Practical Projects in the Teaching of Statistics at Universities

Scott, J. F.

doi:10.2307/2987642

Cited by 8 publications

(3 citation statements)

References 1 publication

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“…There is much to be said for getting students to collect their own data, particularly in introductory courses--see, for example, Jowett and Davies (1960), Murdoch and Barnes (1965) and Scott (1976). Experiments can stimulate student interest and develop self-reliance.…”

Section: Methodsmentioning

confidence: 99%

Teaching a Course in Applied Statistics

Chatfield¹

1982

Applied Statistics

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The purpose of the study is to present the Beehive Interactive Learning Model (BILM) and to provide an example of its application in an undergraduate statistics course. The model is developed by the researcher, who is a professor in Educational Measurement and Evaluation area in Turkey with over 15 years of teaching experience. The model is based on four main components; content, instruction, assessment, and motivational beliefs. The core principal of the model is to stimulate students' desire for learning. Both the instructor and the students are in the center of the model, placed in the beehives, referring to the hard work and constant interaction among students. The graphical representation of the model is presented in the paper. The model has been improved over a period of 10 years by adding new components and omitting some. The model requires the instructor to encourage active learning through class projects and performance assignments. It heavily relies on technology and the Internet; course portal provides online documents, an opportunity to download and submit assignments online, and to take online self-regulated quizzes with instant feedback. There are lab sessions requiring students to demonstrate their analyzing skills in SPSS. The model aims to pack the knowledge in a way that awakens everybody's desire to learn, satisfies the learner through successful hands-on applications and finally develops a sense of success, hopefully yielding positive attitudes toward the content and learning. The model is in the process of development and any suggestions are welcomed from the researchers around the world.

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Section: Methodsmentioning

confidence: 99%

Teaching a Course in Applied Statistics

Chatfield¹

1982

Applied Statistics

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“…Students also gain an introspective appraisal of the working assumptions of an experiment (Jowett and Davies 1960): They become aware of the issues involved in designing an investigation and in the subsequent collection and analysis of the data. There are many good classroom experiments that require minimal setup time yet illustrate important statistical concepts (see Griffiths and Evans 1976;Jowett and Davies 1960;Lowe and Lwanga 1978;Mandel 1965;Scott 1976;Shulte and Smart 1981;Tanner 1985). This method teaches the student to view statistics as a natural component of the dynamic process of scientific investigation.…”

Section: Include Practical Experimentation In the Course Ofmentioning

confidence: 96%

“…The cost and availability of resources for experimentation must be considered, and the logistics involved may be cumbersome. The most cogent objections, according to Scott (1976), are that the project can go wrong and that the statistical lesson can be swamped by the experimental detail. A full discussion of the pros and cons of practical experimentation in the classroom could be very beneficial to the statistics teaching community.…”

Section: Include Practical Experimentation In the Course Ofmentioning

confidence: 97%

Manual Computations—A Tool for Reinforcing Concepts and Techniques

Khamis

1991

The American Statistician

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One of the issues in statistics education today involves the extent to which manual computations should be incorporated into the elementary statistics curriculum. Students should be required to work with data and carry out some manual computations because such activities speed and enhance the learning process, reinforce the concepts and techniques introduced, provide an environment of constructive participation and personal discovery, and improve quantitative skills. A discussion of student populations, of the nature of hand computations, and of different types of data and their role in the learning process is given.

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Ancillary Statistics Which are Not Invariant

Padmanabhan

1977

The American Statistician

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Practical Projects in the Teaching of Statistics at Universities

Cited by 8 publications

References 1 publication

Teaching a Course in Applied Statistics

Teaching a Course in Applied Statistics

Manual Computations—A Tool for Reinforcing Concepts and Techniques

Ancillary Statistics Which are Not Invariant

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