# Econ1203

**Topics:**Normal distribution, Probability theory, Random variable

**Pages:**2 (321 words)

**Published:**June 11, 2012

Progress Report:

1.

* Descriptive statistics (Emphasis of course so far)

* What are the key features of data?

* How can we best describe these features so that analysis is informative * Inferential statistics (Emphasis of course to come)

* Extracting information about population parameters on basis of sample statistics * What does a sample mean tell us about a population mean? * Typically only alternative because difficult or impossible to determine population mean * Need more foundations before covering later in course 2.

* In SIA admission distributions

* Assign probabilities to qualitative characteristics

* Public or private patient

* In auditing example

* Probabilities assigned to quantitative characteristics * Probabilities of number of overdue accounts

* Topic of random variables

* Need to introduce theoretical distributions that are useful in representing/modeling actual data * Initially discrete distribution

* Binomial

3.

* Have now discussed random variables & probability distributions * Have introduced theoretical distributions that are useful in representing/modelling actual data * These cover both discrete distributions (binomial) & continuous (uniform) * Now ready to discuss the normal distribution

* This distribution plays a pivotal role in statistics (both modelling and inference) * This is the classic bell-shaped distribution

4.

* Have introduced a selection of distributions

* Binomial, uniform & normal

* These enable us to model a range of phenomena

* Normal also plays a key role in theory of estimation * Have introduced the basics of estimation

* Need to understand better the notion of a point estimator as a rv * Leads us to sampling distributions

* Role of Normal distribution in theory of estimation comes through the...

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