Notes from IIT Madras online degree course - Statistics for Data Science I

Part -1


  • Create, download, manipulate and analyze data sets.

  • Describe data using numerical summaries and visual representations.

  • Translate real word problems into probability models.

  • Describe and apply the properties of the binomial distribution and normal distribution.

  • Frame questions that can be answered from data in terms of variables and cases.

  • Estimate chance by applying laws of probability.

  • Calculate expectation and variance of a random variable.

Probability Model : A probability model is a mathematical representation of a random phenomenon. It is defined by its sample space, events within the sample space and probabilities associated with each events. - ref

Sample Space : The sample space S for a probability model is the set of all possible outcomes. -ref

Binomial distribution:

Normal distribution:

Variables and cases:

Laws of probability:

Expectation and variance of a random variable:

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