Analytics with R:03 - Business Analytics
EduCBA
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Description
Data Science and Machine Learning with R (Part #3) – Business Analytics with R
In the recent years R has become the widely used programming language for computational statistics, visualization and data science. R is used by many statisticians, scientists and data analysts to find a solution for their problem in various fields. R is used as the most important tool for business analytics in companies like Google, Facebook and LinkedIn. R contains every data analytics techniques at your fingertips. It helps you to perform some of the most commonly performed tasks by business analysts with the help of its 4000 packages.
Through this course we will learn about business analytics using r, normal pdf, what is normal, not normal, sat example, example- birth weights, dnorm, pnorm, qnorm, understanding estimation, properties of good estimators, central limit theorem, kurtosis, constructing central limit theorem, confidence intervals for the mean, confidence intervals examples, computer lab example and t-distribution.
Target Customers:This course will be useful for students and Data analysts and people from Analytics domain. It will also be useful for people who wanted to learn business analytics using R.Pre-Requisites:
The pre requisites for this course include basic knowledge of statistics. Knowledge in any other programming language is an added advantage but not a must.
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This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
