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Multiple Variate Analysis
4.5
Beginner level
1.5 learning hrs
Instructor:
Mr. Anirudh Rao
About this course
Data analysis is a domain that has a key role to play in almost all of the domains it involves in. To think of it, there are many ways to go about performing data analysis as there are numerous types of data that need to be collected, handled, and analyzed respectively. Multivariate analysis is important in today’s world of IT as it has the capability to pick up multiple points of data for observation at once and eventually even supply the same to a Machine Learning model to further amplify the effect of analysis and solve things quicker. Keeping this in mind, we here at Great Learning have come up with this course on multivariate analysis to help you completely grasp all of the content and get upto speed with all the foundationals that are required to proceed in this domain.
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Course outline
Introduction to Data Analysis
Summary
This comprehensive module on Organizational Behaviour, covers the concept, importance, elements, levels, types, and objectives of the field. It provides a deep understanding of the subject to enhance interpersonal and communication skills and create a positive work environment.
Multivariate Analysis Course Agenda
Understanding Multivariate Analysis
Various MVA Techniques
Get access to the complete curriculum once you enroll in the course
4.5
Our course instructor
Mr. Anirudh Rao
Machine Learning Expert
Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What is multivariate analysis and how does it work?
In the realm of data analytics, we use various techniques to get desired outcomes in different situations. Multiple variant analysis is a range of statistical techniques that are used to undergo data analysis. This involves taking multiple measurements and then studying their relationship among different experiments to understand the outcomes better. Multivariate analysis was first started by Wishart in 1928, and since then, it has found its application in the fields of biology, education, and psychology.
What is an example of multivariate analysis?
In the marketing industry, professionals often have to run a lot of techniques to undergo market research and analysis. When dealing with more than one variable, multivariate techniques help in reaching robust conclusions and add clarity to the research. Let us take an example of marketing research where a company wants to understand the impact of variable ‘sales’ on the other variable ‘advertisement expenditure.
We will apply the multivariate technique to understand the relation between these two variables and the impact of one on another. One way to achieve this is by making a list of sales through various advertising channels and how each advertising channel impacts the overall sales. The data and findings can be worked into a model to find certain patterns or correlations to understand the impact of these variables on various outcomes. This will help the company to make informed decisions and set an advertising budget accordingly for driving more sales.
What is the goal of multivariate analysis?
The goals of multivariate analysis include :
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The primary aim of doing multivariate analysis is to establish a correlation between multiple variables and predict outcomes.
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These techniques help in sorting out data and simplifying it as much as possible. This helps in making informed decisions and drawing solid interpretations without altering the data structure.
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Multiple variables used in multivariate techniques help significantly in the sorting of data. Different variables are grouped depending on their key features.
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Multivariate analysis also helps to test and conduct statistical hypotheses. This helps us determine whether our assumptions are correct or not.
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