MAT120 2.2

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

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

True or False: The shape of the distribution shown is best classified as skewed left.

False.

True or False: The shape of the distribution shown is best classified as skewed right.

False.

Continuous Variable

A quantitative variable that has an infinite number of possible values that are not countable.

Discrete Variable

A quantitative variable that has either a finite number of possible values or a countable number of possible values.

What is Uniform Distribution?

A type of probability distribution in which all outcomes are equally likely; each variable has the same probability that it will be the outcome.

To caculate x percentage for y or less,

Add the two highest frequencies, divide the answer over total frequency and convert the decimal answer into a percent.

To caculate x percentage for y or more,

Add the two highest frequencies, divide the answer over total frequency and convert the decimal answer into a percent.

Is this bell-shaped, skewed left, skewed right, or uniform?

Bell-shaped.

For a number of people living in a household​, state whether you would expect a histogram of the data to be​ bell-shaped, uniform, skewed​ left, or skewed right.

Skewed right.

When there are two similar frequency distribution and relative distribution histograms, one being eight classes and the other being four classes, does one frequency distribution provide a better summary of the data than the​ other? Explain.

The shape is not as clear in the distribution with fewer​ classes, so more classes should be used.

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

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.