SOAS University of London

Department of Economics

Quantitative techniques in economics (Dip)

Module Code:
Year of study:
Year 1
Taught in:
Full Year
The purpose of this course is to train students in the basic techniques of Mathematics and Statistics. The course is designed for both students with little prior knowledge of the topics, and students who have not studied these disciplines for a long time. By the end of the year students should be familiar with the techniques most commonly used in economic analysis and be capable of undertaking further study of advanced economic techniques. Topics include: calculus; optimisation; linear algebra; descriptive statistics; estimation; hypothesis testing; regression analysis; and index numbers.

Objectives and learning outcomes of the module

On successful completion of the course, you should be able to;

  • explain basic mathematical concepts including, but not restricted to, real numbers, rational and irrational numbers, integers and fractions, polynomials, functions and relations
  • demonstrate ability to manipulate mathematical expressions
  • explain and use cartesian coordinate space, graphs, intercepts and roots
  • demonstrate ability to solve equations and systems of equations
  • explain and use basic concepts in matrix algebra and define matrix operations including, but not restricted to, addition, subtraction, multiplication, minors, cofactors, determinants
  • use the cofactor method to find inverse matrices and use Cramer's rule to solve systems of equations 
  • explain and use exponential and logarithmic functions
  • demonstrate understanding of derivatives, rules of differentiation, higher order derivatives, their uses and applications
  • explain indefinite and definite integrals and use them to solve problems
  • demonstrate understanding of first- and second-order partial derivatives and Young's theorem
  • use the mathematical methods covered in the course to solve problems in economics
  • explain basic statistical concepts including, but not restricted to, descriptive and inferential statistics, and levels of measurement
  • demonstrate understanding and ability to use basic descriptive statistic techniques including, but not restricted to, frequency tables, histogram, and ogive
  • use the summation operator
  • demonstrate understanding of and ability to use measures of central tendency, dispersion, skewness and kurtosis
  • calculate and interpret covariance and correlation coefficient
  • explain basic concepts in probability theory including, but not restricted to, experiment, population or sample space, sample point, event, mutually exclusive, equally likely and collectively exhaustive events, random variable, discrete and continuous random variable, probability, probability distribution or probability density function (PDF), statistical independence
  • use characteristics or moments of PDF including, but not restricted to expected value, variance and standard deviation, skewness and kurtosis, covariance, coefficient of correlation, conditional and unconditional expectation
  • use population parameters and sample estimators including, but not restricted to sample mean, sample variance, sample standard deviation, sample covariance, sample correlation, sample skewness and sample kurtosis
  • demonstrate understanding of and ability to use normal distribution, chi-square, T and F distributions
  • explain the sampling distribution of an estimator (e.g. the sample mean)demonstrate understanding of and ability to use point and interval estimation and hypothesis testing
  • explain the method of ordinary least squares (OLS) and use it to estimate regression coefficients
  • interpret and critically evaluate econometric results
  • demonstrate understanding of measures of goodness of fit including their uses and limitations
  • explain the assumptions of the classical linear regression model
  • use t test on regression coefficients

Method of assessment

Assessment weighting: Exam 100%


Important notice regarding changes to programmes and modules