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SAS PROC R

PROC REG: PROC REG Statement :: SAS/STAT(R) 9

names the SAS data set to be used by PROC REG. The data set can be an ordinary SAS data set or a TYPE=CORR, TYPE=COV, or TYPE=SSCP data set. If one of these special TYPE= data sets is used, the OUTPUT, PAINT, PLOT, and REWEIGHT statements, ODS Graphics, and some options in the MODEL and PRINT statements are not available 3) Open your SAS foundation and Run in SAS editor: proc options option =rlang; run; .In your SAS log must appear a message like this: SAS (r) Proprietary Software Release 9.4 TS1M2. RLANG Enables SAS to execute R language statements. NOTE: PROCEDURE OPTIONS used (Total process time): real time 0.01 seconds. cpu time 0.01 seconds.Congratulations.

Solved: How to: Run R code inside SAS easily - SAS Support

  1. Generally, aggregate in base R can serve as counterpart to SAS's proc means. Typically, this method runs a single simple function (that takes one input) on a single numeric column. Below is the formula version of the method: aggregate (V1 ~ Temp, df, FUN=mean
  2. Example 56.4 Known G and R. This animal breeding example from Henderson (1984, p. 48) considers multiple traits. An unstructured matrix is specified by using the TYPE=UN option, and it is read into PROC MIXED from a SAS data set by using the GDATA=G specification. The G and GI options request the display of and , respectively
  3. SAS to R guide data step Save data to disk Concatenate datasets Filter data or 'where' statement proc freq Sort by frequency With missing Percentages, missing & sorted by frequency proc means More percentiles proc sort Find duplicated rows Find duplicated values proc print proc contents Save output proc format Transform values according to a.
  4. Summarising data in base R is just a headache. This is one of the areas where SAS works quite well. For R, I recommend the plyr package.. In SAS: /* tabulate by a and b, with summary stats for x and y in each cell */ proc summary data=dat nway; class a b; var x y; output out=smry mean(x)=xmean mean(y)=ymean var(y)=yvar; run
  5. ** Instruction: This SAS macro enables native R language to be embedded in and executed along with a SAS program ** ** in the Base SAS environment under Windows OS. This macro executes a user-defined R code in batch *
  6. SAS IML The SAS IML Procedure can submit R statements from within SAS. It is not a version of R packaged with SAS, it uses the R system installed on the local operating system. The R_HOME environment variable must be set accordingly so SAS can find it. The -RLANG option must be included in the SAS invocation, and can't be turned on later as.

Similar to PROC SQL, the programming interface that enables writing SQL scripts within SAS codes, PROC R is developed as an interface between R and SAS. It Enables Native R Programming in the Base SAS Environment. Using Proc_R, the SAS users can access the extensive statistical and visualization capabilities of R SAS gives the likelihood-based pseudo R-square measure and its rescaled measure. Categorical Data Analysis Using The SAS System, by M. Stokes, C. Davis and G. Koch offers more details on how the generalized R-square measures that you can request are constructed and how to interpret them SAS(R) Procedures by Name and Product Tell us....How satisfied are you with SAS documentation? Thank you for your feedback. Please choose a rating. How satisfied are you with SAS documentation overall? Very Dissatisfied. Dissatisfied. Neither dissatisfied or satisfied (OR neutral Jiho.han, > I wonder if there's a way to replicate SAS rank procedure where it ranks a > variable by a certain number of groups. For example, it's very easy to > calculate quintile rank in SAS, but I couldn't find the similar function in > R. > > Does anyone know how to do this? There are some functions you can try: rank(), order() or sor By default, proc corr uses pairwise deletion for missing observations, meaning that a pair of observations (one from each variable in the pair being correlated) is included if both values are non-missing

There are a number of different model fit statistics available. It also depends on exactly which procedure as several do logistic regression and the nature of your data: Rsquare -2 Log Likelihood, AIC SC Homer-Lemeshow test are some available in Proc Logistic for tests/metrics. Look at the MODEL options SAS can pass data to an R session, and ask R for an analysis. All communication with R is done via SAS's PROC IML. Note here that capitization matters in R, and that character variables are automatically converted to factors. In this example, then, it is important that the variable names be capitalized In the code below, the data = option on the proc reg statement tells SAS where to find the SAS data set to be used in the analysis. On the model statement, we specify the regression model that we want to run, with the dependent variable (in this case, science ) on the left of the equals sign, and the independent variables on the right-hand side %PROC_R: A SAS Macro that Enables Native R Programming in the Base SAS Environment: Abstract: In this paper, we describe %PROC_R, a SAS macro that enables native R language to be embedded in and executed along with a SAS program in the base SAS environment under Windows OS. This macro executes a user-defined R code in batch mode by calling the. The bivariate Pearson Correlation produces a sample correlation coefficient, r, which measures the strength and direction of linear relationships between pairs of continuous variables

