Hands-On Statistical Predictive Modeling

Hands-On Statistical Predictive Modeling, available at $44.99, has an average rating of 3.95, with 18 lectures, based on 46 reviews, and has 275 subscribers.

You will learn about Differentiate between various types of predictive models Master linear regression Explore the results of logistic regression Understand when to use discriminant analysis Understand the inner workings of your models Maximize your productivity by analyzing your models and interpreting their accuracy in a well-organized manner This course is ideal for individuals who are If you are a statistical or data mining professional and want to add statistical predictive modeling to your skill set, then this is the ideal course for you. It is particularly useful for If you are a statistical or data mining professional and want to add statistical predictive modeling to your skill set, then this is the ideal course for you.

Enroll now: Hands-On Statistical Predictive Modeling

Summary

Title: Hands-On Statistical Predictive Modeling

Price: $44.99

Average Rating: 3.95

Number of Lectures: 18

Number of Published Lectures: 18

Number of Curriculum Items: 18

Number of Published Curriculum Objects: 18

Original Price: $109.99

Quality Status: approved

Status: Live

What You Will Learn

Differentiate between various types of predictive models
Master linear regression
Explore the results of logistic regression
Understand when to use discriminant analysis
Understand the inner workings of your models
Maximize your productivity by analyzing your models and interpreting their accuracy in a well-organized manner

Who Should Attend

If you are a statistical or data mining professional and want to add statistical predictive modeling to your skill set, then this is the ideal course for you.

Target Audiences

If you are a statistical or data mining professional and want to add statistical predictive modeling to your skill set, then this is the ideal course for you.

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.

Course Curriculum

Chapter 1: Getting Started with Predictive Modeling

Lecture 1: The Course Overview

Lecture 2: Predictive Modeling – Purpose, Examples, and Types

Lecture 3: Characteristics and Real-World Examples of Statistical Predictive Models

Chapter 2: Making Predictions with Linear Regression

Lecture 1: Understanding Linear Regression Theory

Lecture 2: Using Simple Linear Regression to Predict Salary

Lecture 3: Using Multiple Linear Regression to Predict Salary

Lecture 4: Using Stepwise Linear Regression to Predict Waste

Lecture 5: Testing Linear Regression’s Assumptions

Lecture 6: Incorporating Categorical Variables (Dummy Variables)

Chapter 3: Determining Likelihoods Using Logistic Regression

Lecture 1: Understanding Logistic Regression Theory

Lecture 2: Using Binary Logistic Regression to Predict Birth Weight

Lecture 3: Using Multinomial Logistic Regression to Predict Credit Risk

Lecture 4: Testing Logistic Regression’s Assumptions

Chapter 4: Classifying Cases with Discriminant Analysis

Lecture 1: Understanding Discriminant Analysis Theory

Lecture 2: Using Two-Group Discriminant Analysis to Predict Likelihood of Purchase

Lecture 3: Using Multi-Group Discriminant Analysis to Predict Risky Behavior

Lecture 4: Testing Discriminant Analysis Assumptions

Lecture 5: Comparing Logistic Regression and Discriminant Analysis

Instructors

Packt Publishing
Tech Knowledge in Motion

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 7 votes
4 stars: 23 votes
5 stars: 14 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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