# a sequence of games useful in teaching experimental design to agriculture students

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A Sequence of Games Useful in Teaching ExperimentalDesign to Agriculture StudentsK. H. Pollock a , H. M. Ross-Parker b & R. Mead ca Department of Mathematics , University of California , Davis , CA , 95616 , USAb The Postgraduate Institute of Agriculture, University of Sri Lanka , Peradeniya , Sri Lankac Department of Applied Statistics , University of Reading , Reading, EnglandPublished online: 26 Mar 2012.

To cite this article: K. H. Pollock , H. M. Ross-Parker & R. Mead (1979) A Sequence of Games Useful in Teaching ExperimentalDesign to Agriculture Students, The American Statistician, 33:2, 70-76

To link to this article: http://dx.doi.org/10.1080/00031305.1979.10482663

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A Sequence of Games Useful in Teaching ExperimentalDesign to Agriculture Students

K. H. POLLOCK, H. M. ROSS-PARKER, and R. MEAD*

In this article a sequence of statistical games is described thatwere found useful for teaching statistics to agriculture students.The ideas of experimental design tend to be neglected in statisticsservice courses for agriculturalists because of the practical diffi-culty of allowing students to learn design by experience. Simulat-ing experiments in the classroom or on the computer console is aviable alternative and should be more widely used. In this article,three games-TOMATO, CHICK, and SELECT-are described.Other games can be invented. The relevance of using games ex-tends to fields other than agriculture.

KEY WORDS: Games; Teaching; Experimental design; Inter-active computing.

1. Introduction

Statistics is a necessary part of the education ofagriculture students. Many of these students, however,have a natural aversion to all things mathematicaland little idea of what statistics is about or why theyshould understand it. Therefore, a first course mustpersuade such students that they need to learn thesubject.

Some ideal goals of a first course in statistics arethat the students will (a) understand the essential phi-losophy of statistical methods; (b) know how to usebasic statistical techniques, be able to appreciatewhen to use them, and be capable of interpreting theresults; (c) appreciate the principles and practice ofdesigning agricultural experiments; (d) know when toask for statistical advice and be able to discuss theirproblem intelligently with a statistician.

These goals are difficult to achieve. Many coursesconcentrate solely on the second goal: the analysis ofexperiments using the standard statistical techniques.As a result, the students learn little about the design ofexperiments, the third goal, which is more importantfor them than the method of analysis. Teaching onlyanalysis tends to distort the students' whole view of thesubject and interferes with the realization of the othertwo aims.

The teaching ofdesign ofexperiments is very difficultbecause it is usually not possible for students todo much designing of their own agricultural experi-ments where they can learn by experience. Whereverfeasible, however, this approach should be used.Another way of providing experience in the design of

* K.H. Pollock is Lecturer, Department of Mathematics, Uni-versity of California, Davis, CA 95616. H. M. Ross-Parker is SeniorLecturer, The Postgraduate Institute of Agriculture, University of SriLanka, Peradeniya, Sri Lanka. R. Mead is Reader, Department ofApplied Statistics, University of Reading, Reading, England. Thiswork was begun when all the authors were in the Department ofApplied Statistics at Reading. The authors wish to thank their col-leagues at Reading for many helpful discussions.

experiments is through simulating the experimentalsituation in the classroom.

Mead (1974) described an experimental design gameto simulate a poultry experiment. The game, ap-propriately called CHICK, could be played at an on-line computer console. Pike (1976) described a non-computer version of this game called HEN, whichcould be played in the classroom by using slips of papercarrying simulated observations.

CHICK has been used for several years in a servicecourse for agriculture students at the University ofReading. The class of approximately 150 studentsranged from first year to postgraduate. We found thatCHICK was a little too demanding for the first designgame the students met, partly because it involvedthe use of computer consoles but also because ofsome difficult design concepts inherent in the game.Also, CHICK alone could only illustrate some as-pects of design, and thus we felt a sequence ofgames was necessary. In this article we discuss the se-quence of experimental design games TOMATO,CHICK, and SELECT, which we devised to developthe students' ability to design agricultural experi-ments.

In the next section we give a description of the games.The description will be followed by a discussion ofthe advantages and disadvantages of using the games onthe computer consoles or in the classroom. Finally, wediscuss the sequence as a whole, including its strengthsand weaknesses.

2. The Sequence of Games

2.1. TOMATO

2.1.1. Introduction. This first game is played early inthe statistics course before the students have beentaught any experimental design. TOMATO introducesthe idea of blocking and encourages the use of an un-balanced design, which students tend to resist at a laterstage in the course. The game also introduces studentsto the concept of a factorial treatment structure,informally laying the groundwork for discussion in laterlectures.

A brief verbal description of the game is given toaugment the following specification, emphasizing theimportance of the side-of-greenhouse effect, the twostages of the experiment and the treatment structure.

2.1.2. Specifications given to the students. Twofarmers, Adams and Bloggs, grow glasshouse tomatoesin Guernsey for the English market. After several years,Bloggs clearly gets higher yields than Adams. Unfortu-nately, Bloggs and Adams have difficulty determining

70 The American Statistician, May 1979, Vol. 33, No.2

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Treatment

A. The Greenhouse Used in the Experiment.

for the second stage, even though the incorporation ofastage effect would have made the game more realistic.This point is considered further in subsection (2.1.5.).

When both stages of the experiment were completeand the students had interpreted their observations,we held a class discussion. First, each pair of studentswas asked to give answers for the optimum andeconomic-optimum combinations orally. The answerswere then displayed on the blackboard. The answerswere briefly discussed and the true mean yieldsrevealed. We had to make the point that studentswho received incorrect answers had not necessarilybeen remiss in their design. This point led to a valuablediscussion of uncertainty of inferences in experiments.

2.lA. The model parameters. In designing the game,we had to decide on both the mean yields of each treat-ment-plot combination and the variability of thesequantities. The standard deviation was chosen asunity for all observations on all treatment-plot com-binations; the chosen values for the means are givenin Table 1. You should note that all plots on each sidehad the same mean for each treatment but distinctenvelopes were used.

The treatment code is in the order HEAT, LIGHT,and VARIETY, 0 indicating the norma

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