Manual Computations—A Tool for Reinforcing Concepts and Techniques

Khamis, Harry J.

doi:10.1080/00031305.1991.10475826

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…In a search for the use of hand computations to teach statistics, extant research is extremely limited, relying on dated conceptual articles with no analysis of how hand computations impact student learning and understanding of statistics. For example, Khamis (1991) asserted hand computations for teaching statistics to clinical professionals (e.g., M.D., R.N., psychologists, and social workers) reinforces the skills necessary to evaluate data. However, no studies appear to be conducted to support this assertion.…”

Section: Examining the Fitmentioning

confidence: 99%

The Challenge of Counseling Research in Developing a Signature Pedagogy for Quantitative Methods

Balkin¹

2020

Teaching and Supervision in Counseling

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Section: Examining the Fitmentioning

confidence: 99%

The Challenge of Counseling Research in Developing a Signature Pedagogy for Quantitative Methods

Balkin¹

2020

Teaching and Supervision in Counseling

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“…En este apartado hemos revisado artículos que exponen cómo el uso del SE en la enseñanza de la estadística aumenta las posibilidades didácticas de los docentes y mejora la competencia estadística de los estudiantes en actitudes, habilidades y conocimientos. A principios de los 90 una revisión llevada a cabo por Khamis (1991) indicaba que el 70% de los cursos introductorios de estadística usaban software informático. Hoy día se ha extendido el uso de SE a la mayoría de los cursos de estadística y la cuestión que queda por resolver es qué software específico debe ser integrado en el proceso de enseñanza y aprendizaje (Fernandez y Liu, 1999).…”

Section: Investigaciones Previasunclassified

Las tecnologías en el aula para la enseñanza del contraste de hipótesis

Cañadas¹,

Molina‐Portillo²,

Contreras³

et al. 2019

EduMate

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Resumen. Las tecnologías han influido de forma significativa en todos los campos, y en mayor medida en los temas relacionados con la estadística (Galmacci, 2001). La mayoría de las investigaciones sobre contraste de hipótesis describen errores en la interpretación del nivel de significación y el p-valor (ej., Vallecillos, 1994), existiendo poca presencia de investigaciones de errores sobre el contraste de hipótesis mediante el uso de tecnologías. Esto incentiva la realización de investigaciones con recursos informáticos que están apareciendo cada vez más en el aula, produciéndose una demanda de investigación en este terreno. El presente artículo muestra los resultados de un análisis comparativo en el que se examina la utilización de software SPSS frente al uso de software libre (R) en la enseñanza de estadística a nivel universitario, donde se utilizan

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“…Definitional formulae facilitate this goal; computational formulae block its accomplishment. As Khamis (1991) states:…”

Section: Formulae Should Teach Conceptsmentioning

confidence: 99%

The Obsolescence of Computational Formulae

Muttart

2009

Teaching Statistics

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Computational formulae are a throwback to a time when computers were not widely available. Today their teaching obscures important underpinnings of statistical theory and practice.᭜ INTRODUCTION ᭜ T he teaching of computational formulae impairs the ability of students to understand statistics.Definitional formulae are clearly favoured by some statistical educators. Bradstreet (1996), for instance, noted that 'the simple computations performed by the students should be those which reinforce data analytic and data interpretation concepts' (p. 70). He went on to state that definitional formulae provide superior vehicles for the teaching of statistical concepts than do computational formulae. Furthermore, there are texts which only include definitional formulae. An example of such is the text by Phillips (2000).To clarify the above, almost all statistical formulae come in two forms: a definitional formula, which elegantly describes the relationships between its inherent components, and a computational formula, which generates the same answer but is easier to employ when making calculations with pen and paper. This note argues that only definitional formulae ought to be taught in introductory statistics courses.If we go back to the time when I learned statistics, there were hardly any computers, and those which existed were mainframes which had to be fed the program to be run, along with the data, on a series of 3-inch by 8-inch punch cards. Statistical calculations were done with pencil and paper, aided by hand-held calculators which were then becoming widely available. In this environment, any formulae which reduced the number of tedious mathematical calculations were not just convenient, they were a necessity. Thus the algebraic derivation and practical application of computational formulae, sometimes called raw-scores formulae, were essential components of introductory statistics courses. ᭜ COMPUTING THE STANDARD ᭜ DEVIATIONOne fundamental formula directs the calculation of the standard deviation. The definitional formula is given first below, and a typical raw-scores computational formula follows it.As with most computational formulae, the second one above is much less elegant; indeed one would say that it is most clunky to look at. But in practice, if one were to use pen and paper to calculate a standard deviation, it removes the necessity of subtracting the mean from each value. Thus if the sample size was 150, the computational formula would allow the researcher to avoid one hundred and fifty tedious (and possibly error-provoking) calculations.

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Manual Computations—A Tool for Reinforcing Concepts and Techniques

Cited by 8 publications

References 28 publications

The Challenge of Counseling Research in Developing a Signature Pedagogy for Quantitative Methods

The Challenge of Counseling Research in Developing a Signature Pedagogy for Quantitative Methods

Las tecnologías en el aula para la enseñanza del contraste de hipótesis

The Obsolescence of Computational Formulae

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