Basic and Classic Data Management in SAS

This course aims to provide a comprehensive introduction to the SAS analytic software for Windows. Through a mixture of lectures and in-class examples, quizzes, and take-home assignments, students will gain experience using the SAS system for data manipulation, management and analysis. Emphasis will be placed on the skills and techniques necessary for efficient data manipulation, management and analysis. It is designed for students with little to no background with SAS, and an understanding of the basic statistical concepts. This will be an excellent choice for your first SAS introduction course for your data analysis career.

Target Participants

• Anyone from other programming fields that are interested in SAS
• Anyone with no SAS background
• Anyone who wants to understand the workflow in SAS

Course Objectives

What you'll learn

• Master fundamentals of using SAS
• Read and write various types of raw data with different formats and options
• Create and modify various professional and statistical reports
• Master the most complete SAS descriptive statistical analysis

Course content

1. Fundamentals of Using SAS (part I)

• Introduction to SAS
• Descriptive information and statistics
• An overview of statistical tests in SAS
• Exploring data with graphics

2. Fundamentals of Using SAS (part II)

• Using where with SAS procedures
• Missing values in SAS
• Common SAS options
• Overview of SAS syntax of SAS procedures
• Common error messages in SAS

3. Reading Raw Data into SAS

• Inputting raw data into SAS
• Reading dates into SAS and using date variables

4. Basic Data Management in SAS

• Creating and recoding variables
• Using SAS functions for making/recoding variables
• Subsetting variables and observations
• Labeling data, variables and values
• Using Proc Sort and the BY statement
• Making and using permanent SAS data files (version 8)

5. Classic Data Management Problems

• Merging Data Files via Data Step, Proc SQL
• Concatenating (stacking) SAS data files
• Working across variables
• Collapsing across observations in SAS via Proc Means, Proc SQL, Data Step I, Data Step II
• Reshaping data from wide to long via Proc Transpose, Data Step
• Reshaping data from long to wide via Proc Transpose, Data Step

6. Other

• Comparing SAS and Stata side by side

Prerequisites

It is designed for students with little to no background with SAS.

Training Approach

This Basic and Classic Data Management in SAS course is delivered by our seasoned trainers who have vast experience as expert professionals in data analysis with Stata. The course features plenty of practice materials, quizzes, and a final assessment to cement your newly acquired SAS skills.

Training manuals and additional reference materials are provided to the participants.

Certification

Upon successful completion of this course, participants will be issued with a certificate.

Tailor-Made Course

We can also do this as a tailor-made course to meet organization-wide needs. A training needs assessment will be done on the training participants to collect data on the existing skills, knowledge gaps, training expectations, and tailor-made needs.

Course Duration (classroom-based)

2 Days (8 hours a day)

Payment

1200 ETB

Course Level

Beginner level

Training Language

English (Optional - Amharic)

Download the Course Outline

Download this course outline for use offline or for other devices.

Statistical Data Analysis with SAS

This course aims to provide a comprehensive introduction to the SAS analytic software for Windows. Through a mixture of lectures and in-class examples, quizzes, and take-home assignments, students will gain experience using the SAS system for data manipulation, management and analysis. You will also expect a LOT of extracurricular learning materials for self-pace learning, treat it as a BONUS! Emphasis will be placed on the skills and techniques necessary for efficient data manipulation, management and analysis. This will be an excellent choice for your first SAS introduction course for your data analysis career.

Target Participants

• Anyone from other programming fields that are interested in SAS
• Anyone with no SAS background
• Anyone who wants to understand the workflow in SAS

Course Objectives

What you'll learn

• Learn SAS and be confident on your data analysis skills
• Learn to accomplish a task with various SAS techniques, with tons of examples and quizes
• Learn step-by-step statistical analysis from descriptive statistics, hypothesis testing to linear regression
• Learn data importing with different techniques for variuos type of data
• Use many important functions to make SAS programming easy
• Advanced concepts of meta data: formats and informats, labels, lengths, etc.
• Learn the manipulation techniques to prepare the data and make the data analysis-ready
• Perform dataset manipulations: subsetting, transposition, etc.
• Be able to properly interpret the results from statistical analyses

Course content

1. Understanding the workflow

• Overview
• Ask Questions Wisely to Assist Project Planning
• SAS Basics
• Data Importing - Instream data and Proc Import
• Import Wizard for SAS 9.x
• Data Importing in SAS Studio
• Bring in Data from Pre-existing SAS Dataset and Create Permanent Dataset
• Project Part 1: Data importing - excel data (a must to the other assignments)

2. Data Manipulation - Naming Convention and IF THEN/ELSE Statement

• Overview
• Naming Convention and Variable Types
• IF THEN/ELSE Statement
• Keep and Drop Variables

3. Data Manipulation - SAS Functions and DO Loop

• Overview
• SAS Functions
• DO Loop

4. Dataset Manipulation - Subset and Append

• Overview
• Subset
• Use WHERE statement to subset data
• Concatenation (Append)
• Project Part 2: Concatenate 3 of the 4 datasets into one