SAS proc means equivalent in R - Stack Overflo

  1. d that the code I show here isn't the only (and probably.
  2. Correlation analysis in SAS is a method of statistical evaluation used to study the strength of a relationship between two, numerically measured, continuous variables (e.g. height and weight). SAS Correlation analysis is a particular type of analysis, useful when a researcher wants to establish if there are possible connections between variables
  3. Proc REG Statement PROC REG options; These options may be specified on the PROC REG statement: DATA=SASdataset names the SAS data set to be used by PROC REG. If DATA= is not specified, REG uses the most recently created SAS data set. OUTEST=SASdataset requests that parameter estimates be output to this data set. OUTSSCP=SASdatase
  4. When you conduct a multiple regression using forward, backward or stepwise, the output provides a partial R2 (along with a model R2), I'm interested in generating that from the PROC REG or PROC GLM statement with only the variables of interest
  5. PROC PHREG does not report an R2 statistic. However, Allison (1995, pp. 247-249) discusses a generalized R2 statistic that is based on the likelihood-ratio statistic (LRT) for testing the global null hypothesis. The LRT statistic is giv

PROC MIXED: Known G and R :: SAS/STAT(R) 9

R bubble map, created using geom_polygon() and geom_point() SAS bubble map, created using Proc SGmap. My Approach. I will be showing the R code (in blue) first, and then the equivalent SAS code (in red) that I used to create both of the maps. Note that there are many different ways to accomplish the same things in both R and SAS - and the code I show here isn't the only (and probably not even. Using SAS proc mixed and R gls() to implement the linear population-averaged model with care taken to take proper account of missing observations. SAS program and output; R program; and data set in long format. Chapter 6, EXAMPLE 1, Dental Study. Using SAS proc mixed and R lme() and lmer() to implement the linear mixed effects model Starting in SAS ® 9.3, the R interface enables SAS users on Windows and Linux who license SAS/IML ® software to call R functions and transfer data between SAS and R from within SAS. Potential users include SAS/IML users and other SAS users who can use PROC IML just as a wrapper to transfer data between SAS and R and call R functions R Graph, created using ggplot() SAS Graph, created using Proc SGplot. My Approach. I will be showing the R code (in blue) first, and then the equivalent SAS code (in red) I used to create both of the graphs. Note that there are many different ways to accomplish the same things in both R and SAS - and keep in mind that the code I show here isn't the only (and probably not even the 'best') way. For SAS users, the macro is a huge productivity booster, allowing one to easily complete data management and/or partial data analysis in SAS, skip out quickly to R for analyses that are awkward or impossible in SAS, then return to SAS for completion

Tags: code, howto, R, r-project, SAS, Statistics, Uncategorized Welcome! SAS-X.com offers news and tutorials about the various SAS® software packages, contributed by bloggers Also notice how SAS plotting procedures are way better than a decade or so ago (eg proc sgplot vs proc plot). coincidence that R did good plotting first? I think not! This effectively reduces the efficiency from switching because plotting is not so different anymore - R is still better, but not by enough to switch..

Base SAS Training - Day 2 (PROC Contents, Data Steps and

I am putting together a dataset in SAS and then grouping the data by person and date and trying to push to an access database. The problem I'm running in to is while the dates appear correctly in SAS (I'm using a mmddyy10. format), when they get to the access database they're displaying as 1/1/1960 6:11:13AM lamack lamack wrote: > Dear all, Is there an R equivalent to SAS's proc format? > > Best regards > > J. Lamack Fortunately not. SAS is one of the few large systems that does not implicitly support value labels and that separates label information from the database [I can't count the number of times someone has sent me a SAS dataset and forgotten to send the PROC FORMAT value labels] SAS Syntax (*.sas) Syntax to read the CSV-format sample data and set variable labels and formats/value labels. Pearson Correlation The bivariate Pearson Correlation produces a sample correlation coefficient, r , which measures the strength and direction of linear relationships between pairs of continuous variables

