# Data Driven Design (Virtual)

#### Course description

This intensive, hands-on workshop provides participants with several key techniques for quantitative data analysis. After understanding the data analysis process, participants will investigate the shape of a data set using descriptive statistics and exploratory visualizations. In addition, participants will learn how to measure the degree of correlation between two variables, build predictive models for forecasting trends using regression, determine confidence levels and range forecasts, and evaluate the predictive power of a model. Furthermore, the workshops shows participants how to determine whether the difference between means of two data samples is statistically significant using the t-test. Finally, participants will learn how to explain analysis findings in a research report.

#### Who should attend

Individuals who will benefit from this course include business analysts; data analysts; and research analysts.

#### What you will achieve

• Learn about the process of data analysis using analytics and exploratory visualizations.
• Evaluate the degree of dispersion and central tendency of a data set by calculating descriptive statistics including mean, standard deviation, median, variance, range, and mode.
• Use exploratory visualizations including scatter plots, column charts, and line graphs to identify insights and patterns.
• Measure the degree of correlation between two variables.
• Use linear regression to forecast trend and evaluate the degree of fit of the regression model.
• Determine whether the difference in means between two data samples is statistically significant.
• Detect outliers and how to manage them.
• Write reports summarizing results of a data analysis effort.
• Perform data analytics and visualizations in Excel.

#### What you will learn

##### Course Outline
###### Module 1: Mining Data for Insight
• Data-Driven Analysis Process
• Exercise: Brainstorm Challenges
• Data Categories
• Exercise: Start Analysis Process
###### Module 2: Exploring Data Through Visualization
• Visualizing Categorical Data
• Tabular Summaries
• Graphing Data
• Visualizing Numeric Data
• Exercise: Exploratory Visualization
###### Module 3: Characterizing Data Through Statistics
• Statistical Analysis
• Descriptive Statistics
• Exercise: Calculate Descriptive Statistics
• Correlation
• Calculating Correlation
• Prediction with Regression
• Assessing Correlation
• Exercise: Correlation Analysis
###### Module 4: Making Forecasts Using Predictive Analytics
• Forecasting Strategies
• Weighted Average Models
• Exercise: Forecasting with Weighted Averages
• Discussion: Trends and the Weighted Average Model
• Time Series Regression Models
• Linear and Non-Linear Regression Models
• Exercise: Forecasting with Linear Regression
• Model Evaluation
• MAD and MSE
• Exercise: Model Evaluation
• Prediction Confidence
• Exercise: Evaluate Prediction Confidence and Calculate the 95% Forecast Range
###### Module 5: Comparing Means
• Applying the t-test
• Exercise: Practicing the t-test
• Exercise: Perform a t-test
###### Module 6: Communicating Analysis Results
• Creating a Report
• Instructor-Led Walkthrough: Research Report
• Exercise: Review of Brainstorm Challenges

For an updated schedule for this course, please call us at 1.800.288.7246 (US) or +1.978.649.8200.