Skewness is the measure of the?

RUHS, Jaipur, M.Sc Nursing Entrance Exam-2016

Nursing Research & Statistic

Easy

Appeared in: RUHS, Jaipur, M.Sc Nursing Entrance Exam-2016

Explanation

Skewness is a fundamental concept in statistics used to describe the shape of a data distribution.
Its primary purpose is to quantify the degree of asymmetry, or the departure from a perfectly symmetrical shape (like a bell curve).
A skewness value of zero indicates a symmetrical distribution.
A positive value indicates a distribution skewed to the right (long tail on the right), and a negative value indicates a distribution skewed to the left (long tail on the left).
Therefore, skewness is the measure of the asymmetry of a probability distribution.

Option A: This is the opposite of what skewness measures. A distribution with perfect symmetry has a skewness of zero, but skewness itself is the measure of the lack of symmetry.
Option C: Measures of central tendency describe the center or 'typical' value of a dataset. The main measures are the mean, median, and mode. Skewness, in contrast, describes the shape and asymmetry of the distribution, not its center.
Option D: This is a duplicate of the previous option and is incorrect for the same reason. Measures of central tendency (mean, median, mode) describe the center of the data, while skewness describes the shape of the distribution.

Clinical Relevance

Nursing practice connection: This is primarily an exam-oriented knowledge point with limited direct bedside application, so retain Definition of Skewness in Statistics as background academic context rather than a clinical decision trigger.
Many clinical and biological variables in nursing research, such as patient recovery times, length of hospital stay, or income levels, do not follow a normal (symmetrical) distribution. They are often skewed.
Understanding skewness is critical for nurse researchers to choose the correct statistical methods. For highly skewed data, non-parametric tests are more appropriate than parametric tests.
What if? - If a researcher is analyzing patient satisfaction scores and finds the data is negatively skewed, it means most patients reported high satisfaction, with a few outliers reporting very low satisfaction. In this case, the researcher should report the median satisfaction score instead of the mean, as the mean would be pulled down by the few low scores and would not accurately represent the typical patient's experience.

How to Approach the Question

Identify the core term in the question, which is 'Skewness'.
Recognize this is a definition-based question from the field of statistics.
Recall the fundamental definition of skewness. It is a measure of distortion or departure from a symmetrical distribution.
Evaluate the options: 'Asymmetry' directly matches the definition. 'Symmetry' is the opposite concept. 'Central tendency' is a different statistical concept that deals with the center of the data (mean, median, mode).
Select the option that correctly defines skewness as a measure of asymmetry.

Concept Tested & Keywords

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E6 NursingResearch Sukhpal Kaur p. 469-471

E6 NursingResearch Polit 11e Part 1 p. 384-386