Course Catalogue

Module: AMT202 Foundations of Statistics.

Programme: BA Economics and Population Studies

Credit Value: 12

Module Coordinator: Mr. Rinzin Namgyel

  1. General Objective

The module aims to provide basic knowledge of Statistics and analytical skills.

  1. Learning outcomes

On the completion of the module, the learners will be able to:

  • Express the scope of statistics in day to day life
  • Organize different kinds of data and represent them by various methods like tables, charts etc.
  • Evaluate various measures like central tendency, dispersion etc. and explain their properties and uses.
  • Analyze and interpret data and make conclusions.
  • Use statistical software like SPSS and Excel.
  • Apply analytical skills in decision making
  1. Learning and Teaching Approaches

The module will be delivered in 15 teaching weeks as per the following:

  • 4 hour/week of instruction/demonstration
  • 1 hours/week of supervised practical work

Assessment Written assignment 10% Lab assignments 10% Mid-term Examination 20% Final Examination 60%

  1. Subject Matter

4.1. INTRODUCTION TO STATISTICS

4.1.1. Definition and scope of Statistics, Descriptive Statistics vs. Inferential Statistics, types of data: nominal, ordinal, scalar data, Qualitative and Quantitative data, Variables: Discrete vs. Continuous variables.

4.2. DATA ORGANIZATION

4.2.1. Raw data, Ordered Array, Frequency Distribution: type and construction of frequency distribution tables, Graphical representation of frequency distribution,

4.2.2. Histogram, Frequency Polygon, Cumulative frequency curve or the Ogives.

4.3. MEASURES OF CENTRAL TENDENCY AND DISPERSION

4.3.1. Arithmetic mean and its properties,

4.3.2. Median, Mode, Relationship between Mean, Median and Mode, Geometric mean, Quartiles, Deciles and Percentiles, The Range, Quartile Deviation,

4.3.3. Mean Deviation, Variance, Properties of Variance, Standard Deviation, Application of Standard Deviation,

4.3.4. Relationship between the measures of dispersion, Coefficient of variation.

4.4. MEASURES OF SKEWNESS AND KURTOSIS

4.4.1. Pearsonian Measure of Skewness,

4.4.2. Bowley's Measure of Skewness,

4.4.3. Moment Coefficient of Skewness,

4.4.4. Moment Coefficient of Kurtosis,

4.4.5. Percentile Coefficient of Kurtosis.

4.5. ANALYSIS OF MULTIVARIATE DATA

4.5.1. Bi-variate data and scatter diagram,

4.5.2. Principle of least square and curve fitting,

4.5.3. Correlation and regression, partial and multiple correlation coefficients.

4.6. THEORY OF PROBABILITY

4.6.1. The nature of probability, some important definitions and examples, Basic rules of probability,

4.6.2. Theorems on probability (without proof).

4.7. PROBABILITY DISTRIBUTIONS

4.7.1. Random variables, Discrete probability distributions (without proof):

4.7.2. Binomial distribution, Poisson distribution, Continuous probability distributions (without proof):

4.7.3. Uniform distributions, exponential and normal distributions.

4.8. SAMPLING DISTRIBUTIONS

4.8.1. The rationale for sampling, Sample statistics,

4.8.2. Random Sampling, sampling distributions,

4.8.3. sampling distributions of the Mean, sample variance from a normal population.

4.9. HYPOTHESIS TESTING

4.9.1. The rationale for hypothesis testing, general procedure for hypothesis testing, the null and alternative hypothesis,

4.9.2. One-tailed and Two-tailed tests, Errors in hypothesis testing, Critical region, level of significance of a test.

4.10. TIME SERIES

4.10.1. Calculation of Trends using moving average linear trend by method of least square,

4.10.2. Exponential Trends (of the form (Y=abx). Shifting of trends origin. Conversion of annual trends values to monthly values. Measurement of Seasonal variation by ratio to trend method.

4.10.3. Deseasoning of the series. Forecasting.

4.11. List of Practical

  1. Statistical functions in Excel.
  2. Calculation of various measures for a given set of data using Excel.
  3. Charts and graphs in Excel
  4. Multiple correlation using Excel
  5. Regression and multiple regression in Excel
  6. Defining variables and data entry in SPSS
  7. Data manipulation in SPSS
  8. Descriptive statistics, correlation and regression using SPSS
  9. Graphs and charts using SPSS
  10. Comparison of means and interpretation of P-values using SPSS
  1. Reading List

5.1. Essential Reading

Hooda, R. P. (1994). Statistics for Business and Economics. Macmillian India Ltd. Braverman, J. D. (1978). Fundamentals of Business Statistics. New York:Academic Press Inc. KennyJ. F., and Keeping, E. S. (1974). Mathematics of Statistics, Volume 1. (3rd edn.). Affiliated East-West Press Pvt. Ltd. Freund, J. E. (2001). Mathematical Statistics. (5th edn.). PHI Mood, A. M, Graybill, F. A, and Bose,D. C. (2001). Introduction to the theory of Statistics. (3rd Edition). TMH.

Field,A. (2009). Discovering Statistics Using SPSS (Introducing Statistical Method. (3rd edn.). Sage Publications Ltd.

5.2. Additional Reading:

Walpole,R. E., Myers,R. H., Myers,S. L. and Ye, K. (2001). Probability and Statistics for Engineers and Computer Scientists. (7th edn.). Pearson Education. Murray, R.S. (1982). Theory and problems of Probability and Statistics. Schaum's outline series. Goon, A.M., Gupta, M.K., and Das, G.B. (2002). Fundamentals of Statistics-Volume I and II. (5th Revised Edition). World Press Pvt. Ltd. Sheldon, M.R. (2007). Introduction to Probability Models. (9th Edition). Academic Press.

Date: February 2013
Royal Thimphu College