This is an introduction to quantitative methods in geography with a focus on, but not limited to, statistical techniques. Through this course, students will develop an understanding of basic concepts, reasoning and procedures in quantitative methods used in geography. This course also helps develop skills to present and analyze statistical data in research. These techniques are related to a broader context of geographical applications and research. Basic excel is required for completing the assignments and the mini‐project.
- To develop "statistical literacy," a working understanding of statistics that can help in critically evaluating data-driven results in the discipline of geography (or ecology, etc...).
- To obtain a rich set of statistical tools for data analysis, with an understanding of the how to choose appropriate tools and implement them in statistical software.
- To enable you to confidently and carefully interpret the results of data analyses and clearly communicate those results.
- To provide practical experience in using real sets of data addressing meaningful research questions.
At the end of the course, students will be able to:
- Explain the role of quantitative information in geographic research and applications.
- Demonstrate an understanding of basic descriptive statistics and regression methods as they apply to problem solving in Geography.
- Perform basic data manipulation, statistical calculations and graphical presentation by hand, and using computer spreadsheets or statistical software (e.g. Excel, SPSS).
- Evaluate the roles of probability theory and sampling distributions in drawing inferences about populations based on samples.
- Identify when and where statistical procedures are appropriate.
2. Quantitative revolution and its impact on Geography
3. Parametric and non-parametric statistics
4. Nature of geographical data and measurement scales.
5. Data summarizing techniques: theory of central tendency, dispersion, and variability.
6. Time Series: graphs, growth and decline, index numbers, logarithmic scales, trends and fluctuations, components of time series.
7. Methods of drawing trend lines for linear and exponential series scatter diagrams, standard errors and probability, correlation and regression.
8. Quantitative models in Geography
1. Haring, L. L. (2002) Introduction to Scientific Geographic Research, Oxford: ECB.
2. Levin, J. (2006) Elementary Statistics in Social Research, Pearson, New Delhi.
- Walpole, R. E., & Myers, R. H. (2012). Probability & statistics for engineers & scientists. Pearson Education Limited.
- Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2016). Statistics for business & economics. Nelson Education.
- Sessional: 20 (Assignment 10, Attendance 05, Quiz 05)
- Mid-Term Exam: 30
- Final-Term Exam: 50
10:00 am to 11:00 am
09:00 am to 10:00 am
09:00 am to 10:00 am
Commencement of Classes October 12, 2020
Mid Term Examination December 14-18, 2020
Final Term Examination February 08-12, 2021
Declaration of Result February 19, 2021