If the sample has an odd number of items in it then the median will definitely be in the sample at least once because the median is value of the set of data items whose value(s) are in the middle of the sample when the sample is sorted from smallest to largest. If the sample has an even number of items in it then if the middle items are different the median will be their average, and it will differ from all of the items in the data set. I could continue in this vein but already you can see that the median sometimes occurs in a data set but not always.
Yes; the standard deviation is the square root of the mean, so it will always be larger.
The median shows where the 'middle' of your data is. For qualitative data, this only makes sense when the variable is ordinal. An ordinal variable is one whose values have a natural order, eg never/rarely/sometimes/often/always. If you have nominal data (qualitative data with no order) eg democratic/republican/other, you might find the mode (most common value) useful.
sometimes they can
Yes.
data are not alway numbers sometimes it have letters in it.
No, because sometimes sets of data can have different numbers and other sets of data can have modes in them.
a data set with two modes in is sometimes called "bimodal." Multi-modal, always reflects the contributions of each of the data values in the group!
data
If the sample has an odd number of items in it then the median will definitely be in the sample at least once because the median is value of the set of data items whose value(s) are in the middle of the sample when the sample is sorted from smallest to largest. If the sample has an even number of items in it then if the middle items are different the median will be their average, and it will differ from all of the items in the data set. I could continue in this vein but already you can see that the median sometimes occurs in a data set but not always.
It leads to the result.AnswerNot always. Sometimes it leads you to confusion.
Yes; the standard deviation is the square root of the mean, so it will always be larger.
no * * * * * Yes, almost always. If you have n data points which are 1-to-1, then it is always possible to fit a polynomial of degree n-1 or greater.
An outlier is a number in a data set that is not around all the other numbers in the data. It will always affect the average; sometimes raising the average to a number higher than it should be, or lowering the average to something not reasonable. Example: Data Set - 2,2,3,5,6,1,4,9,31 Obviously 31 is the outlier. If you were to average these numbers it would be something greater than most of the numbers in your set due to the 31.
Because it is defined as the principal square root of the variance.
The median shows where the 'middle' of your data is. For qualitative data, this only makes sense when the variable is ordinal. An ordinal variable is one whose values have a natural order, eg never/rarely/sometimes/often/always. If you have nominal data (qualitative data with no order) eg democratic/republican/other, you might find the mode (most common value) useful.
CDs have greater data track spacing because DVDs have more data thereforemore creases or the data track therefore less data track spacing