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SAS Enterprise Guide 1: Querying and Reporting

30 Hours
Online Instructor-led Training
USD 1399 (USD 2800)
Save 50% Offer ends on 30-Jun-2024
 SAS Enterprise Guide 1: Querying and Reporting course and certification
318 Learners

About this Course

 

SAS Enterprise Guide 2: Advanced Tasks and Querying

This course is intended for experienced SAS Enterprise Guide users who want to learn more about advanced SAS Enterprise Guide techniques. It focuses on using the Query Builder within SAS Enterprise Guide, including manipulating character, numeric, and date values; converting variable type; and building conditional expressions using the Expression Builder. This course also addresses efficiency issues, such as joining tables and using a single query to group, summarize, and filter data.

Learn how to
  • Use tasks to transpose, stack, rank, and create a random sample of your data.
  • Use functions to convert the data type from character to numeric and from numeric to character.
  • Use conditional logic in the Query Builder to create new columns.
  • Use multiple value prompts.

Creating Reports and Graphs with SAS Enterprise Guide


This course is intended for experienced SAS Enterprise Guide users who want to create customized reports and graphs. You learn how to use point-and-click tasks and wizards in SAS Enterprise Guide to generate detail and summary reports. You also learn how to enhance reports by using task options and modifying the generated SAS code. In addition, the course illustrates how to create and customize bar charts, map charts, histograms, box plots, scatter plots, line plots, and bar-line charts using SAS Enterprise Guide tasks and wizards.

Learn how to
  • build complex tabular reports with the Summary Tables task and List Report Wizard
  • create and apply custom formats to improve the displayed data values
  • generate customized bar charts
  • analyze the distribution of numeric variables with histograms and box plots
  • produce map charts to display data geographically
  • examine trends with scatter plots and line plots.

SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression

This course is designed for SAS Enterprise Guide users who want to perform statistical analyses. The course is written for SAS Enterprise Guide 7.1 along with SAS 9.4, but students with previous SAS Enterprise Guide versions will also get value from this course. An e-course is also available for SAS Enterprise Guide 5.1 and SAS Enterprise Guide 4.3.

Learn how to
  • generate descriptive statistics and explore data with graphs
  • perform analysis of variance
  • perform linear regression and assess the assumptions
  • use diagnostic statistics to identify potential outliers in multiple regression
  • use chi-square statistics to detect associations among categorical variables
  • fit a multiple logistic regression model.
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Target Audience

Non-programmers with SAS Enterprise Guide experience, as well as experienced programmers with SAS Enterprise Guide experience

Experienced SAS Enterprise Guide users who want to create complex reports and graphs using point-and-click methods and simple code modifications

Statisticians and business analysts who want to use a point-and-click interface to SAS
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SAS Enterprise Guide 1: Querying and Reporting

Course Details & Curriculum
SAS Enterprise Guide 2: Advanced Tasks and Querying

Working with Data in a Project
  • Working with projects.
  • Accessing data.
Transforming SAS Tables
  • Append Tables task.
  • Split Columns task.
  • Stack Columns task.
  • Random Sample task.
  • Sort Data task.
Manipulating Data Values
  • Introduction to SAS functions.
  • Manipulating numeric values.
  • Manipulating character values.
  • Converting data type.
Prompting and Conditional Processing
  • Multiple values prompts.
  • Range prompts.
  • Conditional processing of project steps.
Recoding Data Values
  • Recoding values.
  • Recoding values based on a condition.
  • Writing CASE expressions.
  • Creating and applying custom formats.
Grouping and Filtering
  • Grouping and summarizing data.
  • Including detail and summarized data.
  • Filtering summarized data in groups.

Creating Reports and Graphs with SAS Enterprise Guide


Course Overview
  • overview of topics and data
  • preparing data
  • output options
Bar Charts
  • Bar Chart Wizard
  • Bar Chart task
  • creating and applying custom formats
  • customizing bar chart code
Summary Tables Task
  • Summary Tables Wizard (review)
  • Summary Tables task
  • enhancing results with summary tables properties
  • including percentages
  • customizing results with code
List Report Wizard
  • overview of the List Report Wizard
  • creating detail and summary reports
  • creating crosstab reports
  • enhancing results with code
Picturing Distributions
  • visualizing distributions
  • picturing distributions with tasks
Map Charts
  • overview of mapping
  • using the Map task to create a simple map chart
  • customizing map charts
Scatter Plots and Line Plots
  • scatter plots and line plots
  • single line plots
  • overlaid line plots
  • bar-line charts
Learning More

SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression


Prerequisite Basic Concepts
  • discussing descriptive statistics
  • discussing inferential statistics
  • listing steps for conducting a hypothesis test
  • discussing basics of using your SAS software
Getting Started in Enterprise Guide 7.1
  • introducing to the SAS Enterprise Guide 7.1 environment
Introduction to Statistics
  • discussing fundamental statistical concepts
  • examining distributions
  • describing categorical data
  • constructing confidence intervals
  • performing simple tests of hypothesis
Analysis of Variance (ANOVA)
  • performing one-way ANOVA
  • performing multiple comparisons
  • performing two-way ANOVA with and without interactions
Regression
  • using exploratory data analysis
  • producing correlations
  • fitting a simple linear regression model
  • understanding the concepts of multiple regression
  • building and interpreting models
  • describing all regression techniques
  • exploring stepwise selection techniques
Regression Diagnostics
  • examining residuals
  • investigating influential observations and collinearity
Categorical Data Analysis
  • describing categorical data
  • examining tests for general and linear association
  • understanding the concepts of logistic regression and multiple logistic regression
  • performing backward elimination with logistic regression
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