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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