Chapter 6: measures of central tendency Flashcards
The population arithmetic mean is denoted by
M
The sample arithmetic mean is denoted by
X bar
One of the two mathermatical property of the mean
this equation value ∑(Xi-c)² is minimum when
c is equal to x bar
One of the two mathermatical property of the mean
∑(Xi-M) is equal to
0
If we add or subtract c to each one of the original observations, then what happens to the mean
the mean will increase or decrease by the same constant
If we divide or multiply all original observations to constant c, then what happens to the mean?
the mean of the new data set is equal to the product of old data and c
This is used if the individual observed values vary in their degree of importance
weighted mean
[https://www.bing.com/images/search?view=detailV2&ccid=7Hd4k%2BQN&id=9D2
A modification of the arithmetic mean. This is an apppropriate alternative to arithmetic mean whenever there are outliers
trimmed mean
When the question says, get the 5 percent trimmed mean of the data – You should delete the top and bottom 5 percent
This divides the array into two equal parts
Median
what is the formula for median
Interpretation for the median
At least half of the observations are less than or equal to the median and at the same time at least half of the observations are greater than or equal to the median
What is the property of the median
Outliers do not affect the meadian
This is the most observed value
Mode
What is the property of the mode
- It does not always exist or it may not be unique
- Outliers do not affect the mode
What is the data requirement for mean
Atleast interval scale
What is the data requirement for median
At least ordinal scale
What is the data requirement for mode
Only nominal scale
What is the property of the mean
It utilizes all of the observed values in the collection
How to approximate for the median from grouped data (formula)
Md = LCB(md) + C (times the equation below)
those parenthesis means subscript
f(md)
How to approximate for the MEAN from grouped data (formula)
N
from i to k
Where,
Fi is the frequency
Xi is the class mark
N is total observations or summation of fi
k is equal to total number of classes
How to approximate for the mode in grouped data
Mo = LCBmo + C ((fmo-f1)/(2fmo-f1-f2))
where,
f1 is the frquency of the class preeceding the modal class
fmo is the frquency of the modal class
f2 is the the frquency of the class following the modal class
What is the property of the mode
It may not always exist
What is the property of the median
Outliers in a data set do not affect the median