Statistics for MBA/ Business statistics explained by example

Statistics Made Easy by Excel Simulations. Master most important concepts of introductory statistics through simulation

Description

Most of the students of MBA (Master of business administration program) / machine learning program / computer science program hate the introductory statistics / business statistics course. The reason is that most of the instructor explain the concept in such a way that students are hardly able to relate to concept with real life situation. Hence the course becomes a nightmare for students and they look forward for just completion of semester to  get rid of the same.

That’s why this course has been prepared through simulation and real life examples.

This course covers the entire syllabus of most of the business statistics / introductory statistics course of MBA (Master of Business administration) program. The explanations are so simple and intuitive that you will learn statistics for life and will love the subject. 

I recommend you to explore the course.

What is the course about? 

                        This course promises that students will 

• Learn the statistics in a simple and interesting way

• Know the business scenarios, where it is applied

• See the demonstration of important concepts (simulations) in MS Excel

• Practice it in MS Excel to cement the learning

• Get confidence to answer questions on statistics

• Be ready to do more advance course like logistic regression etc.

  Course Material 

• The course comprises of primarily video lectures.

• All Excel file used in the course are available for download.

• The complete content of the course is available to download in PDF format.

  How long the course should take? 

                 It should take approximately 25 hours for good grasp on the subject. 

  Why take the course 

• To understand statistics with ease

• Get crystal clear understanding of applicability

• Understand the subject with the context

• See the simulation before learning the theory

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