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Formula:
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Measures of Central Tendency & Dispersion
Measures that indicate the approximate center of a distribution are called measures of central tendency. Measures that describe the spread of the data are measures of dispersion. These measures include the mean, median, mode, range, upper and lower quartiles, variance, and standard deviation.
A. Finding the Mean
The mean of a set of data is the sum of all values in a data set divided by the number of values in the set. It is also often referred to as an arithmetic average. The Greek letter (“mu”) is used as the symbol for population mean and the symbol ̅ is used to represent the mean of a sample. To determine the mean of a data set:
- Add together all of the data values.
2. Divide the sum from Step 1 by the number of data values in the set.
Example:
Consider the data set: 17, 10, 9, 14, 13, 17, 12, 20, 14
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The mean of this data set is 14.
B. Finding the Median
The median of a set of data is the “middle element” when the data is arranged in ascending order. To determine the median:
- Put the data in order from smallest to largest.
- Determine the number in the exact center.
i. If there are an odd number of data points, the median will be the number in the absolute
middle.
ii. If there is an even number of data points, the median is the mean of the two center data
points, meaning the two center values should be added together and divided by 2.
Example:
Consider the data set: 17, 10, 9, 14, 13, 17, 12, 20, 14
Step 1: Put the data in order from smallest to largest. 9, 10, 12, 13, 14, 14, 17, 17, 20
Step 2: Determine the absolute middle of the data. 9, 10, 12, 13, 14 , 14, 17, 17, 20
Note: Since the number of data points is odd choose the one in the very middle.
The median of this data set is 14.
C. Finding the Mode
The mode is the most frequently occurring measurement in a data set. There may be one mode; multiple modes, if more than one number occurs most frequently; or no mode at all, if every number occurs only once. To determine the mode:
- Put the data in order from smallest to largest, as you did to find your median.
- Look for any value that occurs more than once.
- Determine which of the values from Step 2 occurs most frequently.
Example:
Consider the data set: 17, 10, 9, 14, 13, 17, 12, 20, 14
Step 1: Put the data in order from smallest to largest. 9, 10, 12, 13, 14, 14, 17, 17, 20
Step 2: Look for any number that occurs more than once. 9, 10, 12, 13, 14 , 14 , 17 , 17 , 20
Step 3: Determine which of those occur most frequently. 14 and 17 both occur twice.
The modes of this data set are 14 and 17.
D. Finding the Upper and Lower Quartiles
The quartiles of a group of data are the medians of the upper and lower halves of that set. The lower quartile , Q1, is the median of the lower half, while the upper quartile, Q 3 , is the median of the upper half. If your data set has an odd number of data points, you do not consider your median when finding these values, but if your data set contains an even number of data points, you will consider both middle values that you used to find your median as parts of the upper and lower halves.
- Put the data in order from smallest to largest.
- Identify the upper and lower halves of your data.
- Using the lower half, find Q 1 by finding the median of that half.
- Using the upper half, find Q 3 by finding the median of that half.
Example:
Consider the data set: 17, 10, 9, 14, 13, 17, 12, 20, 14
Step 1: Put the data in order from smallest to largest. 9, 10, 12, 13, 14, 14, 17, 17, 20
Step 2: Identify the lower half of your data. 9, 10, 12, 13, 14, 14, 17, 17, 20
Step 3: Identify the upper half of your data. 9 , 10, 12, 13, 14, 14, 17, 17, 20
Step 4: For the lower half, find the median. 9, 10, 12, 13 Since there are an even number of data points in this half, you will find the median by summing the two in the center and dividing by two. This is Q 1.
Step 5: For the upper half, find the median. 14, 17, 17 , 20 Since there are an even number of data points in this half, you will find the median by summing the two in the center and dividing by two. This is Q 3.
Q 1 of this data set is 11 and Q 3 of this data set is 17.
Step 2: Subtract the mean from each data value. 17 – 14 = 3 ; 10 – 14 = -4 ; 9 – 14 = -5 ; 14 – 14 = 0
13 – 14 = -1 ; 17 – 14 = 3 ; 12 – 14 = -2 ; 20 – 14 = 6 ; 14 – 14 = 0
Step 3: Square these values. 32 = 9 ; (-4)^2 = 16 ; (-5)^2 = 25 ; 0^2 = 0 ; (-1)^2 = 1 ; 3^2 = 9 ; (-2)^2 = 4 ; 6^2 = 36
Step 4: Add these values together. 9 + 16 + 25 + 0 + 1 + 9 + 4 + 36 = 100
Step 5: There are 9 values in our set, so we will divide by 9 – 1 = 8. = 12.
Note: This is your variance.
Step 6: Square root this number to find your standard deviation. (^) √ = 3.
The variance is 12.5 and the standard deviation is 3.536.
G. Using the TI-
- To enter the data values, press
the key. Select Edit…
- Enter the data values in the L1 column. 3. Press the key. Under CALC, select 1-VarStats
- Make sure the List is L1 then select Calculate. (^) Mean Sum of all data values
Sample Standard Deviation Population Standard Deviation Number of data values
Lower Quartile
Median Upper Quartile Smallest data value
Largest data value
These could be subtracted to find the range.
