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Data Analysis Flashcards

7 cards from real CAASPP 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 flashcards as text
  1. A back-to-back stem-and-leaf plot compares scores for two classes. Class A has more leaves on the higher stems than Class B. What can you conclude?

    Answer: Class A scored higher overall

    More leaves on higher stems means more high scores, so Class A generally scored higher.

  2. Data set A: 10, 10, 10, 10, 10. Data set B: 2, 7, 10, 13, 18. Both have a mean of 10. How do their standard deviations compare?

    Answer: Set B has a larger standard deviation

    Set A has zero variation (all values equal the mean), while Set B's values vary, giving it a larger standard deviation.

  3. A survey finds that students who sleep more hours tend to score higher on tests. This is an example of what type of relationship?

    Answer: A positive correlation

    When both variables increase together (more sleep → higher scores), the relationship is a positive correlation.

  4. In a data set with values 3, 5, 5, 7, 9, 11, what is the mean absolute deviation (MAD) if the mean is 6.67?

    Answer: 2.22

    The absolute deviations are 3.67, 1.67, 1.67, 0.33, 2.33, 4.33; their average ≈ 2.22.

  5. A teacher displays quiz grades on a dot plot. The plot is skewed right. What does this tell you about most students' grades?

    Answer: Most grades are low to moderate, with a few very high outliers

    A right skew means the tail extends toward higher values, so most data is clustered at the lower end with a few high outliers.

  6. Which of the following is an example of categorical data?

    Answer: Favorite colors of students

    Categorical data describes qualities or groups (like colors), not numerical measurements.

  7. A student claims that because ice cream sales and drowning rates both rise in summer, eating ice cream causes drowning. What error is the student making?

    Answer: Confusing correlation with causation

    Correlation between two variables does not prove that one causes the other; both may be driven by a third factor (hot weather).