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You are here:Open notes-->Iowa-State-->Econ-500-Quantitative-Methods-in-Economic-Analysis-I-iowa

**Econ 500: Quantitative Methods in Economic Analysis I iowa**

# How to study this subject

The main objective of the first part of this course is for the student to be able to comfortably
work standard problems in beginning graduate level micro and macroeconomic theory using tools
from single and multi-variable calculus, elementary matrix algebra, and classical non-linear programming.
Upon completion of the course students will be able to set up and analytically solve
constrained and unconstrained non-linear optimization problems. The student will be able to address
first and second order optimality conditions for such problems and use techniques from linear
algebra to solve implied systems of equations. The student will also be able to perform comparative
statics exercises on equilibrium or first order conditions arising from economic problems.
The main objective of the second half of this course is for the student to be able to comfortably
work standard problems in beginning mathematical statistics. Topics to be covered include basic
notions of probability, random variables, probability distributions for discrete and continuous
random variables, expected value, multivariate distributions, functions of random variables, sampling
distributions, estimation, confidence intervals, hypothesis testing, and properties of estimators.
Based on this material the students will be prepared for an M.S. level course in econometrics
and economic models of decision making under uncertainty.
The student will also demonstrate competence in using a mathematical analysis package (Mathematica)
to solve economic and statistical problems.

# Official Notes

## Mathematica | |

IntroToMathematica | Calculus |

Single Variable Optimization | Multivariate Calculus |

Multiple Variable Optimization | |

Matrix Algebra | Advanced Matrix Algebra |

Mathematica Exercise |

# Notes from other sources

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# Model question papers

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# Previous year question papers

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