Describing distributions

Front

What is the definition of a unimodal distribution?

Back

A unimodal distribution is a probability distribution with a single peak or mode, indicating that most of the data points cluster around one central value.

Front

What does it mean for a distribution to be skewed?

Back

A skewed distribution is one where the data points are not symmetrically distributed around the mean, resulting in a longer tail on one side.

Front

How do you describe the shape of a distribution?

Back

The shape of a distribution can be described as unimodal, bimodal, uniform, or skewed, based on the number of peaks and the symmetry of the data.

Front

What is the range of a distribution?

Back

The range of a distribution is the difference between the maximum and minimum values in the dataset, indicating the spread of the data.

Tags

CCSS.6.SP.A.3

Front

What are the three measures of central tendency?

Back

The three measures of central tendency are the mode (most frequent value), median (middle value when data is ordered), and mean (average of all values).

Tags

CCSS.6.SP.A.3

Front

How is the mode of a distribution determined?

Back

The mode is determined by identifying the value that appears most frequently in the dataset.

Tags

CCSS.6.SP.B.5C

Front

What is the median and how is it calculated?

Back

The median is the middle value of a dataset when it is ordered from least to greatest. If there is an even number of observations, the median is the average of the two middle values.

Tags

CCSS.6.SP.B.5C

Front

What is the mean and how is it calculated?

Back

The mean is calculated by summing all the values in a dataset and dividing by the number of values.

Tags

CCSS.6.SP.B.5C

Front

What does it mean for a distribution to have a high spread?

Back

A high spread indicates that the data points are widely dispersed from the central value, resulting in a larger range and greater variability.

Tags

CCSS.6.SP.A.2

Front

What is the significance of the shape of a distribution in statistics?

Back

The shape of a distribution helps in understanding the data's characteristics, including its central tendency, variability, and the presence of outliers.