Statistical Analysis in MS Excel

Introduction 

Due to its popularity and versatility, Microsoft Excel has become an essential tool for basic quantitative analysis. The aim of the training is to familiarize you with the possibilities offered by Microsoft Excel in carrying out a statistical analysis. We will focus on descriptive statistics, statistical inference, regression model, series decomposition methods and time series forecasting. You will first learn the theoretical concept of each method, and then how to use it. We will show you many possible implementations and examples and you will practice it in Excel via numerous exercises. You will learn how to use statistical functions and add-ins like Analysis ToolPak. 

Who is this training for? 

This training is addressed at those who want to gain or expand their knowledge of statistical analysis methods. We will show you how to use those methods in Microsoft Excel. You may be particularly interested in this training if you are a: 

• Student 
• Analyst 
• Consultant 
• Manager 
• Statistician 
  
  What will I learn? 
  
  After completing the training, participants will be able to: 

• Perform operations on data using advanced features of Microsoft Excel 
• Use Analysis Toolpak Add-in 
• Use Statistical Analysis methods in Excel 
• Interpret and understand the results of your analysis 

• Course outline 

1. Introduction – Excel as a Statistical Analysis Tool  
   • Importing data to Microsoft Excel 
   • Grouping, filtering and sorting data, subtotals 
   • Pivot Tables 
   • Functions and Array functions 
   • Advanced Microsoft Excel features: date and time functions, mathematical, statistical, text and logical functions, search, lookup and match 
   • Analysis ToolPak Add-in 
   • Exercises 
2. Descriptive statistics  
   • What is descriptive statistics? 
   • Empirical distribution 
   • Numerical characteristics of empirical distribution 
   • Exercises 
3. Statistical Inference  
   • What is statistical inference? 
   • Distribution and confidence intervals for the mean 
   • The idea of ​​hypothesis testing 
   • Tests of significance for the mean and variance 
   • Tests of significance for the two means and two variances 
   • Tests of significance for more than two means (ANOVA) and more than two variances 
   • Chi-squared test 
   • Contingency tables and chi-square test of independence 
   • Exercises 
4. Analysis of correlation and regression  
   • Correlation coefficient 
   • Linear regression model 
   • Statistical verification of linear regression 
   • Exercises 
5. Time series analysis and forecasting  
   • Charts 
   • Transformations 
   • Time Series decomposition 
   • Forecasting methods 
   • Forecast accuracy