programme

Ecological Statistics

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Course TypeCourse CodeNo. Of Credits
Foundation ElectiveSHE2ED3112

Semester to which offered: (I/ III/ V) III semester

Course Title: Ecological Statistics

Credits: 2 Credits

Course Code (new): SHE2ED311

Type of Course: Elective: Yes Cohort MAED

Course Coordinator and Course Faculty: Dr. Suresh Babu (CC); Dr. Monica Kaushik (Visiting Faculty)

Email of course coordinator: suresh[at]aud[dot]ac[dot]in

Pre-requisites: None

Aim:

Ecological Statistics is designed as a course in ecological research design and analysis for post-graduate students who plan to undertake quantitative field-based research. It is aimed at developing skills for robust research design and collecting, handling, exploration and analysis of observational/experimental data in the area of ecosystem management. The students will learn to design simple observational studies and field experiments in the ecological context, keeping in mind the needs and assumptions of different statistical frameworks (primarily parametric and non-parametric statistics). They will also learn to develop and analyses empirical models in ecology and ecosystem management and independently carry out data exploration and statistical analysis using a basic spreadsheet programme such as Excel.

Course Content

No.

Module

1

Basics of Data and Data Description

2

Measures of Dispersion

3

Basics of Probability

4

Random Variables & Normal Probability Distribution

5

Statistical Inference

6

Statistical tests for difference in population means, tests of independence- I

7

Statistical tests for difference in population means, tests of independence- II

8

Non-parametric Statistical Methods- I

9

Non-parametric Statistical Methods- II

10

Concepts in Study design

11

Simple Regression Models

12

Choosing the Right Statistic

 

Learning Objectives:

  1. Train the students for statistical analysis in ecological research.
  2. Know the basis of types of data and their properties.
  3. Train students to ask ecological questions with the clear understanding of treatment of collected data.
  4. Ability to recognize cause-and-effect relationships, define problems, formulate hypotheses
  5. Ability to analyses and synthesize data from a variety of sources, using specialized
  6. software for quantitative and qualitative data analysis.

Course Outcomes:

On successful completion of this course, students will be able to:

  1. Understand the different types of data and choose appropriate statistical test for its treatment.
  2. Apply ecological and statistical rigor in identifying, analyzing and interpreting a problem under study
  3. Application of digital literacy to address real world questions.
  4. Used of critical thinking for selection of study variables, analytical reasoning for framing research hypothesis and reflective thinking for understanding the results.

Indicative Reading List:

  1. J. Gotelli & A.M. Ellison, 2004. A Primer of Ecological Statistics. Sinauer Associates.
  2. Weiss, P. 2005. Elementary Statistics. Addison-Wesley Publishing Company.
  3. R.R.Sokal & P.J. Rohlf. Biometry, The Principles and Practice of Statistics in Biological Research.W.H. Freeman & Co.

Assessment Methodology:

  • Assessment structure (modes and frequency of assessments) students will be assessed based on a combination of quizzes, take-home essays (one or two), independent projects and an end-semester exam.

Assessment

Weight

Description

1

30%

Quiz

2

20%

Take-home assignment

3

10%

Take home assignment/Quiz

4

10%

Field visit/ Independent project/ Take home essay

5

30%

End-semester exam