2.2: Organizing and Displaying Quantitative Data

Classes

the categories by which data are grouped.

lower class limit

the smallest value within the class

upper class limit

the largest value within the class.

class width

the difference between consecutive lower class limits.

Bell-shaped (symmetric ) example

Skewed right example

skewed left example

Uniform(symmestric) example

Steps:

• Percentage = frequency of sum / total trials

• 19/100= 19%

An experiment was conducted in which two​ six-sided dice were thrown 100 times. The sum of the pips showing on the dice was then recorded. The frequency histogram to the right gives the results. Use the histogram to complete parts.

• Determining the percentage of time a sum was observed

was observed. (use 5 as a sum and 100 for the total times)

discrete data

Countable data values, usually whole numbers. Example: number of TVs in a household.

continuous data

Data that can take any value within a range. Example: a person’s height in inches.

Because the stem is split to keep the graph readable; one line shows leaves 0–4 and the other shows leaves 5–9.

Why does the same stem sometimes appear on two different lines?

Classes​ shouldn't overlap so there is no confusion as to which class an observation belongs.

Why​ shouldn't classes overlap when summarizing continuous data in a frequency or relative frequency​ distribution?

The statement is true. Any correctly constructed frequency distribution is valid.​ However, some choices for the categories or classes give more information about the shape of the distribution.

T or F. There is not one particular frequency distribution that is​ correct, but there are frequency distributions that are less desirable than others.

Bell shaped

For

IQ scores of students in a country​,

state whether you would expect a histogram of the data to be​ bell-shaped, uniform, skewed​ left, or skewed right.