Stats Ch. 3

Front 1

Measure of location

Back 1

A value used to describe the center of a set of data.

Front 2

Arithmetic mean

Back 2

Is the most widely reported measure of location. It is calculated by adding the values of the observations and dividing by the total number of observations. The major characteristics are:

1 at least the interval scale of measurement is required.

2 all the data values are used in the calculation

3 A set of data has only 1 mean . This is the unique.

4 the sum of the deviation from the mean equals 0.

Front 3

The weighted mean

Back 3

A computation of the arithmetic mean used when you have multiple observations of the same value in the population or sample.

Front 4

The median

Back 4

The value in the middle of a set of ordered data. To find sort the observations from minimum to maximum and identify the middle value. Major characteristics include the following

1 at least ordinal scale of measurement is required

2 it is not influenced by extreme values

3 50% of the observation are larger than the _____

4 it is unique to a set of data

Front 5

The mode

Back 5

Is the value that occurs most often in a set of data. It can be found for nominal-level data. A set of data can have more than one ____.

Front 6

Dispersion

Back 6

Is the variation or spread in a set of data.

Front 7

Range

Back 7

Is the difference between the maximum and the minimum values in a set of data. the major characteristics are :

1. only 2 values are used in its calculation

2. it is influenced extreme values

3. it is easy to compute and to understand. formula is:

maximum value - minimum volume=

Front 8

Mean absolute deviation

Back 8

Is the sum of the absolute values of the deviations from the mean divided by the number of observations. The major characteristics are:

1. it is not in duly enforced by large or small values

2. all observations are used in the calculation

3. the absolute values are somewhat difficult to work with.

Front 9

Variance

Back 9

Is the mean of the squared deviation from the arithmetic mean. The major characteristics are:

1. all observations are used in the calculation

2. it is not unduly influenced by extreme observations

3. the units are somewhat difficult to work with; they are the original units squared.

Front 10

Standard Deviation

Back 10

Is the square root of the variance. The major characteristics are:

1. It is in the same units as the original data.

2. It is the square root of the average squared distance from the mean

3. It can not be negative

4. It is the most widely reported measure of dispersion

Front 11

Interpret the standard deviation using 2 measures

Back 11

1. Chebyshev's theorem states that regardless of the shape of the distribution, at least 1-1/k^2 of the observations will be within K standard deviations of the mean, where K is greater than one..

2. The Empirical Rule States that for a bell shape distribution about 68% of the values will be within standard deviation of the mean, 95% within 2, and virtually all within 3.

Front 12

Empirical Rule (also called the normal rule)

Back 12

Applies only to a symmetrical bell shaped distribution.

+1 or -1

Approximately 68% of the data is with one plus or minus standard deviation from the mean.

+2 or -2

Approximately 95% of the data is within 2 plus or minus standard deviations of the mean.

+3 or - 3

Approximately 99.7% of the data is within 3 plus or minus standard divisions from the mean.

Front 13

Arithmetic mean

Back 13

In a population, it is the sum of all the values divided by the number of items. In a sample, it is the sum of the value of the items selected divided by the number of items.

Front 14

Bi-Modal

Back 14

A population with 2 modes.

Front 15

Deviation

Back 15

The difference between 2 items.

Front 16

Geometric mean

Back 16

A special form of a mean used in a situation in which you are computing averages that compound on each other or you want to compute the rate of change of an item over time.

Front 17

Maximum

Back 17

The highest value in a distribution

Front 18

Mean deviation

Back 18

The arithmetic mean of the absolute values of the deviation of each observation from the arithmetic mean.

Front 19

Median

Back 19

The midpoint of the values after they have been arranged in order, either smallest to largest or largest to smallest.

Front 20

Minimum

Back 20

The lowest value in a distribution.

Front 21

Mode

Back 21

The value of an observation that occurs most frequently.

Front 22

Negatively skewed distribution

Back 22

The arithmetic mean is smaller than the median or mode because of one or more smalle values.

Front 23

Outlier

Back 23

A value that is much larger or much smaller than the rest of the data.

Front 24

Positively skewed distribution

Back 24

The arithmetic mean is larger than the median or mode due to one or more large values.