Menu
  • LOGIN
  • No products in the cart.

Business Analytics with R Course Description

This Business Analytics with R program will provide an overview of the business analytics, data exploration techniques, and introduction level predictive modeling that is widely used in business. This program is an entirely hands-on approach to data analysis using R software.

R is an open source programming language consists of several standard statistical tests, analyses and models.

Business Analytics enables the organizations to make better decisions and develop business insights using extensive use of data, statistical methods, predictive models, and fact-based management. Analytical skills are essential not only for data scientists but also for all decision makers.

 

Business Analytics with R Course Learning Outcomes;

  • Optimize business situations that involve whole numbers, such as employees to deploy.
  • Optimize business decisions that take multiple input variables to predict between two possible outputs.
  • Model decisions under a variety of future uncertain states, depending on the decision maker’s proneness or aversion to risks.
  • Compute correlation where, at first glance, there seem to be none – correlation between data points in a time series.
  • Compute the regression model for time series data that has correlation within itself.
  • Optimize business situations where two variables do not move in a linear fashion.
  • Test hypothesis for experiments involving different treatments.
  • Model continuous outcomes that depend on more than one input variable.
  • Group data points dynamically based on the similarities among the members of each group.

 

Business Analytics with R Training – Suggested Audience

This training is aimed at professionals who want to learn data analytics skills. Suggested attendees based on our past programs are:

  • Software Engineers
  • Data analytics professionals
  • Data Analysts
  • Business Analysts
  • Research professionals

 

Business Analytics with R Training – Prerequisites

Knowledge of programming concepts and familiarity with Excel is desirable but not mandatory.

 

Business Analytics with R Training In-house/Corporate Training

If you have a group of 5-6 participants, apply for in-house training. For commercials please send us an email with group size to hello@pincorps.com

Course Curriculum

1. Introduction to Business Analytics and R Programming
Get introduced to the basics, evolution, and scope of business analytics.  Details 00:00:00
Learn R and data manipulation, functions and data visualizations in R. Details 00:00:00
2. Statistics and Data Exploration
Understand the various types and applications of statistics as well as the types of data and statistics variables.  Details 00:00:00
Master the art of making informed decisions using summary statistics. Details 00:00:00
3. Random Variable and Normal Distribution and Hypothesis Testing
Learn random variables, expected value, probability distribution, standard deviation, variance and the types of distributions.  Details 00:00:00
Learn how to state null and alternative hypotheses, understanding Type-I and Type-II errors. Conduct one-sided hypothesis test for population. Details 00:00:00
4. Correlation and Regression
Apply correlation, strength of linear association, least-squares or regression line, linear regression model Details 00:00:00
Gain expertise in multiple regression, regression diagnostics and detection of collinearity: simple signs. Details 00:00:00
5. Model creation and selection
Learn about fitting of model, diagnostic plots, comparison of models, cross-validation, variable selection, relative importance and Box-Cox transformations. Details 00:00:00
6. Logistic Regression
Master binary response regression model and linear regression output of proposed model.  Details 00:00:00
Work on the various problems with linear probability model, logistic function, logistic regression & its interpretation and the various odds ratio, goodness of fit measures and confusion matrix. Details 00:00:00

Course Reviews

N.A

ratings
  • 5 stars0
  • 4 stars0
  • 3 stars0
  • 2 stars0
  • 1 stars0

No Reviews found for this course.

X