5. Data Manipulation - Merge and Transposition

• Overview
• Merge
• Project part 3: Merge two datasets
• Transpose

6. Descriptive Statistics - Frequency and Univariate Analysis

• Overview
• Explore the Data Using PROC PRINT and CONTENTS Procedures
• Descriptive Statistics
• Calculate the mean of the sample
• PROC FREQ
• Project Part 4: perform descriptive statistical analysis

7. One, Two Sample T-Test ANOVA

• Overview
• One Sample T-Test
• Two Sample T-Test
• Sample ANOVA
• Non-parametric Analysis

8. Linear Regression - Predicting the Outcome

• Overview
• Linear Regression
• Project Part 5: Use Linear Regression model to predict the MSRP
• Dummy Variable
• Project Part 6: Try to include some categorical variables into the model

Prerequisites

It is designed for students with little to no background with SAS, and an understanding of the basic statistical concepts.

Training Approach

This Statistical Data Analysis with SAS course is delivered by our seasoned trainers who have vast experience as expert professionals in data analysis with Stata. The course features plenty of practice materials, quizzes, and a final assessment to cement your newly acquired SAS skills.

Training manuals and additional reference materials are provided to the participants.

Certification

Upon successful completion of this course, participants will be issued with a certificate.

Tailor-Made Course

We can also do this as a tailor-made course to meet organization-wide needs. A training needs assessment will be done on the training participants to collect data on the existing skills, knowledge gaps, training expectations, and tailor-made needs.

Course Duration (classroom-based)

3 Days (8 hours a day)

Payment

1500 ETB

Course Level

Beginner level

Training Language

English (Optional - Amharic)

Download the Course Outline

Download this course outline for use offline or for other devices.

Complete & Practical SAS, Statistics & Data Analysis Course

This course aims to provide a comprehensive introduction to the SAS analytic software for Windows. Through a mixture of lectures and in-class examples, quizzes, and take-home assignments, students will gain experience using the SAS system for data manipulation, management and analysis. You will also expect a LOT of extracurricular learning materials for self-pace learning, treat it as a BONUS! Emphasis will be placed on the skills and techniques necessary for efficient data manipulation, management and analysis. This will be an excellent choice for your first SAS introduction course for your data analysis career.

Target Participants

• Beginners or job seekers interested in learning SAS Programming, statistical and data analysis in industry fields.
• People who wish to enter data science/analytics field.

Course Objectives

What you'll learn

• Be equipped with a powerful tool for the most powerful data analytics career path!
• Read and write various types of raw data with different formats and options
• Create and modify various professional and statistical reports
• Be aware of statistical analysis and concepts such as non-parametric test, interaction, correlation
• Master the most complete SAS graphics tool such GTL and statistical plots
• Learn comprehensive SAS Macro programming knowledge -- variables and user defined functions
• Perform many real world case studies -- retail banks, credit bureau, marketing firms and clinical trials
• Apply powerful data manipulation -- SQL, sub setting, slicing, filtering, transformation, ranking, sorting
• Understand data management and data piping
• Use SAS ODS -- help deliver many useful objects such as charts, tables between different systems
• Hundreds of SAS sample codes to explain arrays, functions and business cases

Course content

1. SAS Environment and Basic Concepts

• Introduce SAS environment
• SAS library
• Try SAS codes
• Homework and data installation

2. Get started SAS Programming

• Create data sets from external files
• SAS program - create data sets
• Valid names and comments
• SAS program -- Valid names and comments
• Data type and format
• SAS program -- data type and format
• SAS program - date and format
• Mechanism of SAS data set
• Summarize SAS operations

3. Input and output raw data

• List input (1)
• List input (2)
• SAS program -- list input
• Read data with fixed layout
• Read data with modified list input
• Input data with other features
• Write data using data step
• SAS program --write data
• Import and export data

4. Manipulate data by data step programming

• Duplicate data sets
• SAS program -- duplicate data sets
• Modify variables
• SAS program -- modify variables
• Variables selection
• Rename variables
• SAS program -- rename variables
• Assign labels to variables
• SAS program -- assign labels to variables
• Subsetting data sets
• SAS program -- Subsetting data sets

5. Control flow in SAS

• Structured programming (I)
• SAS program -- Structured programming (I)
• Structured programming (II)
• SAS program -- Structured programming (II)

6. SAS data step functions

• Data step character functions
• SAS program --data step character functions
• Data step numeric functions
• SAS program -- numeric functions
• Data step special functions
• Data step special functions
• User defined format
• SAS program -- User defined format

7. Use cases study

• Case study 001 (read employee data)
• SAS program -- read employee data
• Case study 002 (read chronic disease data)
• SAS program -- Case study 002(read chronic disease data)
• Case study 003 (read business account data)
• SAS program -- Case study 003 (read business account data)
• Case study 004 (process stock data)
• SAS program -- Case study 004 (process stock data)

8. Other SAS features in data step programming

• Automatic Variables (_N_ and _ERROR_)
• Output statement
• Return statement
• Pinpoint the first and last record
• SAS program -- Pinpoint the first and last record
• Retain statement
• SAS program -- Retain statement
• Data step array (1)
• Data step array (2)

9. Use cases study (2)

• Case study 005 (create new KPI features)
• Case study 006 (students grades)

Prerequisites

It is designed for students with little to no background with SAS. Understanding of the basic statistical concepts, basic computer operational skills, basic math skills, and data intuition is ideal.

