3. (Normality Test, p, If it is possible to obtain a large number of observations for a variable X, a histogram would be helpful to determine whether or not X has approximately a normal distribution....

Extracted text: 3. (Normality Test, p, If it is possible to obtain a large number of observations for a variable X, a histogram would be helpful to determine whether or not X has approximately a normal distribution. However, if the sample is small (size < 30),="" a="" quantile-quantile="" plot="" is="" suggested.="" (1)="" po,="" for="" the="" following="" sample,="" calculate="" the="" z="" quantiles="" z,,="" z,,,="" z,="" (n="12)," which="" divide="" the="" area="" under="" z-curve="" to="" 13="" equal="" parts.="" 0.06="" 0.11="" 0.12="" 0.12="" 0.13="" 0.17="" 0.19="" 0.20="" 0.23="" 0.25="" 0.29="" 0.31="" 1="" 3="" 4="" 5="" 8="" 10="" 11="" 12="" 0.0769="" 0.1538="" 0.2308="" 0.3077="" 0.3846="" 0.4615="" 0.5385="" 0.6154="" 13="" 0.7692="" 0.8462="" 0.9231="" 0.6923="" (2)="" sample="" was="" taken="" from="" a="" normal="" population.="" draw="" a="" q-q="" plot="" (plot="" (x1,="" z,),="" (x2,="" z,),="" .,="" (x12,="" z12="" ))="" to="" determine="" whether="" or="" not="">