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Analysis Before Model Building: SAS and R codes side by side
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Published 6/2023
Created by Ami Traore
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 37 Lectures ( 7h 3m ) | Size: 3.4 GB

SAS codes and R scripts. All the codes you need to prepare, explore and analyze your data before modeling

[b]What you'll learn[/b]
Importing and Combining Files
Exploring and Cleaning data
Distribution of Individual Variables
Pairwise Associations Between Numeric Variables
Pairwise Associations Between Categorical and Numeric Variables
Pairwise Associations Between Categorical Variables

[b]Requirements[/b]
At least basic knowledge in one programming language (R or SAS)

[b]Description[/b]
Basic knowledge in at least one programming language (SAS or R) is a prerequisite for this course. It is a nice start for any programmer or analyst interested in learning more than one programming language.Both SAS Studio and RStudio are open sources available online, instructions are provided in the course to facilitate the installation (R and RStudio), and access (SAS Studio) on student's computer.The course offers a great opportunity to review sample codes used for data cleaning, data exploration and data analysis in SAS and in R.The course is based on a hands-on project and engages you in step-by-step activities through a series of lectures and demos.Students will review procedures and functions in SAS and in R useful for data visualization and for the assessment of candidate variables in future models.The course includes downloadable sample codes of SAS and R that students can copy, paste and run in the appropriate software.The Demos in the course last beyond 10 minutes in many instances so to provide enough time to students to comprehend the codes and appreciate how they vary from SAS Studio to RStudio.The PowerPoint presentations in the videos are enhanced with annotations describing procedures, functions and options in SAS Studio, and functions in RStudio.

Who this course is for
Entry level programmer

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