GitHub - asnr/sas-to-r: Translate SAS to

I use SAS and R on a daily basis. Each has strengths and weaknesses, and using both of them gives the advantage of being able to do almost anything when it comes to data manipulation, analysis, and graphics. If you use both SAS and R on a regular basis, get this book The biggest mistake that companies can make in a SAS to R migration is to try to perform a 'like-for-like' migration; migrating SAS code PROC by PROC into R functions. We often see this when SAS to R migrations are conducted by those without extensive knowledge of both languages. Whilst the like-for-like approach facilitates a 'successful.

Is there an R equivalent of SAS PROC FREQ? - Cross Validate

Programming-SAS/Proc_R

In version 9, SAS introduced two new procedures on power and sample size analysis, proc power and proc glmpower.Proc power covers a variety of statistical analyses: tests on means, one-way ANOVA, proportions, correlations and partial correlations, multiple regression and rank test for comparing survival curves.Proc glmpower covers tests related to experimental design models 3.5 Advantages and Disadvantages of SAS and R 52 . Page | 2 . This paper will go over power and how power is calculated using SAS or R. Chapter 1 will give an introduction to power, what it is, and what is needed for the calculation of power. Chapter 2 goes in depth of the power calculations for a general ANOVA test an Web site created using create-react-ap SAS procedure PROC GROOVY enables SAS code to run Groovy code on the Java Virtual Machine (JVM). In our solution, PROC GROOVY is used to invoke Java code that calls the DeployR java client library. Figure 2. SAS Program and R Program Integration Flow Chart: DEPLOYR FOR WEB ANALYTIC proc print data=table noobs; var p prob0 prob1 - prob10; format _numeric_ 3.2; run; And the results are: p p p p p p p p p p p r r r r r r r r r r r o By placing the R and SAS solutions together and by covering a vast array of tasks in one book, Kleinman and Horton have added surprising value and searchability to the information in their.

SAS : Detailed Explanation of Proc Means

How to use PROC R in SAS Jigsaw Academ

  1. PROC MEANS More than just your average procedure by Peter R. Welbrock, courtesy of NESUG The power of PROC FORMATby Jonas V. Bilenas, courtesy of NESUG ; Ten Things You Should Know About PROC FORMAT by Jack Shoemaker, courtesy of NESUG; PROC SQL for DATA Step Die-Hards by Christianna S. Williams, courtesy of NESU
  2. SAS In SAS we'll use proc lifetest with the strata statement, as in section 5.6.3, removing subjects with missing time, censoring, or treatment indicators using the nmiss function (section 1.4.14) and subsetting if statement (section 1.5.1)
  3. PROC FREQ in SAS is used to find the frequency table. PROC FREQ with condition using WHERE Clause; frequency table without cumulative and percentage; Let's see an example for PROC FREQ with Graph; PROC FREQ with sort.PROC FREQ for cross tables by removing unwanted statistics using norow nocum nopercent . PROC FREQ store the results of frequency table etc
  4. Package 'pROC' January 13, 2021 Type Package Title Display and Analyze ROC Curves Version 1.17.0.1 Date 2021-01-07 Encoding UTF-8 Depends R (>= 2.14

Proc Logistic and Logistic Regression Model

sas: proc reg & r squared change When you conduct stepwise regression, one of the interests is to examine if the newly added variables significantly improve the model prediction, which can be tested by checking R squared change $\begingroup$ @EricaN One thing that you just reminded me of is that you should compare the random effects from R to those in SAS using the ranef() function rather than coef().The former gives the actual random effects, while the latter gives the random effects plus the fixed-effects vector. So this accounts for a lot of why the numbers illustrated in your post differ, but there is still a. SAS Programming: SAS Code Structure . SAS programming is based on two building blocks: DATA Step: The DATA step creates a SAS data set and then passes the data onto a PROC step; PROC Step: The PROC step processes the data; A SAS program should follow below mentioned rules: Almost every code will begin with either DATA or a PROC Ste

