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What is the center of a data set?

Back

The center of a data set refers to a measure that represents the middle or typical value of the data. Common measures of center include the mean, median, and mode.

Tags

CCSS.6.SP.A.2

Front

Define mean in the context of data sets.

Back

The mean is the average of a data set, calculated by adding all the values together and dividing by the number of values.

Tags

CCSS.6.SP.B.5C

Front

What is the median?

Back

The median is the middle value of a data set when the values are arranged in ascending or descending order. If there is an even number of values, the median is the average of the two middle values.

Tags

CCSS.6.SP.B.5C

Front

Explain mode in statistics.

Back

The mode is the value that appears most frequently in a data set. A data set may have one mode, more than one mode, or no mode at all.

Tags

CCSS.6.SP.A.3

Front

What does 'spread' refer to in a data set?

Back

Spread refers to the extent to which data values vary. It indicates how much the values differ from each other and from the center. Common measures of spread include range, variance, and standard deviation.

Tags

CCSS.6.SP.A.3

Front

Define range in statistics.

Back

The range is the difference between the highest and lowest values in a data set. It provides a measure of how spread out the values are.

Tags

CCSS.6.SP.A.3

Front

What is variance?

Back

Variance is a measure of how much the values in a data set differ from the mean. It is calculated by averaging the squared differences between each value and the mean.

Front

Explain standard deviation.

Back

Standard deviation is the square root of the variance. It provides a measure of the average distance of each data point from the mean, indicating the spread of the data.

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What are outliers in a data set?

Back

Outliers are data points that are significantly different from the rest of the data. They can be much higher or lower than the other values and can affect the measures of center and spread.

Front

How can you identify outliers?

Back

Outliers can be identified using methods such as the interquartile range (IQR) method, where values that fall below Q1 - 1.5*IQR or above Q3 + 1.5*IQR are considered outliers.