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Data Analysis & Reporting Flashcards

7 cards from real CSCS practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 Data Analysis & Reporting flashcards as text

  1. A strength coach calculates a Pearson correlation of r = 0.82 between vertical jump height and 40-yard dash time in athletes. How should this be interpreted?

    Answer: Strong negative relationship — faster athletes tend to jump higher

    r = 0.82 is a strong negative relationship (if expressed as negative), but since sprint time is inverse to speed, faster 40-yard times (lower numbers) correlate strongly with greater jump height.

  2. When reporting athlete performance data, the coefficient of variation (CV) is best used to:

    Answer: Assess relative variability between measurements with different units

    CV expresses standard deviation as a percentage of the mean, allowing relative variability comparison across measures with different scales or units.

  3. A coach uses a repeated-sprint protocol and finds the intraclass correlation coefficient (ICC) = 0.95. What does this indicate?

    Answer: The test shows excellent reliability between repeated measurements

    An ICC ≥ 0.90 is generally considered excellent reliability, indicating highly consistent results across repeated administrations.

  4. Which statistical measure represents the smallest change in a performance variable that exceeds measurement error and can be attributed to a true change?

    Answer: Minimal detectable change (MDC)

    The minimal detectable change (MDC) is derived from measurement error and defines the threshold above which a change is considered real rather than noise.

  5. An athlete's 1RM squat improves from 200 lb to 215 lb. What type of data representation best communicates this change to a non-technical audience?

    Answer: A percentage change calculation (7.5% increase)

    Percentage change is intuitive for non-technical audiences and clearly conveys magnitude of improvement in practical terms.

  6. When comparing strength gains between a trained group and a control group, which statistical test is most appropriate if both groups show normally distributed data?

    Answer: Independent samples t-test

    An independent samples t-test compares means between two unrelated groups when data are normally distributed and measured on a continuous scale.

  7. A CSCS practitioner reports Cohen's d = 1.2 for a training intervention. According to conventional benchmarks, how should this effect size be classified?

    Answer: Large effect

    Cohen's d ≥ 0.8 is classified as a large effect size, with d = 1.2 indicating a very large practical difference between conditions.