Training Approach

This Statistical Data Analysis with SAS course is delivered by our seasoned trainers who have vast experience as expert professionals in data analysis with Stata. The course features plenty of practice materials, quizzes, and a final assessment to cement your newly acquired SAS skills.

Training manuals and additional reference materials are provided to the participants.

Certification

Upon successful completion of this course, participants will be issued with a certificate.

Tailor-Made Course

We can also do this as a tailor-made course to meet organization-wide needs. A training needs assessment will be done on the training participants to collect data on the existing skills, knowledge gaps, training expectations, and tailor-made needs.

Course Duration (classroom-based)

6 Days (8 hours a day)

Payment

2900 ETB

Course Level

Beginner to Intermediate level

Training Language

English (Optional - Amharic)

Download the Course Outline

Download this course outline for use offline or for other devices.

Statistics with SAS

This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. Thus, the course is designed to upgrade the skills of participants in the most appropriate methods of computation, analysis and presentation of statistical data to ensure most effective and efficient utilization of the data and information generated from them using SAS.

The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.

Target Participants

Anyone who wants to improve their skills on Statistical data analysis and understand the workflow in SAS. Thus, this SAS training is designed for participants who intend to learn the use of SAS for data management and data analysis. Those working in the corporate world, public sector, research institution and NGOs are welcomed.

Course Objectives

There are 8 modules in this course.

What you'll learn

• The course objective is to equip the participants with exceptional ability to manage qualitative and quantitative data, perform basic and advanced statistical techniques and interpret the output results in acceptable forms.

Course content

Module 1: Course Overview and Data Setup

• In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.

Module 2: Introduction and Review of Concepts

• In this module you learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. Then you review fundamental statistical concepts, such as the sampling distribution of a mean, hypothesis testing, p-values, and confidence intervals. After reviewing these concepts, you apply one-sample and two-sample t tests to data to confirm or reject preconceived hypotheses.

Module 3: ANOVA and Regression

• In this module you learn to use graphical tools that can help determine which predictors are likely or unlikely to be useful. Then you learn to augment these graphical explorations with correlation analyses that describe linear relationships between potential predictors and our response variable. After you determine potential predictors, tools like ANOVA and regression help you assess the quality of the relationship between the response and predictors.

Module 4: More Complex Linear Models

• In this module you expand the one-way ANOVA model to a two-factor analysis of variance and then extend simple linear regression to multiple regression with two predictors. After you understand the concepts of two-way ANOVA and multiple linear regression with two predictors, you'll have the skills to fit and interpret models with many variables.

Module 5: Model Building and Effect Selection

• In this module you explore several tools for model selection. These tools help limit the number of candidate models so that you can choose an appropriate model that's based on your expertise and research priorities.

Module 6: Model Post-Fitting for Inference

• In this module you learn to verify the assumptions of the model and diagnose problems that you encounter in linear regression. You learn to examine residuals, identify outliers that are numerically distant from the bulk of the data, and identify influential observations that unduly affect the regression model. Finally, you learn to diagnose collinearity to avoid inflated standard errors and parameter instability in the model.

Module 7: Model Building for Scoring and Prediction

• In this module you learn how to transition from inferential statistics to predictive modeling. Instead of using p-values, you learn about assessing models using honest assessment. After you choose the best performing model, you learn about ways to deploy the model to predict new data.

Module 8: Categorical Data Analysis

• In this module you look for associations between predictors and a binary response using hypothesis tests. Then you build a logistic regression model and learn about how to characterize the relationship between the response and predictors. Finally, you learn how to use logistic regression to build a model, or classifier, to predict unknown cases.

Prerequisites

Basic statistical knowledge and prior working knowledge of SAS software are required for this course.

Training Approach

This Statistics with SAS course is delivered by our seasoned trainers who have vast experience as expert professionals in data analysis with Stata. The course features plenty of practice materials, quizzes, and a final assessment to cement your newly acquired SAS skills.

Training manuals and additional reference materials are provided to the participants.

Certification

Upon successful completion of this course, participants will be issued with a certificate.

Tailor-Made Course

We can also do this as a tailor-made course to meet organization-wide needs. A training needs assessment will be done on the training participants to collect data on the existing skills, knowledge gaps, training expectations, and tailor-made needs.

Course Duration (classroom-based)

7 Days (8 hours a day)

Payment

3200 ETB

Course Level

Intermediate to Advanced level

Training Language

English (Optional - Amharic)

Download the Course Outline

Download this course outline for use offline or for other devices.