by Jesus Salcedo | Released September 2018 | ISBN: 9781789611618

Data Science at your fingertips: build statistical predictive models to make predictions based on dataAbout This VideoMake your data earn its keep by developing efficient models to predict future results accuratelyMaster the data science forces that drive your company and make the most of these forthcoming opportunitiesApply statistical predictive modeling to help your organization make better business decisionsIn DetailPredicting 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.All data files for this course are available on GitHub at https://github.com/PacktPublishing/Hands-On-Statistical-Predictive-Modeling Show and hide more

1. Chapter 1 : Getting Started with Predictive Modeling
   • The Course Overview 00:03:24
   • Predictive Modeling – Purpose, Examples, and Types 00:03:06
   • Characteristics and Real-World Examples of Statistical Predictive Models 00:03:34
2. Chapter 2 : Making Predictions with Linear Regression
   • Understanding Linear Regression Theory 00:03:30
   • Using Simple Linear Regression to Predict Salary 00:10:03
   • Using Multiple Linear Regression to Predict Salary 00:12:19
   • Using Stepwise Linear Regression to Predict Waste 00:13:50
   • Testing Linear Regression’s Assumptions 00:19:17
   • Incorporating Categorical Variables (Dummy Variables) 00:11:51
3. Chapter 3 : Determining Likelihoods Using Logistic Regression
   • Understanding Logistic Regression Theory 00:08:38
   • Using Binary Logistic Regression to Predict Birth Weight 00:19:12
   • Using Multinomial Logistic Regression to Predict Credit Risk 00:18:11
   • Testing Logistic Regression’s Assumptions 00:08:31
4. Chapter 4 : Classifying Cases with Discriminant Analysis
   • Understanding Discriminant Analysis Theory 00:08:00
   • Using Two-Group Discriminant Analysis to Predict Likelihood of Purchase 00:15:41
   • Using Multi-Group Discriminant Analysis to Predict Risky Behavior 00:10:40
   • Testing Discriminant Analysis Assumptions 00:06:39
   • Comparing Logistic Regression and Discriminant Analysis 00:07:24
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