The document discusses normality tests for interval or ratio scale data, analyzing normal and non-normal data distributions using various statistical techniques. It includes details about descriptive and inferential analysis, skewness, kurtosis, and graphical representations like histograms and Q-Q plots. Specific statistics for weight data (bb) are provided, showing its mean, standard deviation, and results of normality tests such as Kolmogorov-Smirnov and Shapiro-Wilk.

2. Uji Normalitas
 Pada data berskala interval atau rasio
 Menentukan jenis analisis data
ANALISIS
Distribusi data
Normal Tdk Normal
Deskriptif
Central
Tendency
Mean Median
Dispersi
Average Dev.,
Standard Dev.
Interquartile
Deviation
Inferensial Uji Hipotesis Parametrik Non Parametrik

3. Teknik Analisis
 Diagram
 Pengujian Skewness dan
Kurtosis
 Simultan

4. Diagram (histogram)
70.0
60.0
50.0
40.0
30.0
berat badan penderita
10
8
6
4
2
0
Frequency
Mean = 50.772
Std. Dev. = 8.2614
N = 50
Histogram

5. Diagram (P-P Plot)
1.0
0.8
0.6
0.4
0.2
0.0
Observed Cum Prob
1.0
0.8
0.6
0.4
0.2
0.0
Expected
Cum
Prob
Normal P-P Plot of berat badan penderita

6. Diagram (Q-Q Plot)
70
60
50
40
30
Observed Value
70
60
50
40
30
Expected
Normal
Value
Normal Q-Q Plot of berat badan penderita

7. Skewness dan Kurtosis
Statistics
berat badan penderita
50
0
.152
.337
-.414
.662
Valid
Missing
N
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
t skewness = 0.152/0.337 = 0.451
t kurtosis = -0.414/0.662 = -0.625

8. Kolmogorov-Smirnov 1 sampel
One-Sample Kolmogorov-SmirnovTest
50
50.772
8.2614
.118
.118
-.099
.832
.494
N
Mean
Std. Deviation
Normal Parametersa,b
Absolute
Positive
Negative
Most Extreme
Differences
Kolmogorov-Smirnov Z
Asymp. Sig. (2-tailed)
berat badan
penderita
Test distribution is Normal.
a.
Calculated from data.
b.

9. Kolmogorov-Smirnov (Lilliefors)
Shapiro-Wilk
Tests of Normality
.118 50 .081 .962 50 .106
berat badan penderita
Statistic df Sig. Statistic df Sig.
Kolmogorov-Smirnov
a
Shapiro-Wilk
Lilliefors Significance Correction
a.

10. Amos
Variable min max skew c.r. kurtosis c.r.
BB 35.000 70.000 .147 .424 -.491 -.709
Multivariate -.374 -.539

11. Lisrel

 Variable Mean St. Dev. T-Value Skewness Kurtosis Minimum Freq. Maximum Freq.
 -------- ---- -------- ------- -------- -------- ------- ----- ------- -----
 BB 50.772 8.261 43.456 0.152 -0.414 35.000 2 70.000 2

12. Lisrel
Total Sample Size = 100
Univariate Summary Statistics for Continuous Variables
Variable Mean St. Dev. T-Value Skewness Kurtosis Minimum Freq. Maximum Freq.
-------- ---- -------- ------- -------- -------- ------- ----- ------- -----
BB 50.772 8.220 61.769 0.149 -0.454 35.000 4 70.000 4
Test of Univariate Normality for Continuous Variables
Skewness Kurtosis Skewness and Kurtosis
Variable Z-Score P-Value Z-Score P-Value Chi-Square P-Value
BB 0.636 0.525 -1.053 0.292 1.513 0.469