Module Code and Title:        STT202 Inferential Statistics for Economics 

Programme:                          BA in Development Economics

Credit Value:                          12

Module Tutor:                       Sonal Mehta

General objective: The module introduces concepts for drawing inferences. This module will help students to use and apply appropriate inferential statistical tests to test theories, and make decisions. 

Learning outcomes – On completion of the module, students will be able to:

1. Use spreadsheets to solve problems related to probability distribution.
2. Apply probability distribution for decision making.
3. Distinguish between parameters and statistic.
4. Apply standard error to determine appropriate sample size.
5. Use an appropriate inferential statistics test.
6. Differentiate between point and interval estimates.
7. Formulate null and alternative hypotheses.
8. Perform the tests using spreadsheet.
9. Distinguish between type I and type II errors.
10. Make decisions based on tests.
11. Apply inferential statistics for analysing secondary data for making predictions.
12. Apply the inferential tools for conducting research. 

Learning and Teaching Approach: 

Assessment Approach:

The task is for each student to answer the questions on probability distributions using spreadsheets and interpret them

2    Identification of the probability distribution. 

4    Output based on the formula

4    Clearly communicate the analysis of results

Two written tests will be conducted (worth 10 marks each), comprise 45 min duration and covering Unit II for one test and Unit III for another. The tests will contain 5 questions (3 on the conceptual understanding and 2 on problem solving).

The assignment will be based on two sample hypothesis testing and regression. It will assess the ability of students to individually use the data, to identify the test related to the variables picked, arrange the data on spreadsheet, create outputs and provide an in-depth analysis. The assignment should use at least three types of tests.

4    Choice of variables and the tests

4    Outputs

7    Analysis (Include the hypothesis, testing, decision and recommendation)

Students will take a written exam of 1.5-hr duration covering topics up to the mid-point of the semester. The exam will comprise structured questions like MCQ, fill-in-the-blanks, matching, definition, as well as open-ended essay questions.

Students will take a written exam of 2.5-hr duration encompassing all the subject matter covered in the semester. This assessment is comprehensive and summative in nature, and will comprise structured questions like MCQ, fill-in-the-blanks, matching, definition, as well as open-ended essay questions.

Overview of assessment approaches and marks

Pre-requisites: STT101 Descriptive Statistics for Economics

Subject matter:

Use spreadsheets to create outputs and emphasise on data interpretation.

1. Unit I: Probability Distribution (outputs, diagrams and interpretations)
   1. Characteristics, finding probabilities using spreadsheets, diagrams and application
   2. Discrete random variables 
      1. Binomial distribution 
      2. Poisson distribution
   3. Continuous random variables: normal and standard normal distribution
2. Unit II: Sampling Distribution of means and proportions
   1. Sample and parameter
   2. Unbiased and efficient estimators
   3. Central Limit theorem of means and proportions
   4. Sample size and standard error: definitions and the relationship between sample size and standard error
   5. Point and interval estimates
   6. Confidence interval, choosing a confidence level 
3. Unit III: Statistical Decision Theory 
   1. Statistical hypothesis formulation: null hypothesis and alternative hypothesis
   2. Type I and type II errors: meaning, implications and methods of reducing type I error
   3. Level of significance: .01, .05 and .1
   4. Two-tailed and one-tailed tests: graphical presentation
   5. P value for hypothesis test: meaning, computer output
   6. Decision rule- test of hypothesis
   7. One sample and two sample hypothesis testing for proportions
4. Unit IV: Two sample hypothesis testing
   1. Hypothesis formulation, choosing the level of significance, arranging data and creating an output on spreadsheet, decision making and recommendation.
   2. T test: independent and paired samples (nominal and ratio level data)
   3. ANOVA: One factor and two factor (nominal and ratio level data)
   4. Chi Square Test of Independence (both nominal level data)
5. Unit V: Regression
   1. Correlation: correlation and causation
   2. Scatter plot diagram
   3. Pearson coefficient of correlation (ratio level data)
   4. Probable error
   5. Rank correlation (ordinal level data)
   6. Coefficient of determination
   7. Simple - regression: priori, hypothesis testing, reporting outputs, regression equation and interpretations of the non-standardised beta coefficients (both ratio level data)

Reading List:

Essential Reading

Doane, D. & Seward, L. (2020). Applied Statistics in Business and Economics. McGraw-Hills/Irwin.

Newbold, P., Carlson, W. & Thorne, B. (2019). Statistics for Business and Economics. Pearson Education. 

Larsen, R.J. & Marx, M.L. (2011). An Introduction to Mathematical Statistics and its Applications. Prentice Hall.

Spiegel M.L. & Stephens, L. J. (2007). Statistics, Schaum Outline Series. McGraw Hills. 

Additional Reading

Thukral,J.K.( 2012). Business Statistics. Taxmann Publications Private Limited.

 Levin, R. R., Rubin, S. D., Siddiqui, H. M., & Rastogi, S. (2021). Statistics for Management. Pearson.

Date: June, 2022