This course teaches you how to use the IML procedure via the programming language. You benefit from this course if you plan to use SAS/IML for manipulating matrices, simulating data, writing custom statistical analyses, or working with R.
DurationThis course teaches you how to use the IML procedure via the programming language. You benefit from this course if you plan to use SAS/IML for manipulating matrices, simulating data, writing custom statistical analyses, or working with R. The programs in this course require SAS/IML 12.3 or later to run.
Prerequisites
Before attending this course, you should:;
Have completed the SAS Programming 1: Essentials course or understand the material within.
Have completed the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course or understand the material within.
Possess an understanding of elementary matrix algebra or linear algebra concepts and operations, including matrix dimensions, matrix addition and multiplication, matrix inversion, and scalars.
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This course sets out the foundational skills and knowledge to introduce learners to data analysis using Excel functions and formulae and creation of data visualisation to generate business insights by identifying trends and patterns.
In this course, participants will be introduced to the basic concepts of Data Analytics. This knowledge could help us understand our data better, and in many contexts enable us to make better decisions.
With the rise of data analytics applications, it is crucial to learn how to leverage on data analytics to extract useful information from large amounts of data and integrate business expertise with knowledge of data, to derive actionable insights.
Power BI is a business analytics service provided by Microsoft that allows users to visualize and analyze data from a wide range of sources.
Learn exciting ways to add value to your data. We’ve carefully tailored our courses to feature all important aspects of Excel and Power BI’s Query Editor. This includes learning how to build speedy, automated data cleaning workflows.Â
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