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AGR501

Statistics And Research Methodology

This course introduces students to the fundamental principles of research methodology and statistical analysis in Agricultural Science. It covers defining research problems, hypothesis testing, research design, data collection methods, and statistical theories. Students will learn to prepare questionnaires, analyze data using various statistical methods, and present research findings in tabular and graphical forms. The course aims to equip students with the skills to conduct novel research and apply statistical methodologies in agricultural contexts.

About this course

Difficulty
Intermediate
Study hours
300 hours
Maths
Intermediate
Content
Theoretical, practical, case study
Practical work
Yes
Before you start
  • Basic Statistics
  • Introduction to Agricultural Science
How it is assessed
  • Assignments
  • Tutor marked assignments
  • Final examination

One paragraph, so you can see how it reads

AGR501 · UNIT 2: RESEARCH HYPOTHESIS

A hypothesis is a tentative explanation for certain behaviors, phenomena, or events that have occurred or will occur. The hypothesis states the researcher’s expectations concerning the relationship between the variables in the research problem as outlined in the first module. Formulating a research hypothesis requires research questions and generation of operational definitions for variables.

What you should be able to do

  1. Define a research problem and formulate a hypothesis.
  2. Explain the principles of research design and data collection.
  3. Apply statistical theories and methods to analyze agricultural data.
  4. Present research findings in tabular and graphical forms.
  5. Evaluate and validate measurements in agricultural research.

What it prepares you for

Careers
  • Agricultural Researcher
  • Animal Scientist
  • Crop Scientist
  • Data Analyst
  • Research Consultant
Where it is applied
  • Agricultural Research Institutes
  • Animal Production Companies
  • Crop Production Companies
  • Government Agricultural Agencies
  • Consulting Firms
Tools
  • SPSS
  • SAS
  • GENSTAT
  • R

Where it gets hard

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

  • Module 4: Measurement and Evaluation

    Unit 2: Sources of Error in Measurement

    Understanding the different sources of error in measurement requires careful attention to detail and potential biases in data collection.

  • Module 6: Statistical Methods

    Unit 3: Computational Techniques of Experimental Design

    Computational techniques of experimental designs require a strong foundation in statistical theory and the ability to apply formulas correctly.

A suggested way through it

Suggested

13 weeks, about 64 hours in total. Yours will differ.

  1. Week 1Module 1: Definition of Research Problem and its Necessities
    • Unit 1: Research Problem and Selecting the Problem · 2 hours

      Define research problem and identify its components.. Discuss the characteristics of a research problem.. Outline the procedures for selecting a research problem..

    • Unit 2: Research Hypothesis · 2 hours

      Define the concept of hypothesis testing.. Differentiate between null and alternate hypotheses.. Understand Type I and Type II errors..

  2. Week 2Module 1: Definition of Research Problem and its Necessities
    • Unit 3: Procedure for Hypothesis Testing · 2 hours

      Explain the procedure for hypothesis testing.. Learn to select a significance level.. Decide on the appropriate distribution to use..

    • Unit 4: Advantages and Limitations of Hypothesis Testing · 2 hours

      Discuss the advantages of hypothesis testing.. Understand the limitations of hypothesis testing.. Learn to set a criterion for acceptance or rejection..

  3. Week 3Module 2: Principles of Research Design
    • Unit 1: Meaning of Research Design · 2 hours

      Explain the meaning of research design.. Discuss the types of research design.. Understand the need for research design..

    • Unit 2: Concept Relating to Research Design · 2 hours

      Explain the concepts of dependent and independent variables.. Understand extraneous variables and control.. Define research hypothesis and treatment..

  4. Week 4Module 2: Principles of Research Design
    • Unit 3: Basic principles of Experimental Design · 2 hours

      State the principles of experimental design.. Differentiate between formal and informal experimental design.. Understand replication, randomization, and local control..

    • Unit 4: Criteria for Defining a Problem · 2 hours

      Set out the criteria for defining a research problem.. Explain the sources of research problems.. Differentiate between limitation and delimitation..

  5. Week 5Module 3: Questionnaire Preparation and Collection of Data
    • Unit 1: Collection of Primary Data · 2 hours

      Determine the methods of primary data collection.. State the procedures of data collection through questionnaires.. Discuss the advantages and disadvantages of observation and interview methods..

    • Unit 2: Collection of Secondary Data · 2 hours

      Highlight the characteristics of secondary data.. Identify sources of secondary data.. Understand the reliability, suitability, and adequacy of secondary data..

  6. Week 6Module 4: Measurement and Evaluation
    • Unit 3: Guidelines for Constructing Questionnaire · 2 hours

      Construct the steps in questionnaire formulation.. Understand the process of questionnaire design.. Learn to formulate effective questions..

