Lynda.com – Data Analysis Fundamentals with Excel 2015
English | Size: 267.62 MB
Category: Tutorial
Microsoft Excel is an important tool for information workers that design and perform data analysis. This course provides an overview of the fundamentals, from performing common calculations to conducting Bayesian analysis with Excel. Author Curt Frye starts with the foundational concepts, including an introduction to the central limit theorem, and then shows how to visualize data, relationships, and future results with Excel’s histograms, graphs, and charts. He also covers testing hypotheses, modeling different data distributions, and calculating the covariance and correlation between data sets. The course closes with a look at calculating Bayesian probabilities in Excel.
Introduction
Welcome
What you should know
Using the exercise files
1. Foundational Concepts of Data Analysis
Calculating mean and median values
Measuring maximums, minimums, and other data characteristics
Analyzing data using variance and standard deviation
Introducing the central limit theorem
Analyzing a population using data samples
Identifying and minimizing sources of error
2. Visualizing Data
Grouping data using histograms
Identifying relationships using XY scatter charts
Visualizing data using logarithmic scales
Adding trendlines to charts
Forecasting future results
Calculating running averages
3. Testing a Hypothesis
Formulating a hypothesis
Interpreting the results of your analysis
Considering the limits of hypothesis testing
4. Utilizing Data Distributions
Using the normal distribution
Using the exponential distribution
Using a uniform distribution
Using the binomial distribution
Using the Poisson distribution
5. Measuring Covariance and Correlation
Visualizing what covariance means
Calculating covariance between two columns of data
Calculating covariance among multiple pairs of columns
Visualizing what correlation means
Calculating correlation between two columns of data
Calculating correlation among multiple pairs of columns
6. Performing Bayesian Analysis
Introducing Bayesian analysis
Analyzing a sample problem: Kahneman’s Cabs
Creating a classification matrix
Calculating Bayesian probabilities in Excel
Updating your Bayesian analysis
Conclusion
Further resources
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