DAYS 2, 3, 4

Data Analytics

In Foundations of Data Analytics, participants learn how to categorize data and data sets, provide probabilities for events and use decision trees with probabilities to choose courses of action, describe a data set using descriptive statistics, construct exploratory visualizations to identify patterns and analyze time-series data, explore large data sets through pivot tables, measure the degree of correlation between two variables, use multiple linear regression for prediction, and express forecasts using ranges and report results of data analytics efforts.



  • Overview and Learning Objectives

Mining Data for Insight

  • Data-Driven Analysis Process
  • Data Categories

Exploring Data Through Visualization

  • Visualizing Categorical Data
  • Visualizing Numeric Data

Essential Concepts of Probability

  • Concept of Probability
  • Determining Probability
  • Empirical Probability Distributions
  • Expected Value

Decision Trees

Describing Data Through Statistics

  • Statistical Analysis
  • Descriptive Statistics
  • Outliers
  • Interval Estimation

Analyzing Large Data Sets

  • Creating a Pivot Table
  • Adding Slicers

Evaluating Correlations

  • Concept of Correlation
  • Evaluating Correlations
  • Calculating the Pearson Moment Correlation
  • Calculating the Spearman Rank Correlation

Making Forecasts Using Predictive Analytics

  • Forecasting Strategies
  • Delphi
  • Simple Linear Regression
  • Multiple Regression

Evaluating Differences Between Means

  • Hypothesis Testing
  • Applying a t-Test
  • Applying a z-Test
  • Using an ANOVA
  • Limitations of Testing

Communicating Analysis Results

  • Report Structure
  • Explanatory Visualizations

Data Analytics Summary

Practical Application and Demonstrations

The Data Analytics portion of the program features several demonstrations, 16 hands-on exercises, examples, and formal discussions. Participants gain in-depth practice using a variety of real-world data sets.

Comprehensive Learning Assessment

Participant materials include a learning assessment comprised of twenty-six multiple choice questions.


Participants work in groups to complete a comprehensive analysis of a sales data set, planning their analysis effort and communicating their results.

Data Visualization Presentation Prep

Using a real-world financial data set provided or a data set from their work environment, each participant prepares a 5-minute presentation, which includes up to three slides and a narrative memo that explains their conclusions. The presentation will be used on Day 5.