A Gentle Introduction to Statistics Using SAS Studio. Ron Cody
Another option is to use PROC DATASETS, a SAS procedure that enables you to alter various attributes of a SAS data set without having to create a new copy of the data set.
When you import a CSV file without variable names, you will see variable names VAR1, VAR2, and so on, that are generated by SAS.
Importing Data from a CSV File
Comma-separated values (CSV) files are a popular format for external data files. As the name implies, CSV files use commas as data delimiters. Many websites enable you to download data as CSV files. As with Excel workbooks, your CSV file may or may not contain variable names at the beginning of the file. If the file does contain variable names, make sure that the “Generate SAS Variable Names” options box is checked; if not, deselect this option.
For example, look at the CSV file called Grades.csv in Figure 5.19 below:
Figure 5.19: CSV File Grades.csv
This CSV file contains the same data as the Excel Workbook Grades.xlsx. Notice that variable names are included in the file. You can import this file and create a SAS data set using the same steps that you used to import the Excel workbook. The import facility will automatically use the correct code to import this data file because of the CSV file extension. The resulting SAS data set is identical to the one shown in Figure 5.14.
Shared Folders (Accessing Data from Anywhere on Your Hard Drive)
When you follow the instructions in setting up SAS Studio, a default folder referred to in SAS Studio as /folders/myfolders allows you to read data from the folder called \SASUniversityEdition\myfolders on your hard drive. If this is the only place where you plan to read data, you do not need to create any other shared folders in your virtual computer.
If you need to read data from other locations on your hard drive, please see the relevant sections in SAS documentation.
Conclusion
In this chapter, you saw how to import data from Excel workbooks and CSV files. Importing data from any of the other choices displayed in Figure 5.3 follows the same basic procedure. If you need to read data from text files, you will need to learn some basic SAS programming, especially how to use the INPUT statement, one of the most powerful and versatile components of the SAS system.
Chapter 6: Descriptive Statistics – Univariate Analysis
Generating Descriptive Statistics for Continuous Variables
Investigating the Distribution of Horsepower
Adding a Classification Variable in the Summary Statistics Tab
Computing Frequencies for Categorical Variables
Creating a Filter Within a Task
Creating a Box Plot
Conclusion
Chapter 6 Exercises
Introduction
Before you begin any statistical test, you should spend some time “getting to know your data.” This chapter describes ways to examine both continuous and categorical data using a variety of techniques, including descriptive statistical measures such as means and standard deviations as well as graphical techniques such as histograms and box plots. The term univariate describes single variables and not the relationship between variables, which is a topic discussed in several of the later chapters in this book (such as correlation and regression).
This step is so important because understanding your data is necessary when you are choosing appropriate statistical tests to perform. Also, describing your data, especially using graphical techniques, is one way to spot possible errors in your data.
Generating Descriptive Statistics for Continuous Variables
Let’s use the CARS data set, which is located in the SASHELP library, to demonstrate how to produce descriptive statistics for continuous and categorical variables. Start by selecting Summary Statistics from the Statistics tab on the Tasks and Utilities Tasks menu, as shown in Figures 6.1 and 6.2 below.
Figure 6.1: Selecting Summary Statistics from the Statistics Task Menu
Double-click this selection to bring up the following screen.
Figure 6.2: DATA Tab for Summary Statistics
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