SAS(R) Procedures by Name and Produc

  1. PROC CONTENTS DATA=sample; RUN; As with all SAS procedures, the DATA command (which specifies the name of the dataset) is optional, but recommended. If you do not specify a dataset, SAS will use the most recently created dataset by default. The screenshot below shows the output of PROC CONTENTS on the sample data file. Key elements are labeled.
  2. Models fit with PROC GLIMMIX can have none, one, or more of each type of random effect. Note that an R-side effect in PROC GLIMMIX is equivalent to a REPEATED effect in the MIXED procedure. The R-side covariance structure in PROC GLIMMIX is the covariance structure that you formulate with the REPEATED statement in the MIXED procedure
  3. For other situations, see the SAS/STAT manual about proc glm. For other procedures, see the SAS manual for information on how missing data are handled. 4. Missing values in assignment statements. It is important to understand how missing values are handled in assignment statements. Consider the example shown below

R help - replicating SAS's proc rank procedur

names one CAS table to process. The default for libref is the libref of the procedure input library. For example, to obtain the contents of the table HtWt from the procedure input library, use the following PROC CONTENTS: proc contents data=HtWt; < PDF - Download sas for free Previous Next This modified text is an extract of the original Stack Overflow Documentation created by following contributors and released under CC BY-SA 3. In this case the procedure writes a warning to the SAS log. On many devices, you can correct crowded values by increasing the number of cells in your graphics is displayed using the HPOS= and VPOS= graphics options. See: Understanding Midpoints: Example: Grouping and Subgrouping a Block Chart.

The SCORE procedure multiplies values from two SAS data sets, one containing coefficients (for example, factor-scoring coefficients or regression coefficients) and the other containing raw data to be scored using the coefficients from the first data set. The result of this multiplication is a SAS data set containing linear combination Random starting values can be generated by the program, or the user can provide starting values in a SAS data file. An empirical demonstration of PROC LCA appeared in Structural Equation Modeling: Lanza, S. T., Collins, L. M., Lemmon, D. R., & Schafer, J. L. (2007). PROC LCA: A SAS procedure for latent class analysis SAS offers extensive support to most of the popular relational databases by using SQL queries inside SAS programs. Most of the ANSI SQL syntax is supported. The procedure PROC SQL is used to process the SQL statements. This procedure can not only give back the result of an SQL query, it can also create SAS tables & variables SAS SQL Procedure User's Guide Tree level 2. Node 4 of 6. Reporting Procedure Styles Tip Sheet Tree level 2. Node 5 of 6. Video: How to Write JSON Output from SAS Tree level 2. Node 6 of 6 . DATA Step Programming Tree level 1. Node 7 of 31. PROC MIXED Contrasted with Other SAS Procedures PROC MIXED is a generalization of the GLM procedure in the sense that PROC GLM fits standard linear models, and PROC MIXED fits the wider class of mixed linear models. Both procedures have similar CLASS, MODEL, CONTRAST, ESTI-MATE, and LSMEANS statements, but their RANDOM and REPEATED statement

Linear Models in SAS (Regression & Analysis of Variance) The main workhorse for regression is proc reg, and for (balanced) analysis of variance, proc anova.The general linear model proc glm can combine features of both. Further, one can use proc glm for analysis of variance when the design is not balanced. Computationally, reg and anova are cheaper, but this is only a concern if the model has. Introduction to SAS/GRAPH • Graphics component of SAS system. • Includes charts, plots, and maps in both 2 and 3 dimensions. • Procedures included GCHART, GPLOT, GMAP, GCONTOUR etc • We will focus on PROC GPLO Using R, you can directly reference to any cell in the whole matrix. For instance, you have a matrix with 5 rows and 5 columns. You want to add number 3 to the cell (3,3) . This operation can be done very easily on R, but on SAS, you will have a hard time figuring out the right code. SAS does line by line operation on tables SAS is the leader in analytics. Through innovative Analytics, Artificial Intelligence and Data Management software and services, SAS helps turn your data into better decisions

