date_range Débute le 8 septembre 2016
event_note Se termine le 3 novembre 2016
list 5 séquences
assignment Niveau : Introductif
chat_bubble_outline Langue : Anglais
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Les infos clés

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En résumé

Statistics is a versatile discipline that has revolutionized the fields of business, engineering, medicine and pure sciences. This course is Part 1 of a 4-part series on Business Statistics, and is ideal for learners who wish to enroll in business programs. The first two courses cover topics in Descriptive Statistics, whereas the next two courses focus on Inferential Statistics.

Spreadsheets containing real data from diverse areas such as economics, finance and HR drive much of our discussions.  

In Part 1, we shall be exploring multiple ways to describe these datasets, numerically as well as visually. Throughout, we shall embrace a problem-based approach to understanding the material: the primary reason to pick up a tool or a technique will be to solve a problem. Our course makes judicious use of tools.

In Part 2, we shall take up a few datasets that have over a million rows, which makes it impossible to analyze using a spreadsheet. This is a natural setting for R, an advanced statistical programming platform. The courses incorporate helpful tutorials to get learners acquainted with both the mechanisms. Parts 3 and 4 are dedicated to Inferential Statistics. In Part 3, we begin by exploring the benefits of random sampling, and apply the Central Limit Theorem to arrive at confidence intervals for important population parameters. We also learn how to formulate hypotheses for business data, and resolve them with the testing framework that we establish. Along the way, we shall compare two or more populations and draw inferences with a set of statistical tests.

You will learn all these concepts with the help of various demonstrations, which show real-life application of the concepts related to business situations.

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Le programme

  • To download data from prominent Internet sources
  • To analyse a dataset using spreadsheet software
  • To pose pertinent business questions of datasets and to answer them
  • To clean up a dataset and summarize the data using single point measures of centrality and dispersion
  • To classify variables by scale and aggregate them with pivot tables
  • To build an understanding of probability, joint and marginal probability, conditional probability
  • To apply Bayes rule to invert probabilities on a decision tree
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Les intervenants

  • Shankar Venkatagiri
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Le concepteur

Indian Institute of Management, Bangalore
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La plateforme

EdX est une plateforme d'apprentissage en ligne (dite FLOT ou MOOC). Elle héberge et met gratuitement à disposition des cours en ligne de niveau universitaire à travers le monde entier. Elle mène également des recherches sur l'apprentissage en ligne et la façon dont les utilisateurs utilisent celle-ci. Elle est à but non lucratif et la plateforme utilise un logiciel open source.

EdX a été fondée par le Massachusetts Institute of Technology et par l'université Harvard en mai 2012. En 2014, environ 50 écoles, associations et organisations internationales offrent ou projettent d'offrir des cours sur EdX. En juillet 2014, elle avait plus de 2,5 millions d'utilisateurs suivant plus de 200 cours en ligne.

Les deux universités américaines qui financent la plateforme ont investi 60 millions USD dans son développement. La plateforme France Université Numérique utilise la technologie openedX, supportée par Google.

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