Stata descriptive statistics how to#
Stata descriptive statistics code#

You would need to read the PDF documentation that came with your Stata installation, specifically the poststratification chapter of the manual for specific guidance how to do this. (So, if you sampled 1 out of every 100 immigrants and 1 out of every 500 natives, each immigrant's observation would receive a pweight of 100 and each native's observation would get a pweight of 500.) Or, if you don't have that kind of information about the sampling scheme but you know what the distribution of natives and immigrants in the population should be, you can use that to create post-stratification weights and apply those using the -svy- commands. In that case, you would weight each observation by the reciprocal of its probability of having been included in the sample. This could come in the form of sampling probabilities that arise from the design of the sampling. To do the weighting, you need information about the discrepancy between sampling and population for the relevant subgroups at each time. And, if you know that your sample under-represents some population segments and over-represents others, then, yes, you would definitely want to weight the analysis to adjust for the imbalances in the sampling. If, however, you are trying to draw conclusions about the population, not just describing your sample, then, you are not doing descriptive statistics, you are doing inferential statistics. If you are actually looking to do descriptive statistics, then you would not consider weighting anything. 'Descriptive statistics' means you are describing your study sample. Label values ixpxh IXPXHJDWould appreciate some hints, thanks!įirst let's clear up some terminology. Input int tef1 float year byte is051 double ixpxh I was only able to make something like this: 35057413ĩ661 8159 11529I thought of generating a new variable where is051 is weighted likeĩ661 8159 11529 29349However, I would like to use the weighting variable in the dataset, which is named as ixpxh. Means, Standard Deviations and Frequencies of Heimatġ.F�hrung.

Stata descriptive statistics code#

Label values ixpxhj IXPXHJDWithout weighting, I used the following code to show the table: Label def TEF1D 9 '9.Hilfsarbeitskr�fte', modify Label def TEF1D 8 '8.Anlagen und Maschinenbediener, Montierer', modify Label def TEF1D 7 '7.Handwerks- und verwandte Berufe', modify

Label def TEF1D 6 '6.Fachkr�fte in Land- und Forstwirtschaft', modify Label def TEF1D 5 '5.Dienstleistungsberufe und Verk�ufer', modify

Label def TEF1D 4 '4.B�rokr�fte und verwandte Berufe', modify Label def TEF1D 3 '3.Techniker und gleichrangige Berufe', modify Label def TEF1D 2 '2.Akademische Berufe', modify Label def TEF1D 1 '1.F�hrungskr�fte', modify Input int tef1 float year byte is051 float ixpxhj Or, in easier descriptive terms, a third of all students choose commerce in class eleventh.Code: * Example generated by -dataex. For e.g., 33.33% of all students choose commerce in class eleventh. By combining descriptive statistics and graphical statistics, understand and interpreting a set of data becomes fairly easy for the reader. They provide insights from a set of raw information. Descriptive statistics are used to describe the overall summary of a set of data.