Proc corr SAS Annotated Outpu

The VARCLUS procedure is a useful SAS procedure for variable reduction. It is based on divisive clustering technique. All variables start in one cluster. Then, a principal components analysis is done on the variables in the cluster to determine whether the cluster should be split into two subsets of variables SAS® and R - stop choosing, start combining and get benefits!, continued 2 can be accessed from SAS via PROC IML. This paper focuses on the SAS procedure PROC IML and its features to integrate the R language. Special features of SAS/IML as well as the SAS/IML Studio which provides a dynamic an names the SAS data set to be used by PROC REG. be an ordinary SAS data set or a TYPE=CORR, TYPE=COV, or TYPE=SSCP data set. If one of these special TYPE= data sets is used, the OUTPUT, PAINT, PLOT, and REWEIGHT statements and som 3 proc transpose in SAS for long and wide format conversion data samp; input row subject $ treatment $ pc20; cards; 1 1 R1 3.23515672 2 1 R2 4.14426184 3 1 R3 5.85422186 4 1 T 4.40670538 5 2 R1 -0.04801373 6 2 R2 3.47731900 7 2 R3 2.88554550 8 2 T 2.44074469.

Solved: R-square in logistic regression - SAS Support

SAS Viya is an exciting addition to the SAS Platform, allowing you to conduct analysis faster than ever before and providing you the flexibility to utilize open source technologies and generate insights from data in any computing environment As noted here, there is a massive amount of inertia/legacy behind SAS; but SAS just like R is a way to a means, not the means itself. SAS is extremely efficient at sequential data access, and database access through SQL is extremely well integrated

Using R from SAS - University of Wisconsin-Madiso

Package 'pROC' January 13, 2021 Type Package Title Display and Analyze ROC Curves Version 1.17.0.1 Date 2021-01-07 Encoding UTF-8 Depends R (>= 2.14 Here is code to calculate RMSE and MAE in R and SAS. RMSE (root mean squared error), also called RMSD (root mean squared deviation), and MAE (mean absolute error) are both used to evaluate models. MAE gives equal weight to all errors, while RMSE gives extra weight to large errors A.1 SAS EXAMPLES SAS is general-purpose software for a wide variety of statistical analyses. The main procedures (PROCs) for categorical data analyses are FREQ, GENMOD, LOGISTIC, NLMIXED, GLIMMIX, and CATMOD. PROC FREQ performs basic analyses for two-way and three-way contingency tables. PROC GENMOD ts generalized linea

Regression Analysis SAS Annotated Outpu

PROC NLIN The NLIN procedure in SAS/STAT is used for fitting nonlinear regression models. In this, it estimates the parameters by using the method of nonlinear least squares or weighted nonlinear least squares. The NLIN procedure is specially used for segmented models As previously mentioned, this seamless ability to execute R code directly from SAS requires license of appropriate software in SAS. Two products, one from SAS and one from an external vendor, are readily available for this purpose. If you have the SAS/IML procedure licensed, then you can execute R code from a SAS IML Studio 3.2 session

The PROC TRANSPOSE statement tells SAS to execute the transpose procedure on an existing dataset called Dataset-name. The OUT keyword says that the transposed dataset should be created as a new dataset called New-dataset-name. The BY statement is used to determine the row structure of the transposed dataset As for the second question, your SAS code doesn't quite match your R code; it only has a term for fac*ind, while the R code has a term for both ind and fac*ind. (See the Variance Components output to see this.) Adding this gives the same SE for trt in all models in both Q1 and Q2 (0.1892) SAS procedures are usually far more efficient. This talk shows how to fit neural networks using SAS/OR notR, SAS/ETS R, and SAS/STAT R software. Introduction As Sarle (1994) points out, many types of neural networks (NNs) are similar or identical to conventional statistical methods. However, many NN training methods converge slowly or not at all The example in this section calls an R package and imports the results into a SAS data set. This example is similar to the example in the section Creating Graphics in a SUBMIT Block, which calls the UNIVARIATE procedure to create a kernel density estimate. The program in this section consists of the following steps

Performing an Outer Join :: SAS(R) 9

The SAS PROC CONTENTS statement prints SAS meta data about the Table1_From_SS table in the SQL Server database referenced by the SQL SAS name. The SAS PROC PRINT statement displays the actual data values for all columns and all rows in the SQL Server Table1_From_SS table SAS date, time, and date/time variables are converted respectively to Date, POSIX, or chron objects in R, variable names are converted to lower case, SAS labels are associated with variables, and (by default) integer-valued variables are converted from storage mode double to integer Proc Tabulate is mainly used to create a professional looking table. Terminologies VAR : The Var statement tells SAS that these variables are analysis variables. They must be numeric. They are used to create summary statistics. CLASS : The Class statement tells SAS that these variables are categorical variables Using PROC GLM. The linear regression model is a special case of a general linear model. Here the dependent variable is a continuous normally distributed variable and no class variables exist among the independent variables. Therefore, another common way to fit a linear regression model in SAS is using PROC GLM. PROC GLM does support a Class.

