May 26, 2020 6:36 PM
| Last Modified: Aug 18, 2020 5:11 PM
Analytics has become a very hot topic. It's used widely in a variety of business and industrial settings, and analytics has also become extremely popular in sports, in social media, and in politics.
The ability to transform data from business processes into insights is crucial in today’s competitive environment. That’s why techniques like data mining and predictive modeling are so highly valued.
Tune in to this webcast where we use a housing case study to learn how to:
1. Analyze Distributions 2. Investigate Relationships 3. Build and compare models 4. Classify Response Based on Predictors 5. Publish and Share.
Situation: you are looking for a new home and want to be able to find a home with at least seven rooms that close to schools.
Task: you need to understand what are the main factors and how they affect the median value of homes in the Boston area.
Action: you obtain real estate data and model home values using multiple linear regression and predictive model techniques.
Result: you are able to accurately predict home values and understand which variables contribute the most.
Want to learn more about Data Mining and Predictive Analytics? Why not explore the Statistical Thinking for Problem Solving e-learning course. This free on-line course is broken down into seven practical modules including Data Mining and Predictive Analytics. Each module comes with its own certificate of completion, which is especially useful for people that want to add statistical techniques to their skills development plans.
Data Mining and Predictive Modelling.jrn
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