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AEM772

Statistics And Research Methods In Extension

This course provides an understanding of research methods and statistical methods for explaining and drawing inferences from research findings. It aims to equip students with the skills to approach research studies for academic purposes. The course covers research problems, hypothesis development, research design, questionnaire design, data analysis using statistical tools, and presentation of findings in various forms. It is useful for administrators and stakeholders in the agricultural sector.

About this course

Difficulty
Intermediate
Study hours
156 hours
Maths
Intermediate
Content
Theoretical, practical, case study, problem solving, research
Practical work
Yes
Before you start
  • Basic knowledge of statistics
  • Familiarity with research concepts
How it is assessed
  • Assignments
  • Tutor marked assessments
  • Final examination

One paragraph, so you can see how it reads

AEM772 · UNIT 1 RESEARCH: MEANING, IMPORTANCE AND CHARACTERISTICS

Extension refers to an out of school education services for the members of the farm family and others directly or indirectly engaged in farm production to enable them adopt improved practices in production, management, conservation and marketing.

What you should be able to do

  1. Understand research problems and formulate research questions.
  2. Develop testable hypotheses and research objectives.
  3. Design appropriate research methodologies for different research questions.
  4. Design questionnaires and collect data effectively.
  5. Analyze data using appropriate statistical tools.
  6. Present research findings in narrative, tabular, and graphical forms.
  7. Write clear and concise research reports.

What it prepares you for

Careers
  • Agricultural Extension Officer
  • Research Assistant
  • Project Manager
  • Data Analyst
  • Policy Analyst
Where it is applied
  • Agriculture
  • Rural Development
  • Government Agencies
  • Research Institutions
  • Non-Governmental Organizations
Tools
  • SPSS

Where it gets hard

The units students slow down on, and what makes each one heavy.

  • Module 3: Statistical Theory and Different Statistical Methods for Handling Data

    Unit 1: Sampling and Statistical Tools

    Understanding different sampling techniques requires careful attention to probability and representativeness, which can be challenging for students without a strong statistical background.

  • Module 4: Presentation of Research Findings in Narrative, Tabular and Graphical Forms

    Unit 1: Data Presentation

    Selecting appropriate data presentation methods (tables, charts, graphs) and interpreting their implications require analytical skills and attention to detail.

A suggested way through it

Suggested

13 weeks, about 54 hours in total. Yours will differ.

  1. Week 1Module 1: Research Problems and Statement of Hypothesis
    • Unit 1: Research: Meaning, Importance and Characteristics · 3 hours

      Define research and its characteristics.. Discuss the importance of research in the development context.. Identify different types of research..

  2. Week 2Module 1: Research Problems and Statement of Hypothesis
    • Unit 2: Selection and Formulation of a Research Problem · 3 hours

      Define a research problem and its components.. Identify factors that determine the choice of a research problem.. Describe sources of research problems.. Formulate and evaluate a research problem..

  3. Week 3Module 1: Research Problems and Statement of Hypothesis
    • Unit 3: Developing Hypothesis, Objectives and Identification of Variables · 3 hours

      Develop a hypothesis for a research problem.. List the criteria for a good hypothesis.. Describe hypothesis testing and levels of significance.. Identify types of errors in research.. Describe the different types of variables..

  4. Week 4Module 2: Research Design, Questionnaire Design and Data Collection
    • Unit 1: Research Design · 3 hours

      Define research design and its purpose.. Explain the different types of research designs, including experimental, quasi-experimental, and non-experimental designs.. Discuss the benefits of a research design..

  5. Week 5Module 2: Research Design, Questionnaire Design and Data Collection
    • Unit 2: Questionnaire Design · 3 hours

      Develop a questionnaire for social surveys.. Structure a questionnaire effectively.. Determine the steps for pre-testing a questionnaire.. Describe the process of administering a questionnaire..

  6. Week 6Module 2: Research Design, Questionnaire Design and Data Collection
    • Unit 3: Measurement and Data Collection Methods · 3 hours

      Identify the types of data required to study research problems.. Explain different data collection methods, including observation, self-reporting, and archival data.. Differentiate between quantitative and qualitative research.. Describe the different types of data (primary and secondary) and their sources..

