Lecturers

 Dr S.M. Makuza
 Dr F.N. Mhlanga
 Dr K.D. Dzama

 Objectives:
 * Offer students the most useful experimental designs used in agricultural research.
 *    Help students in the correct analysis and interpretation of their data.

 Text:
 Students may use any of the books available in the Library.

A limited number of copies of the following books are available at the   Biometry workroom: Department of Crop Science.

 1.         Cochran and Cox - Experimental Designs.
 2.         Mead and Curnow - Statistical Methods in Agriculture and Experimental Biology.
 3.         Payner A.A. - Biometry.
 4.         Sr J Canhao -- Experimental Design. A manual of notes compiled from various sources but
             mainly Dr D Neely.
 5.         Gill J.L. Design and Analysis of Experiments in the Animal   and Medical Sciences.

 Examination:

The examination paper (3 hours) contributes 50% of the final mark and continuous assessment will contribute the other 50% of the final mark.  Students are allowed to carry into the examination Hall two (2) sheets  of A4 paper with their personal notes and formulae.
Calculators are supplied (if not available).

 Teaching schedule:

 Four 1 hour lectures per week. One 3 hour practical every week.

 Practicals involve:

 1. The use of computer statistical packages (SAS) in evaluating data.
 2. Problem solving using hand calculators.

NB: Continuous assessment comprises of (a) Tests (b) Homework  practicals (c) Unannounced quizzes.

COURSE OUTLINE

1997

SEMESTER II

Dr F.N. Mhlanga: Lectures 1-3

Introduction

 1.1  Introductory Concepts - Experimental units, replication, randomisation, blocking, local control,
        balance etc.
 

 Dr S.M. Makuza: Lectures 4-6

 1.2  Populations, samples, variance.

 1.3  Distribution of means.

 Lectures 7-10

 2. Hypothesis Testing

 2.1  Confidence Intervals.

 2.2  Statistical inference.

 Lecture 11

 Dr F.N. Mhlanga

 3.  Experimental Designs.

 3.1  Simple Randomised Design (CRD).

 Lecture 12-15

 3.2  Randomised Complete Block Design (RCBD).

 Lecture 16-17

 3.3  Split - plot designs

 Dr F.N. Mhlanga: Lectures 18-21

 3.4  Latin Square and Cross-over Designs.

 Dr S.M. Makuza: Lectures 22-25

 3.5  The Factorial Experiments.
      - Factorial within a split-plot design.

 Lectures 26-27

 3.6 Nested Designs

 Lectures 28-29

 3.7 Incomplete Block Designs.

 Lecture 30
 

 MID TERM TEST.

 Dr K.D. Dzama: Lectures 31-34

 4.  Regression Techniques

4.1 Simple and Multiple Regression, and correlations.

 Lectures 35

 4.2 Indicator variables.

 Lecture 36

 4.3 Trend Analysis.

 Dr S.M. Makuza: Lectures 37-38

 4.4 Analysis of Covariance.

 Dr F.N. Mhlanga: Lectures 39-40

 5. Analysis of unbalanced (messy) data -- Animal breeding data/records.

 Dr S.M. Makuza: Lectures 41-42

 6. Analysis over sites.

 Dr(s) S.M. Makuza, F.N. Mhlanga and Dr K.D. Dzama: Lectures 43 and
 Beyond.

7. REVISION