SAS refers to statistical software which is used in the management of data, analysis, and graphics. It comprises of advanced functions which includes forecasting, survival analysis, data analysis, and time series analysis and survey methods. It can be utilized via graphical interface using very intuitive language. It benefits from the active user community which gives its support on a dedicated mailing.
At the end of course participants should be able to:
- Understand the entire workflow from a high level perspective
- Learn the SAS basic to advance to buildup solid understanding of SAS technical skills
- Learn to accomplish a task with various SAS techniques
- Learn step-by-step statistical analysis from descriptive statistics, hypothesis testing to linear regression
- Learn data importing with different techniques for various type of data
- Use many important functions to make SAS programming
- Learn the important 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.
- Learn how to properly interpret the results from statistical analyses
WHO SHOULD ATTEND
The course targets Statistician, analyst, or a budding data scientist and beginners who want to learn how to analyze data with SAS.
Module 1: Research Design, Analysis and interpretation
- Introduction to Research and the Research Process
- Problem Definition
- Research Design and Secondary Data Sources
- Qualitative Methods
- Descriptive Research Design and Observation
- Causal Research Design
- Measurement, Scaling and Sampling
- Data Preparation and Analysis Strategy
- Hypothesis testing, Frequencies and Cross-tabulation
- Testing for Significant Differences – t-test/ANOVA
- Testing for Association – Correlation and Regression
Module 2: Understanding the Workflow
- The Workflow
- 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
- Data importing - excel data
Module 3: Data Manipulation - Naming Convention and IF THEN/ELSE Statement
- Naming Convention and Variable Types
- IF THEN/ELSE Statement
- Keep and Drop Variables
- Data Manipulation - SAS Functions and DO Loop
- SAS Functions
- DO Loop
- Dataset Manipulation - Subset and Append
- Use WHERE statement to subset data
- Concatenation (Append)
Module 4: Dataset Manipulation - Merge and Transposition
- Merge two datasets into a single dataset
- Project part 3: Merge two datasets
- A comprehensive task using several techniques to subset, transpose data
Module 6: Descriptive Statistics - Frequency and Univariate Analysis
- Explore the Data Using PROC PRINT and CONTENTS Procedures
- Descriptive Statistics
- Calculate the mean of the sample
- PROC FREQ
Module 7: Perform descriptive statistical analysis
- One, Two Sample T-Test and ANOVA
- One Sample T-Test
- Two Sample T-Test
- Two Sample T-Test and paired T-Test
- Sample ANOVA
- Non-parametric Analysis
Module 8: Linear Regression - Predicting the Outcome
- Linear Regression
- Use Linear Regression model to predict the MSRP
- Dummy Variable
- Include some categorical variables into the model
- This course is delivered by our seasoned trainers who have vast experience as expert professionals in the respective fields of practice. The course is taught through a mix of practical activities, theory, group works and case studies.
- Training manuals and additional reference materials are provided to the participants.
- Upon successful completion of this course, participants will be issued with a certificate.
- We can also do this as tailor-made course to meet organization-wide needs. Contact us to find out more: email@example.com
- The training will be conducted at DATA-AFRIQUE TRAINING CENTRE, NAIROBI KENYA.
- The training fee covers tuition fees, training materials, lunch and training venue. Accommodation and airport transfer are arranged for our participants upon request.
- Payment should be sent to our bank account before start of training and proof of payment sent to: firstname.lastname@example.org