INTRODUCTION TO RESEARCH DATA ANALYSIS: Excel Application

Description

While Excel is a powerful tool for data analysis, it's worth noting that for more complex and specialized tasks, you may eventually need to explore other data analysis tools and programming languages. However, Excel is an excellent starting point and can often meet the needs of many data analysis projects. It is for this reason that this course presents the fundamentals in data analysis, and a guide on how to use of Microsoft Excel for this purpose. It offers lessons that covers areas in Measures of Central Tendency, Measures of Dispersion, Correlation, Regression and Inferential statistics.

Excel is known for its user-friendly interface. It doesn't require extensive programming or technical skills, making it accessible to a broad audience. It provides a wide range of built-in functions and formulas for performing basic calculations and mathematical operations.

Excel is a versatile tool that can handle a wide range of data analysis tasks, from simple data entry and calculations to more complex statistical analysis and data visualization. Learning Excel for data analysis provides you with transferable skills that can be valuable in various roles and industries. It can also serve as a foundation for learning more advanced data analysis tools like Microsoft Power BI, R, or Python.

What You Will Learn!

• Identify and discuss the various statistical methods
• Choose the right statistics for analysis collected data
• Implement data analysis on Microsoft Excel
• Interpret results of analsys and draw inferences

Who Should Attend!

• Academic researchers
• High school, undergraduate and postgraduate students

TAKE THIS COURSE