SAS Predictive Modeling

SAS Predictive Modeling, available at $29.99, has an average rating of 4.05, with 35 lectures, based on 30 reviews, and has 157 subscribers.

You will learn about Linear Regression, Multiple Regression Logistic Regression Time Series forecasting ARIMA Modelling Live case studies on regression, logistic regression, time series forecasting, building ARIMA model. Hands On Exercises using SAS Correlation Co-efficient ODDS & ODDS ratio BOX JENKINS technology Importance of business analytics Multi Collinearity and Auto Corelation Concordant,Discordant and Tied Pairs Variance Inflation Factor Durbin-Watson test Confusion Matrix Stationarity & Non-Stationarity Components of time series Importing of data sets in SAS This course is ideal for individuals who are Aspiring Analytics Professionals or Next generation data scientist or Visionary predictive modeler or SAS programmer It is particularly useful for Aspiring Analytics Professionals or Next generation data scientist or Visionary predictive modeler or SAS programmer.

Enroll now: SAS Predictive Modeling

Summary

Title: SAS Predictive Modeling

Price: $29.99

Average Rating: 4.05

Number of Lectures: 35

Number of Published Lectures: 35

Number of Curriculum Items: 35

Number of Published Curriculum Objects: 35

Original Price: ₹1,199

Quality Status: approved

Status: Live

What You Will Learn

Linear Regression, Multiple Regression
Logistic Regression
Time Series forecasting
ARIMA Modelling
Live case studies on regression, logistic regression, time series forecasting, building ARIMA model.
Hands On Exercises using SAS
Correlation Co-efficient
ODDS & ODDS ratio
BOX JENKINS technology
Importance of business analytics
Multi Collinearity and Auto Corelation
Concordant,Discordant and Tied Pairs
Variance Inflation Factor
Durbin-Watson test
Confusion Matrix
Stationarity & Non-Stationarity
Components of time series
Importing of data sets in SAS

Who Should Attend

Aspiring Analytics Professionals
Next generation data scientist
Visionary predictive modeler
SAS programmer

Target Audiences

Aspiring Analytics Professionals
Next generation data scientist
Visionary predictive modeler
SAS programmer

This course covers a range of introductory statistical topics and uses SAS software to carry out analysis. Emphasis placed on the interpretation of the results. It covers the skills required to assemble analysis flow diagrams using the rich tool set and predictive modeling. Ready-to-use procedures handle a wide range of statistical techniques.

Learn how to

•generate descriptive statistics and explore data with graphs

•perform linear regression and assess the assumptions

•use diagnostic statistics to identify potential outliers in multiple regression

•fit a multiple logistic regression model

•modify data for better analysis results

•build and understand predictive models such as regression models

•compare and explain complex models generate and use score code

SAS is the global leader in analytics. Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS (Statistical Analysis System) is a programming language for analyzing statistical data and data visualization. SAS Programming Completion is perfect for the beginner but also digs into more intermediate topics. SAS is entry point to Data Science, Machine Learning, Artificial Intelligence. Here in this course, you will learn three module of SAS BASE SAS, ADVANCED SAS, PREDICTIVE MODELING.

Impress employers by your skill, and showcase your SAS certificate as a pride. Future-proof your career with this industry-relevant curriculum. Course Overview SAS is the global leader in analytics. Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS (Statistical Analysis System) is a programming language for analyzing statistical data and data visualization. SAS Programming Completion is perfect for the beginner but also digs into more intermediate topics. SAS is entry point to Data Science, Machine Learning, and Artificial Intelligence. Here in this course, you will learn three modules of SAS BASE SAS, ADVANCED SAS, and PREDICTIVE MODELING. Who can join? Any graduate with knowledge of basic computing.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Business Analytics

Chapter 2: Bussiness Analytics

Lecture 1: Categories of Business Analytics

Chapter 3: Installation of SAS

Lecture 1: Installation of SAS

Chapter 4: Importing CSV file in SAS

Lecture 1: Importing CSV dataset in SAS

Chapter 5: Linear Regression

Lecture 1: Concept of Linear Regression

Lecture 2: Assumptions of Classical Linear Regression Model

Lecture 3: Concept of Multi collinearinty and Auto correlation

Chapter 6: Linear Regression-Case Study & Practical session

Lecture 1: Case study discussion and Dataset descriptions

Lecture 2: Linear Regression Practical Session – Part – 1

Lecture 3: Linear Regression Practical Session – Part – 2

Lecture 4: Linear Regression Practical Session – Part – 3

Lecture 5: Linear Regression Practical Session – Part – 4

Lecture 6: Linear Regression Practical Session – Part – 5

Chapter 7: Logistic Regression

Lecture 1: Concept of Logistic Regression

Lecture 2: Assumptions of Logistic Regression

Lecture 3: ODDS AND ODDS Ratio

Lecture 4: Concept of Concordant, Discordant and Tied Pairs

Lecture 5: Setting the probability level

Lecture 6: Detail description of Confusion Matrix

Chapter 8: Logistic Regression- Case Study & Practical

Lecture 1: Case Discussion and Data set Description of Logistic Regression

Lecture 2: Logistic Regression Practical part- 1

Lecture 3: Logistic Regression Practical part- 2

Lecture 4: Logistic Regression Practical part- 3

Lecture 5: Logistic Regression Practical part- 4

Lecture 6: Logistic Regression Practical part- 5

Chapter 9: Time Series Forecasting

Lecture 1: Concept of time series

Lecture 2: Components of Time Series

Lecture 3: Smoothing Techniques

Lecture 4: Stationarity and non-stationarity of Time Series Data

Lecture 5: ARIMA Modelling

Lecture 6: BOX JENKINS Technology

Chapter 10: Time Series – Case Study & Practical Session

Lecture 1: Case Study and Data set discussion of Time Series

Lecture 2: Time Series Practical Session Part- 1

Lecture 3: Time Series Practical Session Part- 2

Lecture 4: Time Series Practical Session Part- 3

Instructors

Handson System
Develop your Hands-On Skill

Rating Distribution

1 stars: 4 votes
2 stars: 3 votes
3 stars: 7 votes
4 stars: 5 votes
5 stars: 11 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?

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