  7. Week 7Module 3: Statistical Theory and Different Statistical Methods for Handling Data
    • Unit 1: Sampling and Statistical Tools · 4 hours

      Explain the importance of sampling in research.. Define key terms such as universe, population, sample, statistic, parameter, sampling frame, and sampling error.. Describe different types of sampling methods, including probability and non-probability sampling..

  8. Week 8Module 4: Presentation of Research Findings in Narrative, Tabular and Graphical Forms
    • Unit 1: Data Presentation · 4 hours

      Calculate and interpret measures of central tendency (mean, median, mode).. Calculate and interpret measures of dispersion (range, quartiles, mean deviation, variance, standard deviation).. Present data in narrative, tabular, and graphical forms (histograms, frequency polygons, bar charts, pie charts)..

  9. Week 9Module 4: Presentation of Research Findings in Narrative, Tabular and Graphical Forms
    • Unit 2: Report Writing · 4 hours

      Appraise methods of preparing research reports.. Identify target audiences (sponsors, administrators, policy makers, academic community) and tailor reports accordingly.. Provide a general framework for preparing a research report.. Understand the importance of accuracy and clarity in report writing..

  10. Week 10Module 1: Research Problems and Statement of Hypothesis
    • Unit 1: Research: Meaning, Importance and Characteristics · 3 hours

      Review key concepts from Module 1.. Practice formulating research problems and hypotheses.. Work on assignment 1..

    • Unit 2: Selection and Formulation of a Research Problem · 3 hours

      Review key concepts from Module 1.. Practice formulating research problems and hypotheses.. Work on assignment 1..

  11. Week 11Module 2: Research Design, Questionnaire Design and Data Collection
    • Unit 1: Research Design · 3 hours

      Review key concepts from Module 2.. Practice designing questionnaires and data collection methods.. Work on assignment 2..

    • Unit 2: Questionnaire Design · 3 hours

      Review key concepts from Module 2.. Practice designing questionnaires and data collection methods.. Work on assignment 2..

  12. Week 12Module 3: Statistical Theory and Different Statistical Methods for Handling Data
    • Unit 1: Sampling and Statistical Tools · 6 hours

      Review key concepts from Module 3.. Practice applying statistical tools to sample data.. Work on assignment 3..

  13. Week 13Module 4: Presentation of Research Findings in Narrative, Tabular and Graphical Forms
    • Unit 1: Data Presentation · 6 hours

      Review key concepts from Module 4.. Practice presenting data in different formats.. Work on assignment 4..

Preparing for the exam

What to do
  • Review all unit objectives and summaries to reinforce key concepts.
  • Practice formulating hypotheses and research questions based on different scenarios (Units 1-3).
  • Create tables and graphs from sample datasets to master data presentation techniques (Module 4).
  • Focus on understanding the application of different statistical tools and sampling methods (Module 3).
  • Practice writing concise summaries of research findings and recommendations (Unit 2, Module 4).
  • Allocate study time proportionally based on the difficulty level of each module, focusing more on Modules 3 and 4.
  • Create flashcards for key statistical terms and formulas to aid memorization.
  • Review all Tutor-Marked Assignments (TMAs) and feedback to identify areas for improvement.

Questions students ask about this course

What is AEM772 about?

This course provides an understanding of research methods and statistical methods for explaining and drawing inferences from research findings. It aims to equip students with the skills to approach research studies for academic purposes. The course covers research problems, hypothesis development, research design, questionnaire design, data analysis using statistical tools, and presentation of findings in various forms. It is useful for administrators and stakeholders in the agricultural sector.

How many units does AEM772 have?

AEM772, Statistics And Research Methods In Extension, has 9 units across 4 modules, over 128 pages of course material. You can read it one unit at a time.

How many credit units is AEM772?

AEM772 carries 2 credit units, at 700 level in Agricultural Sciences.

Is AEM772 hard?

AEM772 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical, practical, case study, problem solving and research work, and it has a practical component.

How long does AEM772 take to study?

About 156 hours of study, spread across its 9 units.

How is AEM772 assessed?

AEM772 is assessed by assignments, tutor marked assessments and final examination.

What do I need before starting AEM772?

Basic knowledge of statistics Familiarity with research concepts

What can I do with AEM772?

Agricultural Extension Officer, Research Assistant, Project Manager, Data Analyst and Policy Analyst.

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