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Test for Normal Distribution

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Presentation on theme: "Test for Normal Distribution"— Presentation transcript:

1 Test for Normal Distribution

2 Test of Normality - 1 Graphical Test
Histogram Check shape: skewness, outliers Normal Probability Plot Check shape: straight, convex, S-shaped

3 Construction of a Normal Probability Plot
Alternative estimates of the cumulative relative frequency of an observation pi = (i - 0.5)/ n pi = i / (n+1) pi = (i ) / (n+0.25) Estimate of the percentile | Normal Standardized Q(pi) = NORMSINV(pi) Q(pi) = NORMINV(pi, mean, stand. dev.)

4 Non-Normal Populations
Flat Skewed Expected | Normal Data Expected | Normal Data

5 Test of Normality - 2 Test Statistics
Stand. Dev. Skewness Kurtosis

6 The Jarque-Bera Test If the population is normal and the data are random, then: follows approximately c2 with the # 0f degrees of freedom 2. Reject H0 if JB > 6


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