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AGR305Agricultural Sciences2 Unitsintermediate

Analytical Techniques For Animal Production I

This course introduces students to experimental designs and statistical analysis in animal science. It covers topics such as experimental error, sampling techniques, common experimental designs, and data presentation. Students will learn about measures of central tendency, dispersion, relationships, and hypothesis testing. The course also explores volumetric, gravimetric, thermometric, electrochemical, and optical methods of chemical analysis relevant to animal science research.

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150h

Study Time

13

Weeks

12h

Per Week

intermediate

Math Level

Course Keywords

Experimental DesignStatistical AnalysisAnimal ScienceData AnalysisChemical Analysis

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level

Builds on foundational knowledge

65%

intermediate

📊

Math Level

Moderate Math

🔬

Learning Type

Hands-on Practice

Course Topics

Key areas covered in this course

1

Experimental Error

2

Sampling Techniques

3

Experimental Designs

4

Statistical Analysis

5

Hypothesis Testing

6

Volumetric Analysis

7

Gravimetric Analysis

8

Thermometric Analysis

9

Electrochemical Analysis

10

Optical Methods

Total Topics10 topics

Requirements

Knowledge and skills recommended for success

Basic Biology

Basic Chemistry

Introductory Statistics

💡 Don't have all requirements? Don't worry! Many students successfully complete this course with basic preparation and dedication.

Assessment Methods

How your progress will be evaluated (3 methods)

assignments

Comprehensive evaluation of course material understanding

Written Assessment

tutor-marked assessments

Comprehensive evaluation of course material understanding

Written Assessment

final examination

Comprehensive evaluation of course material understanding

Written Assessment

Career Opportunities

Explore the career paths this course opens up for you

Animal Nutritionist

Apply your skills in this growing field

Livestock Scientist

Apply your skills in this growing field

Research Assistant

Apply your skills in this growing field

Laboratory Technician

Apply your skills in this growing field

Agricultural Consultant

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

Animal Feed IndustryLivestock ProductionAgricultural ResearchFood SafetyEnvironmental Monitoring

Study Schedule Beta

A structured 13-week journey through the course content

Week

1

Module 1: Introduction

3h

Unit 1: General Introduction to Experimental Error

3 study hours

•Define experimental error and its types.
•Identify sources of systematic and random errors.
•Differentiate between accuracy and precision.
•Calculate percent error and percent difference.

Week

2

Module 1: Introduction

3h

Unit 2: Sampling Techniques

3 study hours

•Describe characteristics of a good sample.
•Develop a sampling plan considering objectives, consequences, and homogeneity.
•Explain representative, probability, and random number sampling.
•Differentiate between simple, systematic, and stratified sampling.

Week

3

Module 1: Introduction

4h

Unit 3: Common Experimental Designs in Animal Science

4 study hours

•Define experiment and experimental design.
•Explain randomization, replication, and control in experimental design.
•Describe Completely Randomized Designs (CRD) and Randomized Complete Block Design.
•Understand Factorial and Split Block Designs.

Week

4

Module 1: Introduction

4h

Unit 4: Practical Application of Common Designs in Animal Experiments

4 study hours

•Apply calculations in CRD.
•Calculate Analysis of Variance (ANOVA) in RCBD.
•Calculate ANOVA from data in Latin Square.
•Solve calculations (ANOVA) from data in nested design.

Week

5

Module 2:

3h

Unit 1: Introduction to Statistics

3 study hours

•Define statistics and describe its scope.
•Differentiate between descriptive and inferential statistics.
•Explain data collection methods and their importance.
•Summarize and present data in tabular and graphical formats.

Week

6

Module 2:

4h

Unit 2: Descriptive Statistics

4 study hours

•Calculate mean, median, and mode for ungrouped and grouped data.
•Determine range, mean deviation, variance, and standard deviation.
•Calculate coefficient of variation and standard error.
•Interpret measures of central tendency and dispersion.

Week

7

Module 2:

4h

Unit 3: Probability

4 study hours

•Explain correlation and regression concepts.
•Draw and interpret scatter diagrams.
•Compute Pearson product moment correlation coefficient.
•Perform simple regression analysis.

Week

8

Module 2:

3h

Unit 4: Measures of Relationships

3 study hours

•Define probability and its types.
•Explain and compute additive and multiplicative probability laws.
•Distinguish between empirical, classical, and subjective probabilities.
•Apply Bayes' Theorem.

Week

9

Module 2:

4h

Unit 5: Statistical Tests

4 study hours

•Define hypothesis and its types.
•Explain errors in hypothesis testing.
•Perform Z-test and T-test for significance.
•Differentiate between one-sided and two-sided tests.
•Apply F-test and Chi-square distribution.

Week

10

Module 3:

3h

Unit 1: Principle of Volumetric Data Analysis

3 study hours

•Explain the basic principles of volumetric analysis.
•List requirements for volumetric treatment of samples.
•Describe acid-base, precipitation, and redox titrations.
•Identify methods for determining the endpoint in titration.

Week

11

Module 3:

3h

Unit 2: Gravimetric Data Analysis

3 study hours

•Explain the concept of gravimetric analysis.
•List types of gravimetric analysis.
•Describe precipitation and volatilization gravimetric methods.
•Explain the general procedure for gravimetric analysis.

Week

12

Module 3:

3h

Unit 3: Thermometric Data Analysis

3 study hours

•Define thermometric analysis.
•List different types of thermometric analysis.
•Explain the principles of thermometry.
•Discuss advantages and disadvantages of thermometric analysis.

Week

13

Module 3:

3h

Unit 4: Electrochemical Analysis

3 study hours

•Explain the concept of electrochemical analysis.
•List and differentiate electrochemical methods.
•Apply electrochemical principles to animal science research.
•Describe potentiometric, voltametric, coulometric, and conductometric methods.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Create detailed summaries of experimental designs (CRD, RCBD, Factorial) with examples from animal science.

2

Practice calculating ANOVA tables and interpreting F-values for different experimental designs.

3

Develop flashcards for statistical terms (mean, median, mode, standard deviation, variance) and their formulas.

4

Work through practice problems involving hypothesis testing (Z-test, T-test, Chi-square) with real-world data.

5

Review laboratory procedures for volumetric, gravimetric, and electrochemical analyses, focusing on calculations and error analysis.

6

Create concept maps linking Units 3-5 statistical concepts

7

Practice SQL queries from Units 7-9 weekly

8

Allocate specific study time for each module based on its weight in the final grade

9

Form a study group to discuss challenging concepts and practice problem-solving together

10

Review all TMAs

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