
This video provides an overview of the entire course.
This video aims to explain the predictive modeling.
Understand the purpose of predictive modeling
Learn more about predictive modeling with the help of examples
Explore the types of predictive modeling
This video aims to demonstrate the characteristics with the help of real-world examples.
Explains the characteristics of statistical predictive models
Explore the different statistical predictive models
Demonstrate with the help of a real world example
This video aims to explain the Linear Regression theory.
Understand the purpose of Linear Regression
Explore the hypotheses for Linear Regression
Demonstrate with the help of a real world example
This video aims to explain the use of simple Linear Regression to predict salary.
Explains the simple Linear Regression
Demonstrate with the help of a real world example
This video aims to explain the use of multiple Linear Regression to predict salary.
Explains the multiple Linear Regression
Demonstrate with the help of a real world example
This video aims to demonstrate an example using stepwise Linear Regression to predict waste.
Understand correlations
Explore an example using the Venn diagram
Demonstrate with the help of a real world example
This video aims to explore different Linear Regression’s assumptions.
Understand the different Linear Regression’s assumptions
Explore the different Linear Regression’s assumptions using examples
This video aims to explain how to incorporate categorical variables the need of dummy variables.
Understand the need of dummy variables
Demonstrate with the help of a real world example
This video aims to explain the Logistic regression theory.
Learn the purpose of Logistic regression
Understand the basics and goals of Logistic regression
Explore the Logistic regression theory and formulas
This video aims to explain the binary Logistic regression to predict birth weight.
Learn about the binary Logistic regression
Demonstrate with the help of a real world example
This video aims to explain the multinomial Logistic regression to predict credit risk.
Learn about multinomial Logistic regression
Explore multinomial Logistic regression with the help of formulas
Demonstrate with the help of a real world example
This video aims to explore all the assumptions made for testing Logistic regression.
Learn and understand the assumptions
Demonstrate with the help of a real world example
This video aims to create a complete understanding for Discriminant Analysis theory.
Learn the purpose and basics of Discriminant Analysis
Explore the Discriminant Analysis theory and formulas
This video aims to demonstrate a real world example to predict likelihood of purchase using two-group Discriminant Analysis.
Demonstrate with the help of a real world example
Understand the Discriminant Analysis equation
Learn about the Discriminant Analysis interpretation
This video aims to demonstrate a real world example to predict risky behavior using multi-group Discriminant Analysis.
Demonstrate with the help of a real world example
Understand the Discriminant Analysis equation
Learn about the Discriminant Analysis interpretation
This video aims to explore all the assumptions made for testing Discriminant Analysis.
Learn about the testing Discriminant Analysis assumptions
Demonstrate with the help of a real world example
This video aims to demonstrate the comparison between Logistic regression and Discriminant Analysis with the help of an example.
Demonstrate an example for similarities
Demonstrate an example for differences
Predicting future trends can be the difference between profit and loss for competitive enterprises. Most businesses state that poor data quality leads to bad decision-making. Further, the predictive analytics market is expected to grow by 22% by 2020. As this technology hits the mainstream, now is the time to consider which predictive modeling techniques will produce the best results for your organization.
Hands-On Statistical Predictive Modeling gives you everything you need to bring the power of statistical predictive models into your statistical or data mining work. However, without the right predictive modeling techniques, analytics projects are unlikely to provide actionable insights. This course will show you how these core algorithms underpin the accuracy and relevance of statistical results and drive competitive differentiation. You will be able to anticipate customer behavior, take steps to cultivate customer loyalty, and capture a greater share of the market. You will be aware of the data science forces shaping your future economy and will have mastered how best to use and seize these coming opportunities.
By the end of this course, you will be able to elevate your company's analytics know-how to enhance its decision-making skills, cost efficiency, and profitability. You will also be able to put these skills to use in your upcoming statistical and data mining projects.
About the Author
Jesus Salcedo has a Ph.D. in Psychometrics from Fordham University. He is an independent statistical and data-mining consultant and has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist; he has written numerous SPSS training courses and trained thousands of users.