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Probability and statistical inference for economics and business
ETC2520
Synopsis
An introduction to probability and statistical inference for use in economics and business. Topics covered include random variables, moments and cumulants generating function, discrete and continuous distributions, independence, jointly distributed random variables, conditional random variables, the central limit theorem, sampling distribution, properties of estimators, confidence intervals, tests of hypotheses.
Sourced from the Monash Handbook 2026.
Quick facts
- Credit points
- 6
- Level
- 2
- Audience
- Undergraduate
- Type
- Coursework
- School
- Faculty of Business and Economics
- Faculty
- Department of Econometrics and Business Statistics
- Handbook year
- 2026
Prerequisites (8)
- Business statisticsETB1100
- Business and economic statisticsETC1000
- Business statisticsETF1100
- Introduction to statistical analysisETW1001
- Business statisticsETX1100
- Business information analysisFIT1006
- Introduction to statistical reasoningSCI1020
- Statistical methods for scienceSTA1010
What it unlocks (12)
- Principles of econometricsETC3400
- Applied insurance methodsETC3420
- Financial mathematics under uncertaintyETC3430
- Foundations of quantitative financeETC3520
- Bayesian inference and data analysisETC4541
- Applied insurance methodsETC5342
- Financial mathematics under uncertaintyETC5343
- Foundations of quantitative financeETC5352
- Bayesian inference and data analysisETC5410
- Random processes in the sciences and engineeringMTH3241
- Financial mathematicsMTH3251
- Statistics of stochastic processesMTH3260
Offerings (1)
- Second semesterClayton · BLENDED
Listed in 6 areas of study
- Actuarial studiesCore units
- Actuarial studiesCore units
- EconometricsCore units
- EconometricsAdditional econometrics units
- Mathematical economics and econometricsCore studies
- Mathematical foundations of econometricsCore units