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Statistical Data Analysis with SAS

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Statistical Data Analysis with SAS, available at $74.99, has an average rating of 4.22, with 48 lectures, 12 quizzes, based on 703 reviews, and has 6312 subscribers.

You will learn about Learn SAS and be confident on your data analysis skills Learn to accomplish a task with various SAS techniques, with tons of examples and quizes Learn step-by-step statistical analysis from descriptive statistics, hypothesis testing to linear regression Learn data importing with different techniques for variuos type of data Use many important functions to make SAS programming easy Advanced concepts of meta data: formats and informats, labels, lengths, etc. Learn the manipulation techniques to prepare the data and make the data analysis-ready Perform dataset manipulations: subsetting, transposition, etc. Be able to properly interpret the results from statistical analyses I am giving out one course for free. Check out the last lecture after you enroll This course is ideal for individuals who are Anyone from other programming fields that are interested in SAS or Anyone with no SAS background or Anyone who wants to understand the workflow in SAS It is particularly useful for Anyone from other programming fields that are interested in SAS or Anyone with no SAS background or Anyone who wants to understand the workflow in SAS.

Enroll now: Statistical Data Analysis with SAS

Summary

Title: Statistical Data Analysis with SAS

Price: $74.99

Average Rating: 4.22

Number of Lectures: 48

Number of Quizzes: 12

Number of Published Lectures: 46

Number of Published Quizzes: 12

Number of Curriculum Items: 74

Number of Published Curriculum Objects: 72

Original Price: $59.99

Quality Status: approved

Status: Live

What You Will Learn

  • Learn SAS and be confident on your data analysis skills
  • Learn to accomplish a task with various SAS techniques, with tons of examples and quizes
  • Learn step-by-step statistical analysis from descriptive statistics, hypothesis testing to linear regression
  • Learn data importing with different techniques for variuos type of data
  • Use many important functions to make SAS programming easy
  • Advanced concepts of meta data: formats and informats, labels, lengths, etc.
  • Learn the manipulation techniques to prepare the data and make the data analysis-ready
  • Perform dataset manipulations: subsetting, transposition, etc.
  • Be able to properly interpret the results from statistical analyses
  • I am giving out one course for free. Check out the last lecture after you enroll

Who Should Attend

  • Anyone from other programming fields that are interested in SAS
  • Anyone with no SAS background
  • Anyone who wants to understand the workflow in SAS

Target Audiences

  • Anyone from other programming fields that are interested in SAS
  • Anyone with no SAS background
  • Anyone who wants to understand the workflow in SAS

COURSE ABSTRACT

This course aims to provide a comprehensive introduction to the SAS analytic software for Windows. Through a mixture of lectures and in-class examples, quizzes, and take-home assignments, students will gain experience using the SAS system for data manipulation, management and analysis. You will also expect A LOT of extracurricular learning materials for self-pace learning, treat it as a BONUS! Emphasis will be placed on the skills and techniques necessary for efficient data manipulation, management and analysis. It is designed for students with little to no background with SAS, and an understanding of the basic statistical concepts. This will be an excellent choice for your first SAS introduction course for your data analysis career.

Plus, you will get a FREE course – SAS Data Issue Handling and Good Programming Practice (check out in the bonus lecture)!!!

WHAT DO I EXPECT?

  • A comprehensive course design from SAS basics to statistical analysis

  • Many in-class examples, exercises and take-home assignment

  • Master various techniques for data importing

  • Solid understanding of variable attributes, and learn various character/numeric functions

  • IF-THEN/ELSE statements

  • Do loop and counter variables

  • Master DATA step with Concatenation, Merge, etc.

  • Exposed to several useful PROC step (PRINT, SORT, TRANSPOSE, etc.).

  • Descriptive statistics procedures (MEANS, UNIVARIATE, FREQ)

  • Hypothesis testing (UNIVARIATE, TTEST, ANOVA)

  • Correlations (CORR)

  • Regression (REG)

PREREQUISITE COURSES AND KNOWLEDGE:

  • No SAS background required;

  • Basic knowledge of statistics is preferred.

Course Curriculum

Chapter 1: L1 – Course Introduction

Lecture 1: L1 – How to Get the Most out of the Course

Lecture 2: L2 – SAS OnDemand Registration

Lecture 3: L3 – Why use SAS (you may skip this introductory lecture)

Chapter 2: Understanding the Workflow

Lecture 1: L4 – Overview

Lecture 2: L4 – The Workflow

Lecture 3: L4 – Ask Questions Wisely to Assist Project Planning

Lecture 4: L4 – SAS Basics

Lecture 5: L4 – Data Importing – Instream data and Proc Import

Lecture 6: L4 – Import Wizard for SAS 9.x

Lecture 7: L4 – Data Importing in SAS Studio

Lecture 8: L4 – Bring in Data from Pre-existing SAS Dataset and Create Permanent Dataset

Lecture 9: Section Summary in Text

Chapter 3: Data Manipulation – Naming Convention and IF THEN/ELSE Statement

Lecture 1: L5 – Overview

Lecture 2: L5 – Naming Convention and Variable Types

Lecture 3: L5 – IF THEN/ELSE Statement

Lecture 4: L5 – Keep and Drop Variables

Lecture 5: Section Summary in Text

Chapter 4: Data Manipulation – SAS Functions and DO Loop

Lecture 1: L6 – Overview

Lecture 2: L6 – SAS Functions

Lecture 3: L6 – DO Loop

Lecture 4: Section Summary in Text

Chapter 5: Dataset Manipulation – Subset and Append

Lecture 1: L7 – Overview

Lecture 2: L7 – Subset

Lecture 3: L7 – Concatenation (Append)

Lecture 4: Section Summary in Text

Chapter 6: Dataset Manipulation – Merge and Transposition

Lecture 1: L8 – Overview

Lecture 2: L8 – Merge

Lecture 3: L8 – Transpose

Lecture 4: Section Summary in Text

Chapter 7: Descriptive Statistics – Frequency and Univariate Analysis

Lecture 1: L9 – Overview

Lecture 2: L9 – Explore the Data Using PROC PRINT and CONTENTS Procedures

Lecture 3: L9 – Descriptive Statistics

Lecture 4: Section Summary in Text

Chapter 8: One, Two Sample T-Test and ANOVA

Lecture 1: L10 – Overview and Introduction to Hypothesis Testing

Lecture 2: L10 – One Sample T-Test

Lecture 3: L10 – Two Sample T-Test

Lecture 4: L10 – 3+ Sample ANOVA

Lecture 5: L10 – Non-parametric Analysis

Lecture 6: Section Summary in Text

Chapter 9: Linear Regression – Predicting the Outcome

Lecture 1: L11 – Overview

Lecture 2: L11 – Linear Regression

Lecture 3: L11 – Dummy Variable

Lecture 4: Thank You and Please Leave Your Comments for Future Improvement of the Course!

Lecture 5: Section Summary in Text

Chapter 10: Bonus section: Data Visualization using SAS

Lecture 1: Bonus Lecture: How to Draw Statistical Graphs using SAS

Chapter 11: Source Codes

Lecture 1: Download source code of the course

Instructors

Rating Distribution

  • 1 stars: 9 votes
  • 2 stars: 15 votes
  • 3 stars: 96 votes
  • 4 stars: 250 votes
  • 5 stars: 333 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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