Data Analysis with Microsoft Excel (Basic to Advance)
Â This course is designed for individuals seeking to harness the power of Microsoft Excel for data analysis and decisionmaking. Participants will delve into essential Excel functions, tools, and techniques to manipulate, visualize, and analyze data effectively. From basic data cleaning to advanced statistical analysis, this course provides a comprehensive guide to unlocking the full potential of Excel for datadriven insights.
Module 1. Introduction
Module 2. Foundational Concepts of Data Analysis

3Calculate mean and median values
Calculate mean and median values

4Analyze data using variance and standard deviation
Analyze data using variance and standard deviation

5Introducing the central limit theorem
Introducing the central limit theorem

6Analyze a population using data samples
Analyze a population using data samples

7Identify and minimize sources of error
Identify and minimize sources of error
Module 3. Visualize Data

8Group data using histograms
Group data using histograms

9Identify relationships using XY scatter charts
Identify relationships using XY scatter charts

10Visualize data using logarithmic scales
Visualize data using logarithmic scales

11Add trendlines to charts
Add trendlines to charts

12Forecast future results
Forecast future results

13Calculate running averages
Calculate running averages
Module 4. Test a Hypothesis
Module 5. Utilize Data Distributions

17Use the normal distribution
Use the normal distribution

18Use the exponential distribution
Use the exponential distribution

19Use a uniform distribution
Use a uniform distribution

20Use the binomial distribution
Use the binomial distribution

21Use the poisson distribution
Use the binomial distribution
Module 6. Measure Covariance and Correlation

22Visualize what covariance means
Visualize what covariance means

23Calculate covariance between two columns of data
Calculate covariance between two columns of data

24Calculate covariance among multiple pairs of columns
Calculate covariance among multiple pairs of columns

25Visualize what correlation means
Visualize what correlation means

26Calculate correlation between two columns of data
Calculate correlation between two columns of data

27Calculate correlation among multiple pairs of columns
Calculate correlation among multiple pairs of columns
Module 7. Perform Bayesian Analysis

28Introduce Bayesian analysis
Introduce Bayesian analysis

29Analyze a sample problem: Kahnemanâ€™s Cabs
Analyze a sample problem: Kahneman’s Cabs

30Create a classification matrix
Create a classification matrix

31Calculate Bayesian probabilities in Excel
Calculate Bayesian probabilities in Excel

32Update your Bayesian analysis
Update your Bayesian analysis