Course Title: TRAINING COURSE ON QUANTITATIVE DATA MANAGEMENT AND ANALYSIS USING SAS

Course Date Location Course fee: Click to Register (Group)
Start Date: 26/12/2022 End Date: 30/12/2022 Nairobi Kenya $ 1,000 Register as Individual Register for Online Training Register as a Group
Start Date: 13/02/2023 End Date: 17/02/2023 Nairobi Kenya $ 1,000 Register as Individual Register for Online Training Register as a Group

INTRODUCTION

SAS (Statistical Analysis Software) is used in data management, analysis and graphics. This includes advanced features including forecasting, survival analysis, data analysis and time series analysis and research methods.  The trainees of this course will be able to correctly analyze data using SAS by the end of the 5-day programme.

Participants who successfully complete the course will receive Certificate of Participation.

OBJECTIVES

By the end of this course the participants will be able to:

·         Get Data in various format into SAS

·         Create temporary and permanent SAS data sets

·         Combine data sets

·         Use SAS Functions to manipulate SAS date values

·         Use SAS Functions to manipulate character and numeric data values

·         Conditionally execute SAS statements:

·         Creating Variables in an ARRAY Statement;

·         Process data with DO LOOPS

·         Work with data & Creating labels and formats

·         SAS Statistical Procedures

·         Generate list reports using the PRINT procedure (using VAR, SUM, WHERE, ID and BY statements

·         Generate reports using ODS statements (Identify ODS destinations, create HTML, PDF, RTF, and Excel files with ODS statements)

·         Reconstruct/Reshape SAS Data sets in DATA step and using Proc TRANSPOSE

DURATION

 5 days

WHO SHOULD ATTEND?

This course is intended for Statisticians, data analysts, or a budding data scientist and beginners who want to learn how to analyze data with SAS.

COURSE OUTLINE

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

·         Merge two datasets into a single dataset

·         Project part 3: Merge two datasets

·         Transpose

·         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

 

GENERAL NOTES

·         The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

·         The participants should be reasonably proficient in English as all facilitation and course materials will be offered in English.

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

·         The training will be held at Kincaid Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.

·         All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.

·         Accommodation and airport pickup are arranged upon request. For reservations contact the Training coordinator at Email: training@kincaiddevelopmentcenter.org or Tel: +254 724592901

·         This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our Kincaid Training Centre or at a convenient location.

 

For further inquiries, please contact us on Tel: +254 724592901 or send mail to training@kincaiddevelopmentcenter.org

 

Payments are due upon registration. Payment should be sent to our Bank account before commencement of training and proof of payment sent to training@kincaiddevelopmentcenter.org