Webinar: Data Analysis, Sampling and Hypothesis Testing
There’s a saying – you can’t improve what you can’t measure. This has never been truer than in the case of businesses, which collect data from different sources, to measure different aspects of their performance and to understand what is happening, in different areas of operations.
However, collecting data on its own is not enough to give you a serious grasp over business processes, as the data itself is facts and figures. It should first be analyzed, using different tools and techniques, to get a better understanding of the operations, market, and customers.
Data Analysis helps businesses organize, prepare, interpret and get useful information that help decision-makers take actions based on measurable facts and information. To give you just a few examples, you can use data to explore and describe past performance, measure specific KPIs, research a topic of interest and/or predict future outcomes.
Main topics covered
- Data Analysis – Key Concepts
- Relevant Data Analysis Techniques
- The process and importance of Sampling
- Hypothesis testing using different methods
- The impact of data analysis on the decision-making process
Key Learning Points
- Understand the need for Data Analysis in Business
- Understand how we can get benefit from the data to help in decision-making process
- Use Microsoft Excel – Data Analysis tool
- Learn about hypothesis testing procedure using different hypothesis tests
- How to interpret the results you get from the survey
Presenter’s profile
Fadi Fuad Al-Jafari is a Management Consultant at The KPI Institute with Specialties in Data Surveying and Data Visualization. He delivered multiple training courses in 4 countries in Data Analysis and Visualization.
Fadi has several certifications in Statistics Foundation, Data Analysis using Excel, Analyzing and Visualizing Data with Excel, Working with Real-Time Data in Excel, Excel Macros in Depth, Predictive Analytics using BigML and he has been part of several projects in the last years.