Coefficient of Variation and Standard Scores MCQs

Prepare for Coefficient of Variation and Standard Scores MCQs with verified questions, past-paper solutions, and conceptual explanations for CSS, PMS, FPSC, PPSC, and NTS examinations.

41 Solved Questions • 31 Mins Practice • Updated for 2026 Competitive Exams
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Coefficient of Variation and Standard Scores constitutes an essential examination topic within Statistics, evaluating theoretical principles, historical context, and practical problem-solving applications. On MCQsMind, candidates practice verified past-paper solutions, conceptual breakdowns, and syllabus-aligned questions tailored for CSS, PMS, and competitive screening examinations.

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Topic Notes: Coefficient of Variation and Standard Scores

Quick Revision 3 min read 15 key points
Section 1 of 4

1 1. Coefficient of Variation (CV) Fundamentals

4 points
  • Definition
    Coefficient of Variation (CV): A relative measure of dispersion that expresses the standard deviation as a percentage of the arithmetic mean, allowing for the comparison of variability between datasets with different units.
  • Theory Jan 2024
    CV Formula: Calculated as (Standard Deviation / Arithmetic Mean) * 100. It is essential for comparing the relative stability or consistency of two or more data series.
  • Fact
    Unit-Free Nature: Because both the numerator (standard deviation) and the denominator (mean) are expressed in the same units, the CV is a dimensionless quantity, making it independent of the measurement scale.
  • Fact
    Interpretation: A lower CV indicates a more consistent, stable, or uniform dataset, while a higher CV indicates greater relative dispersion or volatility in the observations.
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1
Which of the following options is classified as a relative measure of dispersion?
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2
What is the approximate relationship between mean deviation and standard deviation in a normal distribution?
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3
In a standard normal distribution where the mean is 75 and the observed value is 120, what is the sign of the resulting z-statistic?
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4
According to the empirical rule for a normal distribution, which interval captures approximately 95.45% of the data?
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5
Given the linear transformation y = bx + c, what is the relationship between the range of y and the range of x?
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6
Calculate the standard normal variable (z-score) given a sample mean of 70, a population mean of 15, and a standard deviation of 20.
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7
According to the empirical rule for a normal distribution, what interval centered around the mean covers approximately 99.7% of the data?
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8
If a dataset of 40 observations has a variance of 50, what will the variance be if every observation is increased by 20?
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9
Which measure of dispersion is considered unsuitable for open-end distributions?
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10
What is the definition of the positive square root of the mean of the squared deviations of observations from their mean?
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Pedagogical Syllabus Blueprint

Coefficient of Variation and Standard Scores MCQs: Preparation Strategy & Exam Blueprint

Examination Weightage & Commission Distribution

In Pakistan's premier competitive examinations—including the Federal Public Service Commission (FPSC General Recruitment & CSS MPT), Punjab Public Service Commission (PPSC Lecturer, Tehsildar & PMS Screening), KPPSC, SPSC, and BPSC—questions derived from Coefficient of Variation and Standard Scores MCQs consistently constitute a decisive 10% to 25% weightage of the Descriptive Statistics paper. Testing agencies frequently evaluate both foundational factual recall and deeper analytical comprehension, requiring aspirants to master key dates, statutory articles, constitutional clauses, and thematic definitions.

High-Yield Conceptual Pillars & Distractor Analysis

Historical trend analysis across past five-year examination cycles demonstrates that examiner traps frequently involve closely matched numerical alternatives, chronologically contiguous treaties, and semantic subtleties in statutory phraseology. When preparing Coefficient of Variation and Standard Scores MCQs, candidates must deliberately review the underlying rationale provided for every question rather than merely memorizing raw answer options. Understanding why incorrect distractors fail is the most reliable predictor of achieving top percentiles in computerized and optical mark recognition (OMR) screening tests.

Negative Marking Mitigation & Time Management Protocol

For examinations enforcing negative marking penalties (such as PPSC's 0.25-mark deduction per erroneous response or NTS gatekeeper quotas), an aggressive elimination technique must be deployed. Candidates should systematically rule out improbable options first to elevate probability thresholds from 25% to 50% or 100%. Allocating an average of 45 to 60 seconds per item during mock trials builds the psychological stamina and cognitive precision required to complete 100-question papers within official 90-minute time limits.

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