Statistics and data analysis with Excel
What you'll learn
- Basic and advanced univariate statistics in Excel
- Hypothesis tests (Student's t test, chi-square, F-test, Welch test), t-table and z-table
- Confidence intervals for mean value and proportions
- Correlation coefficient and linear regression forecast
- Outlier identification
- Database operations
- Pivot tables
- Basic knowledge of Excel
In this practical course, we are going to focus on how to perform advanced statistical calculations and data analysis using Microsoft Excel.
Excel is a very used tool in several companies and has very powerful data analysis capabilities that can be used by data analysts and marketing experts. Even if you work with a lot of statistics you'd be surprised at how valuable Excel is for calculating hypothesis tests and the most common metrics you can calculate on a dataset. There are several basic and advanced functions you can use to get the best from your data and that's why Excel is a very useful tool for anybody who needs to crunch data and perform analyses of various kinds.
This course can be attended by both data analysts and marketing experts who need to work with data and surveys.
With this course, you are going to learn:
Univariate descriptive analysis (mean, standard deviation, skewness, quantiles, percentiles, IQR)
Advanced univariate analysis (outlier detection, rolling measures)
Linear correlation and regression forecasting
Hypothesis tests (Student's t-test, chi-square test, F-test, Welch test)
t tables and z tables
Database operations and conditional operations
All the video lessons of this course start with a brief introduction and end with a practical example in Excel. All the Excel spreadsheets are attached to each lesson and can be downloaded.
Who this course is for:
- Data analysts
- Marketing experts
- Data scientists
My name is Gianluca Malato, I'm Italian and have a Master's Degree cum laude in Theoretical Physics of disordered systems at "La Sapienza" University of Rome.
I'm a Data Scientist who has been working for years in the banking and insurance sector. I have extensive experience in software programming and project management and I have been dealing with data analysis and machine learning in the corporate environment for several years.
I am also skilled in data analysis (e.g. relational databases and SQL language), numerical algorithms (e.g. ODE integration, optimization algorithtms) and simulation (e.g. Monte Carlo techniques).
I've written many articles about Machine Learning, R and Python and I've been a Top Writer on Medium in Artificial Intelligence category.