    • Unit 1: Measurement in Research and in Scale · 2 hours

      Explain the concept of measurement.. Explain measurement scales as related to agricultural design.. List various types of measurement scales..

  7. Week 7Module 4: Measurement and Evaluation
    • Unit 2: Sources of Error in Measurement · 2 hours

      Determine the major sources of error in agricultural research.. Know the various techniques in development of measurement tools.. Learn to minimize errors in measurement..

    • Unit 3: Data Collection Techniques · 2 hours

      Clearly state why, how, and when we need to collect data.. Understand the reasons for data collection.. Learn about primary and secondary data sources..

  8. Week 8Module 5: Statistical Theory
    • Unit 1: Sampling Fundamentals in Agricultural Research · 2 hours

      State the importance of sampling.. Explain some fundamental definitions of population parameters.. Understand the need for sampling in agricultural research..

    • Unit 2: Sampling Distribution · 2 hours

      Discuss the application of different sampling distributions.. Understand the importance of sampling distributions.. Learn about sampling distribution of mean and proportion..

  9. Week 9Module 6: Statistical Methods
    • Unit 3: Central Limit and Sampling Theory · 2 hours

      Delineate between sampling and central limit theorem.. List and explain different types of sampling distribution.. Understand the concept of standard error..

    • Unit 1: Guidelines and Explanations of Statistical Methods · 2 hours

      Discuss the characteristics of different statistical methods.. Explain guidelines for the application of different statistical methods.. Understand the basic procedures of statistical methods..

  10. Week 10Module 6: Statistical Methods
    • Unit 2: Approaches to Data Compilations and Analysis · 2 hours

      Screen and clean data before analysis.. Choose the right statistical tool and computer program for data analysis.. Understand data computation and analysis techniques..

    • Unit 3: Computational Techniques of Experimental Design · 2 hours

      Explain the mathematical steps involved in the calculation of t-test.. Understand analysis of variance (f-test), change over design, factorial, and nested design.. Learn computational techniques for experimental designs..

  11. Week 11Module 7: Presentation of Research Findings in Narrative, Tabular and Graphical Forms
    • Unit 1: Results Presentation through Tabular Form · 2 hours

      Differentiate between table types.. Itemize the guidelines for construction of tables.. Understand the advantages and disadvantages of tabular presentation..

    • Unit 2: Results Presentation through Graphical Form · 2 hours

      Present data using figures.. Determine the features of different graphs.. Understand graphical or diagrammatical representation of data..

  12. Week 12Module 7: Presentation of Research Findings in Narrative, Tabular and Graphical Forms
    • Unit 1: Results Presentation through Tabular Form · 4 hours

      Review all modules and units.. Work on assignments and TMAs.. Prepare for final examination..

    • Unit 2: Results Presentation through Graphical Form · 4 hours

      Review all modules and units.. Work on assignments and TMAs.. Prepare for final examination..

  13. Week 13Module 7: Presentation of Research Findings in Narrative, Tabular and Graphical Forms
    • Unit 1: Results Presentation through Tabular Form · 6 hours

      Final Revision. Complete any pending assignments. Focus on areas of weakness.

    • Unit 2: Results Presentation through Graphical Form · 6 hours

      Final Revision. Complete any pending assignments. Focus on areas of weakness.

Preparing for the exam

What to do
  • Review all study units and focus on key concepts and definitions.
  • Practice solving numerical problems from the examples in the units.
  • Create concept maps linking different modules and units.
  • Pay special attention to hypothesis testing procedures and statistical methods.
  • Practice data presentation techniques using different types of tables and graphs.

Questions students ask about this course

What is AGR501 about?

This course introduces students to the fundamental principles of research methodology and statistical analysis in Agricultural Science. It covers defining research problems, hypothesis testing, research design, data collection methods, and statistical theories. Students will learn to prepare questionnaires, analyze data using various statistical methods, and present research findings in tabular and graphical forms. The course aims to equip students with the skills to conduct novel research and apply statistical methodologies in agricultural contexts.

How many units does AGR501 have?

AGR501, Statistics And Research Methodology, has 21 units across 7 modules, over 122 pages of course material. You can read it one unit at a time.

How many credit units is AGR501?

AGR501 carries 3 credit units, at 500 level in Agricultural Sciences.

Is AGR501 hard?

AGR501 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical, practical and case study work, and it has a practical component.

How long does AGR501 take to study?

About 300 hours of study, spread across its 21 units.

How is AGR501 assessed?

AGR501 is assessed by assignments, tutor marked assignments and final examination.

What do I need before starting AGR501?

Basic Statistics Introduction to Agricultural Science

What can I do with AGR501?

Agricultural Researcher, Animal Scientist, Crop Scientist, Data Analyst and Research Consultant.

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