Experiment in elementary statistics

Fernando, P. C. B.

doi:10.1119/1.10177

Cited by 5 publications

(4 citation statements)

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“…Although many other examples belong in this category (e.g., Rao, 1970), consider the demonstrations described by Fernando (1976) and Pierce (1983). In Fernando's demonstration, the purpose was to have students "verify empirically the various aspects of the Gaussian distribution" (p. 460).…”

Section: Distributional Shapementioning

confidence: 98%

Estimating the Probability of Success for Classroom Demonstrations in Statistics

Huck¹,

Clark²,

Ranney³

1985

Journal of Educational Statistics

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Classroom demonstrations, if well designed, can help students gain insights into statistical concepts and phenomena. Unfortunately, however, some instructors choose not to use this instructional device for fear that the data generated will turn out to be "uncooperative"; other instructors use demonstrations but use them unscientifically, ending up with data sets that either yield no insights or constitute "overkill." After discussing four kinds of demonstrations for which a "proper N" can and should be computed, we present three possible approaches for determining how much data are needed for the demonstration to have a reasonable probability of success. Examples from the literature are used to illustrate the need for a more scientific approach to this form of instruction.

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Section: Distributional Shapementioning

confidence: 98%

Estimating the Probability of Success for Classroom Demonstrations in Statistics

Huck¹,

Clark²,

Ranney³

1985

Journal of Educational Statistics

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“…Commonly these experiments are tedious and require a lot of time to be able to perform an adequate number of measurements to perform the statistical analysis (see for example the classical experiments proposed in Refs. [3,4]).…”

Section: Introductionmentioning

confidence: 99%

A home-lab to study uncertainties using smartphone sensors and determine the optimal number of measurements

Monteiro,

Stari,

Martí

2024

J. Phys.: Conf. Ser.

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We present a home-lab experimental activity, successfully proposed to our students during covid19 pandemic, based on state-of-the-art technologies to teach error analysis and uncertainties to science and engineering students. In the last decade the appearance of smartphones considerably affected our daily life. Thanks to their built-in sensors, this revolution has impacted in many areas and, in particular, the educational field. Here we show how to use smartphone sensors to teach fundamental concepts for science students such as any measurement is useless unless a confidence interval is specified or how to determine if a result agrees with a model, or to discern a new phenomenon from others already known. We explain how to obtain and analyse experimental fluctuations and discuss in relation with the Gaussian distribution. In another application we show how to determine the optimal number of measurements as a function of the standard error and the digital resolution of a given sensor.

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“…It is expected that, after finishing their studies, students are able to discuss whether a result agrees with a given theory and, if it is reproducible, or to distinguish a new phenomenon from a previously known one. With this objective, various experiments are usually proposed in introductory laboratory courses [7][8][9][10][11][12] . These experiments usually involve a great amount of repetitive measurements such as dropping small balls 12 , measuring the length of hundreds or thousands of nails using a vernier caliper 9 or randomly sampling an alternating current source 10 .…”

Section: Introductionmentioning

confidence: 99%

“…With this objective, various experiments are usually proposed in introductory laboratory courses [7][8][9][10][11][12] . These experiments usually involve a great amount of repetitive measurements such as dropping small balls 12 , measuring the length of hundreds or thousands of nails using a vernier caliper 9 or randomly sampling an alternating current source 10 . The measurements obtained are usually examined from a statistical viewpoint plotting, histograms, calculating mean values and standard deviations and, eventually, comparing them with those expected from a known distribution, typically a normal distribution.…”

Section: Introductionmentioning

confidence: 99%

Using mobile-device sensors to teach students error analysis

Monteiro,

Stari,

Cabeza

et al. 2020

Preprint

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Science students must deal with the errors inherent to all physical measurements and be conscious of the need to expressvthem as a best estimate and a range of uncertainty. Errors are routinely classified as statistical or systematic. Although statistical errors are usually dealt with in the first years of science studies, the typical approaches are based on manually performing repetitive observations. Our work proposes a set of laboratory experiments to teach error and uncertainties based on data recorded with the sensors available in many mobile devices. The main aspects addressed are the physical meaning of the mean value and standard deviation, and the interpretation of histograms and distributions. The normality of the fluctuations is analyzed qualitatively comparing histograms with normal curves and quantitatively comparing the number of observations in intervals to the number expected according to a normal distribution and also performing a Chi-squared test. We show that the distribution usually follows a normal distribution, however, when the sensor is placed on top of a loudspeaker playing a pure tone significant differences with a normal distribution are observed. As applications to every day situations we discuss the intensity of the fluctuations in different situations, such as placing the device on a table or holding it with the hands in different ways. Other activities are focused on the smoothness of a road quantified in terms of the fluctuations registered by the accelerometer. The present proposal contributes to gaining a deep insight into modern technologies and statistical errors and, finally, motivating and encouraging engineering and science students.

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Experiment in elementary statistics

Cited by 5 publications

References 0 publications

Estimating the Probability of Success for Classroom Demonstrations in Statistics

Estimating the Probability of Success for Classroom Demonstrations in Statistics

A home-lab to study uncertainties using smartphone sensors and determine the optimal number of measurements

Using mobile-device sensors to teach students error analysis

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