Learning Excel: Data Analysis

Introduction

• The power of data analysis using Excel
• What you should know

1. Foundational Concepts of Data Analysis

• Calculate mean and median values
• Measure maximums, minimums, and other data characteristics
• Analyze data using variance and standard deviation
• Introducing the central limit theorem
• Analyze a population using data samples
• Identify and minimize sources of error

2. Visualize Data

• Group data using histograms
• Identify relationships using XY scatter charts
• Visualize data using logarithmic scales
• Add trendlines to charts
• Forecast future results
• Calculate running averages

3. Test a Hypothesis

• Formulate a hypothesis
• Interpret the results of your analysis
• Consider the limits of hypothesis testing

4. Utilize Data Distributions

• Use the normal distribution
• Use the exponential distribution
• Use a uniform distribution
• Use the binomial distribution
• Use the Poisson distribution

5. Measure Covariance and Correlation

• Visualize what covariance means
• Calculate covariance between two columns of data
• Calculate covariance among multiple pairs of columns
• Visualize what correlation means
• Calculate correlation between two columns of data
• Calculate correlation among multiple pairs of columns

6. Perform Bayesian Analysis

• Introduce Bayesian analysis
• Analyze a sample problem: Kahneman’s Cabs
• Create a classification matrix
• Calculate Bayesian probabilities in Excel
• Update your Bayesian analysis

Conclusion

• Further resources