By Simpliv
Online
Can be taken anytime
Professional Training Course
Yes (Details)
English
$10
Course Overview
SAS Predictive Modeling - Series - 2: Linear Regression, Logistic Regression and Time Series
This course is a path of a SAS predictive modeling. This program emphasis on deep understanding of hypothesis testing using use case. You will learn a variety of statistical test with applied predictive analytics approaches using the most popular software SAS as well as strategies to know how to apply the appropriate one to your specific data and question. Participants will discover trained and best practices from the experiences of academic and industry experts. This program will help you to build a robust data science skills. This will cover the following topics:
- Build a regression model
- Check Auto correlation & Multi collinearity
- Stepwise Regression process
- Logistic Regression
- Confusion Matrix
- Time Series Forecasting
- ARIMA modeling
- Basic knowledge
- There are no formal prerequisites for this course
Who should take this course
Anyone who needs motivation to learn SAS predictive modelling.
Accreditation
Course Completion Certificate
Course content
What will you learn
- Linear Regression, Multiple Regression
- Logistic Regression
- Time Series forecasting
- Hands On Exercises using SAS
- ARIMA Modelling
- Live case studies on regression, logistic regression, time series forecasting, building ARIMA model
About Course Provider
Simpliv LLC, a platform for learning and teaching online courses. We basically focus on online learning which helps to learn business concepts, software technology to develop personal and professional goals through video library by recognized industry experts or trainers.
Why Simpliv
With the ever-evolving industry trends, there is a constant need of the professionally designed learning solutions that deliver key innovations on time and on a budget to achieve long-term success.
Simpliv understands the changing needs and allows the global learners to evaluate their technical abilities by aligning the learnings to key business objectives in order to fill the skills gaps that exist in the various business areas including IT, Marketing, Business Development, and much more.