{"id":13822,"date":"2018-04-29T05:20:50","date_gmt":"2018-04-29T05:20:50","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=13822"},"modified":"2021-12-05T22:33:35","modified_gmt":"2021-12-05T17:03:35","slug":"stat-distribution-analysis","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/stat-distribution-analysis\/","title":{"rendered":"SAS\/STAT Distribution Analysis – KDE Procedure"},"content":{"rendered":"

In our last SAS\/STAT tutorial, we studied\u00a0STAT Group Sequential Design and Analysis<\/strong>. Today, we will be looking at another type of analysis called SAS\/STAT distribution analysis. Moreover, we will also discuss how distribution analysis is used in SAS\/STAT<\/strong> for kernel density estimation.<\/p>\n

Our focus here will be to understand the KDE procedure that can be used for SAS\/STAT Distribution analysis through the use of an example.<\/p>\n

So, let’s start with SAS\/STAT Distribution Analysis.<\/p>\n

SAS\/STAT Distribution Analysis<\/h3>\n

The\u00a0distribution\u00a0of a statistical data set is a listing or function showing all the possible values of the data and how often they occur. When a distribution of categorical data is organized, you see the number or percentage of individuals in each group.<\/p>\n

When a distribution of numerical data is organized, they\u2019re often ordered from smallest to largest, broken into reasonably sized groups, and then put into graphs and charts to examine the shape, centre, and amount of variability in the data.<\/p>\n

SAS\/STAT Distribution analysis provides information about the distribution of\u00a0numeric variables. A variety of\u00a0plots\u00a0such as histograms,\u00a0probability plots, and\u00a0quantile-quantile plots\u00a0can be used in this analysis.<\/p>\n

\"SAS\/STAT<\/a>

Example of Distribution Analysis in SAS\/STAT<\/p><\/div>\n

Procedures for Distribution Analysis in SAS\/STAT<\/h3>\n

Following procedure is used to compute SAS\/STAT distribution analysis of a sample data. Let’s explore each of it.<\/p>\n

a. PROC KDE<\/h4>\n

The PROC KDE procedure in SAS\/STAT performs univariate and multivariate estimation. The kernel density estimation technique is a technique used for density estimation in which a known density function, known as a kernel, is averaged across the data to create an approximation. It is very similar to the way we plot a histogram.<\/p>\n

PROC KDE Syntax-<\/strong><\/p>\n

PROC KDE\u00a0DATASET;\r\nUnivar <variables>;\r\nBivar <variables>;\r\ndata bivar;\r\n\u00a0\u00a0 seed = 1234567;\r\n\u00a0\u00a0 do i = 1 to 1000;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 z1 = rannor(seed);\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 z2 = rannor(seed);\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 z3 = rannor(seed);\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 x = 3*z1+z2;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 y = 3*z1+z3;\r\n\u00a0\u00a0\u00a0\u00a0\u00a0 output;\r\n\u00a0\u00a0 end;\r\n\u00a0\u00a0 drop seed;\r\nrun;\r\n\/**kernel density plot**\/\r\nods graphics on;\r\nproc kde data=bivar;\r\n\u00a0\u00a0 univar x ;\r\nrun;\u00a0\r\n\/**bivariate plot**\/\r\nods graphics on;\r\nproc kde data=bivar;\r\n\u00a0\u00a0 bivar x y \/ plots=all;\r\nrun;\r\nods graphics off;<\/pre>\n
The UNIVAR statement computes one or more univariate kernel density estimates\u00a0and similarly, the BIVAR statement computes bivariate kernel density estimate.
\nThe PLOTS= option prints different plots between the two variables. We can specify the type of plot we want inside the brackets, we have displayed all plots here.\u00a0<\/strong>\u00a0<\/strong><\/p>\n
\"SAS\/STAT<\/a>
Distribution Analysis in SAS\/STAT – PROC KDE<\/p><\/div>\n
\"SAS\/STAT<\/a>
Distribution Analysis in SAS\/STAT – PROC KDE<\/p><\/div>\n
 <\/p>\n
\"SAS\/STAT<\/a>
SAS\/STAT Distribution Analysis<\/p><\/div>\n
\"SAS\/STAT<\/a>
Distribution Analysis in STAT – PROC KDE<\/p><\/div>\n
\"SAS\/STAT<\/a>
Distribution Analysis in SAS – PROC KDE<\/p><\/div>\n
 <\/p>\n
\"SAS\/STAT<\/a>
Distribution Analysis in SAS – PROC KDE<\/p><\/div>\n
\"SAS\/STAT<\/a>
SAS\/STAT Distribution Analysis – PROC KDE<\/p><\/div>\n
\"SAS\/STAT<\/a>
SAS\/STAT Distribution Analysis\u00a0– PROC KDE<\/p><\/div>\n
\"SAS\/STAT<\/a>
SAS\/STAT Distribution Analysis\u00a0– PROC KDE<\/p><\/div>\n
Hence, this was all about\u00a0SAS\/STAT Distribution Analysis. Hope you like our explanation.<\/p>\n
Conclusion<\/h3>\n
So finally, this was a complete description and a comprehensive understanding of the KDE procedure offered by SAS\/STAT distribution analysis. Stay tuned for more interesting topics in SAS\/ STAT. Furthermore, for any queries, post your doubts in the comments section below.<\/p>\n","protected":false},"excerpt":{"rendered":"
In our last SAS\/STAT tutorial, we studied\u00a0STAT Group Sequential Design and Analysis. Today, we will be looking at another type of analysis called SAS\/STAT distribution analysis. Moreover, we will also discuss how distribution analysis...<\/p>\n","protected":false},"author":6,"featured_media":13828,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[56],"tags":[7993,8004,8005,10042,10043,10044,12338,13756],"class_list":["post-13822","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sas-stat","tag-kde-procedure","tag-kernel-density","tag-kernel-density-procedure","tag-proc-kde","tag-proc-kde-example","tag-proc-kde-syntax","tag-sasstat-distribution-analysis","tag-stat-distribution-analysis"],"yoast_head":"\nSAS\/STAT Distribution Analysis - KDE Procedure - DataFlair<\/title>\n<meta name=\"description\" content=\"SAS\/STAT Distribution Analysis Tutorial-What is Distribution Analysis in SAS, Procedure for Distribution analysis in STAT, PROC KDE,Kernel Density Procedure\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/stat-distribution-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"SAS\/STAT Distribution Analysis - 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