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Applied Statistical Modelling & Data Science with SAS

person icon Nkosingimele Ngcobo

4.4

Applied Statistical Modelling & Data Science with SAS

Hands on Linear Regression, Logistic Regression, Cluster Analysis, Principal Component Analysis, Factor Analysis, Backward, Forward & Stepwise Model Selections

updated on icon Updated on May, 2024

language icon Language - English

person icon Nkosingimele Ngcobo

English [CC]

category icon Teaching & Academics,Statistical Modelling

Lectures -46

Resources -11

Duration -3.5 hours

4.4

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Course Description

*Looking for a course that well explain Statistical Models & Data Science algorithms using SAS*

Do you want to learn how to use SAS for regression analysis?

Are you starting your SAS journey?

Are you looking for a course that teaches you how to well interpret statistics p-values, hypothesis tests as well as Applied Statistical Modelling?

If you are that person that you are about to enroll in the best course to guide you!

Your Instructor has more than 3 years of SAS experience, deep knowledge of Statistical modelling, Data Analysis, as well as Data Science. You will enjoy this course. It includes lot of practical knowledge on how to perform statistical tests.

Why learn SAS?

SAS jobs ! 

Try to search for “SAS Jobs” online. Your search is sure to turn up many current job listings that require a variety of SAS expertise. Since, SAS emerges as a key research data analysis tool, it is in demand in the market. Every company is looking for SAS resources.

SAS is fun !

It is fun learning SAS. It provides easy way to access multiple applications. It relies on user-written scripts or “programs” that are processed when requested to know what to do. Because it is a script-based application, the key to being successful using SAS is learning the rules and tricks of writing scripts. It works with large data and generate graphs and report.

Data Analysis

SAS is versatile and powerful enough for data analysis. SAS is flexible, with a variety of input and output formats. It has numerous procedures for descriptive, inferential, and forecasting types of statistical analyses. Because the SAS System is an integrated system with similar architecture shared by modules or products, once you master one module, you can easily transfer the knowledge to other modules.

By the end of this course you will be able to:

  • Use SAS libraries to access data

  • Manipulate data using sas if statements

  • Use sas loops

  • Understand the difference between Statistical modelling and Machine Learning

  • Perform Regression Analysis using PROC REG & PROC LOGISTIC

  • Select model with Backward, Forward & Stepwise method selection

  • Perform Cluster Analysis

  • Understand Principal Component Analysis and when to use it

  • Understand Factor Analysis and when to use it

The course will help you implement statistical analysis and interpret the results.

After the end of the course you will be able to make data driven decisions.

Don't miss this opportunity of continuous learning.

Goals

What will you learn in this course:

  • You will be able to interpret all the SAS output
  • You will be able to interpret models such as the regression model and Cluster Analysis
  • You will be able to interpret the Odds ratios
  • You will be able to interpret the Principal Components & Factors
  • You will be able to tell the story from the SAS output

Prerequisites

What are the prerequisites for this course?

  • No SAS experience the course will cover the Basics of SAS
  • SAS profile for using SAS onDemand for Academics
  • A desire to learn
Applied Statistical Modelling & Data Science with SAS

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction To the Course
1 Lectures
  • play icon Introduction to the Course 05:04 05:04
SAS onDemand for Academics
1 Lectures
Tutorialspoint
SAS Programming for Beginners
19 Lectures
Tutorialspoint
Statistical Modelling vs Machine Learning
1 Lectures
Tutorialspoint
Linear Regression using SAS
7 Lectures
Tutorialspoint
Logistic Regression using SAS
4 Lectures
Tutorialspoint
Model Selection Algorithms
6 Lectures
Tutorialspoint
Cluster Analysis
3 Lectures
Tutorialspoint
Principal Component Analysis
2 Lectures
Tutorialspoint
Factor Analysis
2 Lectures
Tutorialspoint

Instructor Details

Nkosingimele Ngcobo

Nkosingimele Ngcobo

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