Chapter 3 Section 1: Measures Of Center Flashcards

1
Q

Arithmetic mean

A

The sum of all the data values divided by the number of data values often simply called the mean

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2
Q

Median

A

The middle value in an ordered array of data

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3
Q

Mode

A

The value i the data set that occurs the most frequently

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4
Q

No mode

A

Describes a data set in which all the data values accur only once or each value occurs an equal number of times

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5
Q

Unimodal

A

A data set in which only one data value occurs most often

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6
Q

Bimodal

A

A data set in which exactly two data values occur equally often

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7
Q

Multimodal

A

A data set in which more than two data value occur equally often

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8
Q

Sample mean/population mean

A

1+2+3+4/4

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9
Q

Properties of the mean

A

1) most familiar and widely used measure of center
2) its value is affected by EVERY value in the data set
3) may not be a value in the data set
4) appropriate measure of center for quantitative data with no outliers

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10
Q

Properties of the median

A

1) east to compute by hand
2) only determined by middle values of a data set, not affected by outliers
3) may not be a value in the data set if there are an even number of values in the set
4) useful measure of center for skewed distribution

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11
Q

Properties of the mode

A

1) a data set may not have a mode
2) a data set may have one or more than one mode
3) if a mode exists for a data set, the mode is a value in the data set
4) not affected by outliers in the data set
5) only measure of center appropriate for qualitative data

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12
Q

Determining the most appropriate measure of center

A

1) for qualitative data, the mode should be used
2) for quantitative data, the mean should be used, unless the data set contains outliers or is skewed
3) for quantitative data sets that are skewed or contain outliers, the median should be used

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13
Q

Graphs and measures of center

A

1) the mode is the data value at which a distribution has its highest peak
2) the median is the number that divides the area of the distribution in half
3) the mean of a distribution will be pulled toward any outliers

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