%PROC_R: A SAS Macro that Enables Native R Programming in

Pearson Correlation with PROC CORR - SAS Tutorials

SAS graphs for R programmers - paneled graphs

Technical overview and terminology. SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it. SAS provides a graphical point-and-click user interface for non-technical users and more through the SAS language.. SAS programs have DATA steps, which retrieve and manipulate data, and PROC steps, which analyze the data This is my second post in converting SAS's PROC MCMC examples in R. The task in his week is determining the transformation parameter in a Box-Cox transformation. SAS only determines Lambda, but I am not so sure about that. What I used to do was get an interval for Lambda, select an interpretable value (e.g. 1/2 is square root, -1 is inverse. 2. SAS SQL - PROC SQL SAS. The procedure PROC SQL is used to process the SQL statements. This procedure can not only give back the result of an SQL query, it can also create SAS tables & variables. The syntax of PROC SQL SAS-PROC SQL: calls the SAS SQL procedure SELECT: specifies the column(s) (variables) to be selecte SAS statement or procedure its name is in bold face. Menu commands are accessed by clicking the left button of the mouse on items in lists. We use a special notation for menu commands. For example, A I B I C means left-click the command A on the menu bar, then in the list that drop

Hi all, By using SAS code to create the report table with three regressions having the same number of independent variables as below : The Press J to jump to the feed. Press question mark to learn the rest of the keyboard shortcut The GLM Procedure Overview The GLM procedure uses the method of least squares to fit general linear models. Among the statistical methods available in PROC GLM are regression, analysis of variance, analysis of covariance, multivariate analysis of variance, and partial corre-lation. PROC GLM analyzes data within the framework of General linear. The matrix of row scores R h has dimension (R-1) ×R and is created internally by PROC FREQ as R h = [ I R-1, -J R-1] where I R-1 is an identity matrix of rank R-1, and J R-1 is an (R-1) ×1 vector of ones. This matrix has the effect of forming R-1 independent contrasts of the R mean scores

PPT - PROC GLIMMIX Generalized Mixed Linear Models

SAS : Power of PROC FORMAT Deepanshu Bhalla 3 Comments SAS. This tutorial explains the uses of PROC FORMAT in the most common data manipulation tasks. Sample Data Data Source : sashelp.cars. Sample Data: Example 1 : Suppose you are asked to group MSRP variable based on the following conditions and check the number of observations falling in. In SAS the SD values is measured using PROC MEAN as well as PROC SURVEYMEANS. Using PROC MEANS. To measure the SD using proc means we choose the STD option in the PROC step. It brings out the SD values for each numeric variable present in the data set. Syntax. The basic syntax for calculating standard deviation in SAS is − PROC means DATA. Using SAS's PROC GPLOT to plot data and lines PROC GPLOT creates publication quality color graphics which can easily be exported into documents, presentations, etc. To export the graphs for future use click on file, export. In the dialog box choose

PROC LCA: A SAS Procedure for Latent Class Analysis Struct Equ Modeling. 2007;14(4):671-694. doi: 10.1080/10705510701575602. Authors Stephanie T Lanza 1 , Linda M Collins, David R Lemmon, Joseph L Schafer. Affiliation 1 The Methodology Center, The. For the GPLOT procedure, SYMBOL definitions control the appearance of plot symbols and plot lines, including bars, boxes, confidence limit lines, and area fills. interpolation methods. how plots handle data out of range. For the GCONTOUR procedure, SYMBOL definitions control the appearance and text of contour labels. the appearance of contour. Folks, In this blog we will explore the basic concept of Inner Join using SAS Merge & Proc SQL. An inner join retrieve only the matched rows from the data-sets/tables. Suppose we have two data-sets/tables Customer & Sales. So an inner join of Customer and Sales gives the result of Customer intersect Sales, i.e. the inner part of Sas Institut

SAS Correlation Analysis - Understand the PROC CORR

Updating Data in a PROC SQL Table :: SAS(R) 9PROC VARCLUS: Correlations among Physical Variables :: SAS
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