Data Science at your fingertips: build statistical predictive models to make predictions based on data
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.
Differentiate between various types of predictive models
Master linear regression
Explore the results of logistic regression
3 Lectures
6 Lectures
4 Lectures
Packt are an established, trusted, and innovative global technical learning publisher, founded in Birmingham, UK with over eighteen years experience delivering rich premium content from ground-breaking authors and lecturers on a wide range of emerging and established technologies for professional development.Packt’s purpose is to help technology professionals advance their knowledge and support the growth of new technologies by publishing vital...
This course is a great refresher of regression techniques for those of us who may have already studied it in college but now, years later, need to be working wih these techniques in a professional setting. It is NOT, however, a good course for someone looking to learn regression from scratch.
yes so far
It's good. I was hoping to use IBM SPSS Modeler, but I'm okay with this. I can use my own software package.
Example and explanation related to it is understandable and
I started to understand how predictive models are built and what to consider when building the model
So far, so good. I am worried as more than 40% of the course is covered, how can I know about predictive modelling within the remaining 60%.
This was a really good course for someone looking to get an introduction to statistics and has a little bit of basic knowledge in statistics. It helped me understand the data better and also to make a decision on which method fits into which kind of data.
Its getting interesting and fantastic!
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Allen T.
R, Python, EXCEL - who the hell uses SPSS anymore