Exploring Percentiles and Box-and-Whisker Plots

What is the primary difference between a percentile and a percentage?

• A percentage is used to measure data spread.

• A percentile can only be used in educational contexts.

• A percentile is always higher than a percentage.

• A percentile compares a score to a group, while a percentage is an absolute value.

If a student scores in the 95th percentile, what does it indicate about their performance?

• They need to improve to reach the 100th percentile.

• They were the top scorer.

• They answered 95% of the questions correctly.

• They scored better than 95% of the participants.

How does scoring in the 60th percentile in a group of brilliant individuals contextualize the score?

• It suggests the score is low.

• It indicates high performance.

• It reflects average performance relative to a high-achieving group.

• It is irrelevant in understanding performance.

What does the second quartile (Q2) represent in a data set?

• None of the above

• The lowest 25% of data

• The highest 25% of data

• The median of the data

In a box and whisker plot, what does the box represent?

• The total spread of the data

• Outliers in the data set

• The interquartile range from Q1 to Q3

• The range between the minimum and maximum values

What is the purpose of the whiskers in a box and whisker plot?

• To show the range of typical data points

• To represent the minimum and maximum values

• To indicate the median and mean

• To highlight the interquartile range

What statistical measure can be misleading if not aligned on a number line in a box and whisker plot?

• Mean

• Median

• Mode

• Quartiles

How is the interquartile range calculated?

• Q2 minus Q1

• Q3 minus Q1

• Q4 minus Q2

• Maximum value minus minimum value

What does a long whisker in a box and whisker plot indicate about the data?

• There are no outliers

• Data is tightly grouped

• The median is very high

• High variability in the upper quartile

Using software for statistical analysis helps in:

• None of the above

• Only organizing data

• Calculating complex statistical measures quickly

• Creating graphs only