The Course deals with simple tools and techniques, which will help a student in data collection, presentation, analysis and drawing inferences about various statistical hypotheses. The students are expected to formulate problems in economic theory and learn simple solutions with one or two variables.
Course Outcomes: The students will be able to
1 Compare and contrast various types of data.
2 Select and estimate measures of central tendency and dispersion based on specific economic problems.
3 Apply various sampling methods based on the context and need of the study.
4 Apply the rules of probability theory and able to identify which approach is used in a given scenario.
5 Understand the concept of Bayes theorem with its economic applications.
6 Use correlation analysis on different types of data sets to find the degree of association.
7 Estimate cause and effect relationship through regression analysis
8 Able to select a good estimator in the process of estimation.
9 Perform hypothesis testing using z test t-test, chi-square and f-tests and interpret the results.
Course Content:
UNIT I
Typical data sets arising in economics, Qualitative, Quantitative, Income, Expenditure, Time
Series and Panel data. Major sources of data sets: Census, Government agencies, e-resources,
Graphical representations, Measures of Central tendency, Measures of dispersion. Sampling
methods: Census, simple random sample with and without replacement, stratified sampling
methods.
UNIT II
Probability theory I: Laws of addition and multiplication; Independence of events,
Conditional probability and concept of independence; Bayes theorem with applications;
UNIT III
Probability theory II: Random variable; Discrete and Continuous random variables;
Probability density functions; Binomial, Poisson and Normal distributions, their mean and
variance, graphs of normal density functions.
UNIT IV
Correlation: Pearson‘s product moment and Spearman‘s rank correlation-their properties;
Partial and multiple correlations, linear and nonlinear regression.
UNIT V
Estimation: Concept of an estimator and its sampling distribution: Desirable properties of a
good estimator; Point and Interval estimation.
UNIT VI
Testing of statistical hypotheses – Formulation of the problem; Null and alternative
hypothesis; Type 1 and Type 2 errors, Goodness of fit; Confidence intervals and level of
significance; Hypothesis testing for means, variance, regression coefficients based on
standard normal, t, Chi-square and F tests.
Text Books:
1. Lee, C. F., Lee, J. C. and Lee, A. C. Statistics for Business and Financial Economics. (2000), World
Scientific, Singapore.
2. Monga, G S, Mathematics and Statistics for Economics ( 2005), Vikas Publishing House
Reference Books:
1. Black, Ken. Business Statistics. (2004), John Wiley & Sons.
2. Taylor, S. Business Statistics. (2001), Palgrave.
3. Bluman, A. G. Elementary Statistics. (2009), McGraw-Hill
- Teacher: Department of Economics