Hands-On Statistical Predictive Modeling

Hands-On Statistical Predictive Modeling

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.

Data Science at your fingertips: build statistical predictive models to make predictions based on data

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What you will learn

• Differentiate between various types of predictive models
• Master linear regression
• Explore the results of logistic regression

Rating: 3.65

Level: Intermediate Level

Duration: 3 hours

Instructor: Packt Publishing