Statistics and Data Analysis with Excel

Advanced data analysis skills are what separate professionals who report on data from those who draw confident, evidence-based conclusions from it. This course takes your statistical toolkit to the highest level, equipping you with the techniques needed to analyse multiple datasets simultaneously, model complex cause-and-effect relationships, incorporate qualitative variables into quantitative models, and generate rigorous forecasts — all in Microsoft Excel. You'll begin with ANOVA — Analysis of Variance — learning how to compare three or more groups of data using one-way, two-way with replication, and two-way without replication tests. You'll then extend your regression skills into multiple regression, building models with several predictors, generating forecasts, and running the statistical tests that validate your results. Module 3 introduces dummy variable regression — a powerful technique for incorporating categorical data (such as region, product type, or yes/no variables) directly into a quantitative regression model. The course closes with advanced charting and forecasting, covering Bubble Charts for three-variable visualisation, Exponential Smoothing, and Excel's Forecast Sheet, including dashboard design principles and business cycle analysis. Who this is for: Data analysts, business analysts, and research professionals who have completed the Intermediate course in this series and are ready to apply the most demanding statistical techniques available in Excel. Join over 1 million professionals who have advanced their careers with our highly-rated Excel courses. Whether you’re looking to boost your employability, enhance your current role, or simply elevate your Excel skills, this course will provide you with the knowledge and tools to stand out in the competitive job market.

Data drives decisions in every field — business, health, science, sports, and beyond. This course gives you the statistical tools to make sense of data, spot patterns, and present findings that inform real-world decisions. You'll work through both branches of statistics in a structured, practical sequence. Descriptive statistics help you summarise and describe data — covering measures of centredness like mean, median, and mode, and measures of spread including variance, standard deviation, and boxplots. You'll then move to inferential statistics, where you'll use the normal distribution, the Central Limit Theorem, and hypothesis testing to draw conclusions about whole populations from sample data. Everything is applied in Microsoft Excel, so you're not just learning theory — you're building working spreadsheet models. Each module includes downloadable workbooks, toolbox summary references, and both practice and graded assignments to reinforce your skills step by step. The course closes with a final assignment that brings all four modules together, giving you the opportunity to demonstrate your full range of statistical and analytical skills in a single integrated Excel model. Who this is for: Students, business professionals, and anyone who works with data and wants to understand it more rigorously. No prior statistics or Excel expertise is required.