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Essential Mathematics for Data Analysis in Microsoft Excel

Data analysis is inextricably linked with maths. While statistics are the most important mathematical element, it also requires a good understanding of different formulas and mathematical inference. This course is designed to build up your understanding of the essential maths required for data analytics. It’s been designed for anybody who would like to refresh their maths knowledge or learn it in a simplified way before embarking on further data analytics training. Build your knowledge of basic statistics Explore summary statistics and learn how to make statistical predictions so that you can analyse data across any field or discipline. You’ll discover how to apply statistical methods to your data, and will practice the formula required to do that so that you can analyse and understand your data sets. Understand simple mathematical notation Mathematical notations include numbers, variables, delimiters, functions, relational symbols, and operator symbols. You’ll learn basic notation and expressions, and find out how they are applied to Excel formulas to complete simple calculations. Apply your maths to business forecasting methods Once you have a good understanding of the maths behind it, you’ll move onto forecasting future trends using your data. You’ll apply inferential maths to your data sets and calculate business metrics and KPIs to turn your new knowledge into genuine business value.


What you’ll learn

Through this learning opportunity you may acquire the compentencies demanded from organizations today. The most relevant technique within the learning opportunity that is frequently mentioned from companies is Data Analysis. The most in demand tool is Microsoft Excel. You will also find out about Applied Mathematics, a trait commonly included in job postings.

Who will benefit?

Evaluating material from this educational opportunity with nearly 10,000 data-related job descriptions, we find that those in or pursuing Data Scientist roles would benefit the most.