 33,0

Large sample test statistic z = 1,19581

P-value = 0,23177

(3) Box-Pierce Test

Test based on first 16 autocorrelations

Large sample test statistic = 11,7136

P-value = 0,76345

8)Проверка гипотезы о виде закона распределения исследуемой случайной величины:

Data variable: Col_1

50 values ranging from 15,9393 to 21,6077

Fitted Distributions

Erlang	Lognormal	Normal
shape = 231,0	mean = 19,0324	mean = 19,0312
scale = 12,138	standard deviation = 1,2735	standard deviation = 1,25595
	Log scale: mean = 2,94391
	Log scale: std. dev. = 0,0668373