Fill in the blank: A cumulative frequency distribution table includes columns for frequency, cumulative frequency, and ___ percentage.

Cumulative

What is the difference between relative frequency and percentage frequency?

Relative frequency compares observations.

• Fraction of total observations.

• Calculated as frequency/total.

• Percentage frequency is multiplied by 100.

True or False: Continuous variables can be represented in frequency distribution tables without class intervals.

False. Continuous variables should always be represented using class intervals to allow for accurate frequency representation.

Describe the relationship between mean, median, and mode in a symmetric distribution.

In a symmetric distribution, the mean, median, and mode are equal, indicating that the data is evenly distributed around a central point.

When constructing cumulative frequency tables, what additional columns are typically included?

Cumulative frequency tables include extra columns.

• Cumulative frequency shows totals.

• Cumulative percentage indicates proportions.

• Both enhance data interpretation.

Fill in the blank: The width of a class interval is the difference between the ___ of one interval and the ___ of the next.

Lower endpoint

What does the interquartile range measure, and how is it calculated?

Measures data spread effectively.

• Focuses on middle 50%.

• Calculated as Q₃ minus Q₁.

• Reduces outlier impact.

True or False: The range is the most comprehensive measure of dispersion in a dataset.

False

Range is not comprehensive measure.

• Only max and min values.

• Ignores data distribution aspects.

• Variance and SD are better.

Explain how Chebyshev’s Theorem applies to data distribution.

Chebyshev's Theorem estimates data variability.

• Applies to any dataset shape.

• Defines data within k std deviations.

• Useful for variability estimation.

What is the primary purpose of constructing a frequency distribution table?

Organizing data for analysis.

• Shows frequency of observations.

• Helps identify distribution patterns.

• Facilitates easier data interpretation.