Format: Live instructor-led online training via Zoom / Microsoft Teams

Quantitative Data Management and Analysis with SAS Training Course

Introduction

The Quantitative Data Management and Analysis with SAS Course is designed to equip professionals with advanced analytical and statistical skills using SAS software. SAS (Statistical Analysis System) is one of the most powerful tools for managing, analyzing, and visualizing large-scale quantitative data in research, business, and policy environments. This course provides a comprehensive understanding of data preparation, statistical modeling, and interpretation techniques, enabling participants to derive actionable insights from quantitative datasets.

In today’s data-driven world, organizations and researchers rely heavily on quantitative analysis to make informed decisions. This SAS training covers key areas such as data cleaning, transformation, regression analysis, ANOVA, hypothesis testing, and predictive modeling. Participants will learn how to apply quantitative techniques to real-world datasets using SAS procedures and advanced analytics functions. The training emphasizes accuracy, reproducibility, and efficiency in handling large datasets for decision-making and reporting.

The course bridges theory and practice through a hands-on, case study-driven approach. Participants will use SAS tools such as SAS Studio, Enterprise Guide, and SAS Visual Analytics to explore quantitative data from diverse fields, including health, business, economics, and social sciences. With a focus on applied data management, statistical inference, and modeling, the course prepares participants to tackle modern data challenges with confidence and expertise.

By completing this course, participants will gain the technical skills and analytical mindset required to perform complex quantitative analysis using SAS. They will be able to design data collection frameworks, clean and manage data effectively, conduct advanced statistical analyses, and generate insightful reports that inform strategic decisions.

Course Objectives

1. Understand the fundamentals of quantitative data management using SAS.
2. Master SAS data manipulation, cleaning, and transformation techniques.
3. Apply statistical methods such as regression, ANOVA, and hypothesis testing.
4. Learn how to build and validate predictive models using SAS.
5. Conduct exploratory data analysis and data visualization.
6. Develop reproducible workflows for large-scale data projects.
7. Gain practical experience in coding with SAS syntax and procedures.
8. Apply quantitative methods to solve real-world analytical problems.
9. Interpret statistical results for decision-making and reporting.
10. Integrate SAS with other data analytics tools and platforms.

Organization Benefits

1. Enhanced capacity for data-driven decision-making.
2. Improved data management and analytics workflows.
3. Strengthened research and reporting efficiency.
4. Increased organizational competence in statistical modeling.
5. Reduced dependence on external data analysts and consultants.
6. Empowered staff with SAS proficiency for advanced data analysis.
7. Enhanced data accuracy, reproducibility, and compliance.
8. Better insights into business performance and operational efficiency.
9. Improved communication of analytical findings through visualization.
10. Competitive advantage through data literacy and innovation.

Target Participants

• Data analysts and statisticians.
• Monitoring and evaluation professionals.
• Researchers and academic staff.
• Business intelligence and data science practitioners.
• Economists and financial analysts.
• Health, social science, and development researchers.
• Policy planners and program evaluators.
• Graduate students in data-related fields.

Course Outline

Module 1: Introduction to SAS and Quantitative Data

1. Overview of SAS environment and interface.
2. Understanding quantitative data types and structures.
3. Importing and exporting datasets in SAS.
4. Introduction to SAS libraries and data steps.
5. Case study: Setting up a quantitative data analysis project in SAS.
6. Practical exercise: Loading and inspecting real-world datasets.

Module 2: Data Management and Cleaning

1. Data entry, transformation, and recoding in SAS.
2. Handling missing data and outliers.
3. Merging and appending datasets.
4. Data validation and error checking.
5. Case study: Cleaning household survey data using SAS.
6. Workshop: Developing automated data cleaning scripts.

Module 3: Descriptive and Inferential Statistics

1. Descriptive analysis using PROC MEANS and PROC FREQ.
2. Hypothesis testing and confidence intervals.
3. Correlation and chi-square analysis.
4. ANOVA and t-tests in SAS.
5. Case study: Statistical analysis of healthcare outcomes.
6. Group exercise: Reporting descriptive statistics in SAS.

Module 4: Regression and Predictive Modeling

1. Simple and multiple linear regression.
2. Logistic regression and model diagnostics.
3. Variable selection and model validation.
4. Predictive modeling using SAS procedures.
5. Case study: Predicting sales trends using SAS regression models.
6. Workshop: Building a predictive model using real data.

Module 5: Data Visualization and Reporting

1. Data visualization using PROC SGPLOT and SAS Visual Analytics.
2. Creating charts, graphs, and dashboards.
3. Automating report generation with SAS ODS.
4. Communicating analytical findings effectively.
5. Case study: Visualizing financial performance indicators.
6. Simulation: Developing an interactive SAS dashboard.

Module 6: Advanced Topics and Case Studies

1. Time series analysis and forecasting in SAS.
2. Multivariate data analysis techniques.
3. Integrating SAS with R and Python.
4. Automating workflows with SAS macros.
5. Case study: Forecasting agricultural production data.
6. Final project: Full-cycle quantitative data analysis using SAS.

General Information

1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after the course.
11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.
14. Website: Visit our website at www.fdc-k.org for more information.