Statistics Assignment: Week 5 Discussion on Levels of Measurement

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This discussion post explores the concept of levels of measurement in statistics, focusing on interval and ratio scales. It explains that the interval level of measurement involves interpretable intervals between values, such as temperature measured in Fahrenheit. It also mentions that in interval measurement, the separation between the values is the same along the scale. The post then discusses the ratio level of measurement, which includes an absolute zero point, allowing for ratio comparisons. It highlights that weight is a ratio variable and that many 'count' variables in social research are also ratio variables. The post references several sources to support the discussion, including works by Salkind, McPhail, Goodwin, and Gordon, Neuman, and Cox et al.
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Running Head: MEASUREMENT 1
Week 5 Discussion: Levels of Measurement
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MEASUREMENT 2
Week 5 Discussion: Levels of Measurement
First is the interval level which is the parting amongst features that means something. For
instance, when we measure temperature (in Fahrenheit), the separation from 20-50 is same as
separation from 60-90. The interval between values is interpretable. In this way, it looks great to
process a normal of an interval variable, where it doesn't look great to do everything considered
for ordinal scales. In any case, watch that in interval measurement ratios don't look great - 90
degrees isn't two times as hot as 45 degrees (in spite of how the quality view is twice as
sweeping). (Salkind, 2016).
Additionally, social occasions and requesting the measure, and furthermore confirms that
the separations between every interval on the scale are undefined along the scale from low to
high levels of interval. (McPhail, Goodwin, and Gordon, 2006). For instance, an interval level of
measurement could be the measurement of weight out of an understudy between the score of 20
and 21; this interval is the same as that of an understudy who scores in the area of 50 and 51. The
separation in the district of 830C and 860C is the same as the separation in the area of 2000C and
2030C.
At long last, in ratio measurement, there is always a level out zero that is basic. This
proposes you can collect a basic part (or ratio) with a ratio variable. Weight is a ratio variable.
(Cox et al., 2009). In related social research most "check" factors are a ratio, for instance, the
measure of customers lately. (Neuman, 2016). In this level of measurement, the perceptions, in
spite of having procured back the first speculation with intervals, can have an estimation of zero
too. The zero in the scale makes this sort of measurement not in the smallest degree like trade
sorts of measurement, paying little mind to the way that the properties look like that of the
interval measurement level.
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MEASUREMENT 3
References
Cox, E., Martin, B. C., Van Staa, T., Garbe, E., Siebert, U., & Johnson, M. L. (2009). Good
research practices for comparative effectiveness research: Approaches to mitigate bias
and confounding in the design of nonrandomized studies of treatment effects using
secondary data sources: The International Society for Pharmacoeconomics and Outcomes
Research Good Research Practices for Retrospective Database Analysis Task Force
Report—Part II. The value in Health, 12(8), 1053–1061
McPhail, D., Goodwin, I., & Gordon, K. (2006). Reviewing statistical analysis plans—A guide
for medical writers. Drug Information Journal, 40(2), 197–202.
Neuman, W. L. (2016). Understanding research. Pearson.
Salkind, N. J. (2016). Statistics for people who (think they) hate statistics. Sage Publications.
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