#Stata descriptive statistics how to#

While there is a number of other possibilities to create an overview of means and S.D.s, an nice feater of tabulate is that it can display these statistics conditional on two variables combined. As to the standard deviation see my remark above. Will display the mean and the standard deviation of income, plus the number of observations, for each social class. Let's assume that variable 'class' indicates the social class of the persons in your sample and 'income' their income.

For the time being, please refer to the User's Guide.ДЄ related, but somewhat different possibility is to display summary statistics for a variable contingent on the values of another variable. It offers more flexibility in the choice of statistics displayed.

#Stata descriptive statistics how to#

The help file will show you how to get the different measures.Д¬ommand tabstat is yet another way to compute a number of sample statistics. Dirk Enzmann has written an ado file moments2 that allows you to pick the measure of your choice. The option 'detail' (abbreviated as 'd') will cause Stata to deliver, in addition to the mean and the S.D., several further statistics: Various percentiles, the four smallest and the four largest values, the variance and finally skewness and kurtosisДЄctually, quite a number of measures have been proposed in the literature for skewness and kurtosis, and particularly concerning kurtosis the implementation in Stata's summarize is somewhat unfortunate. Several variables can be listed, as in the following expanded example: (In other words, when computing the variance, the denominator is not n, the number of cases in your dataset, but n-1.).

The standard deviation is calculated on the assumption that your data are a sample from a population and therefore is an estimation for that population and not simply the standard deviation of the data at hand. Will display the number of observations for this variable, the arithmetic mean (commonly abbreviated as mean), the standard deviation and the minimum and maximum values.

Multiple Imputation: Analysis and Pooling Steps.

Confidence Intervals with ci and centile.

Changing the Look of Lines, Symbols etc.