first off you have to no what the median is
the median is the middle number in a group of data
if there is no "middle" number ad the two middle numbers together and then divide by 2
example:
1,2,3,4
2+3=5
5 divided by 2 is equal to 2.5
2.5 is your median
{note explanaition was for people who might read this question so that they could understand}
For an odd number of data values, the median is the middle number, the [(n+1)/2]th numberi.e. for 7 data values, (7 +1)/ 2 = 4, and the 4th is the middle value, or median.*For an even number of values, the median is the mean of the two middle numbers,i.e. one-half the sum of the two middle values (add n/2nd value and n/2+1st values and divide by 2).Examples:Median of 1, 3, 2 reordered as 1, 2, 3 = median 2Median of 6, 5, 3, 1 reordered as 1, 3, 5, 6 = median 4 (3+5 divided by 2)
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.
The median is advantageous because it is not influenced by extreme values, making it a robust measure of central tendency for skewed data sets. It is also easy to interpret and calculate. However, the median may not accurately represent the true center of a dataset if the data is heavily skewed or if there are outliers present. Additionally, the median may not be as efficient as the mean for certain statistical calculations due to its lack of sensitivity to all data points.
Any set of numbers can have only one mean and only one median but it can have as many modes as it has values.
A central tendency is a number that expresses something "central" about a sample of values (which could be test scores, temperatures, etc...). Measures of central tendency include the mean, the median, and the mode.The Mean is equal to the average of all the values. Thus, the Mean is equal to the sum of all the values (add them all up) divided by the total number of values in your set or sample. This average tells you nothing about what your highest and lowest values are (the range). However, ...The Median is equal to the the number which, if you were to arrange your values from lowest to highest, falls exactly in the middle of your distribution of values. So, if you have 41 values, for instance, the Median would be the 21st value, and there would be 20 values equal to or smaller than the Median, and 20 values equal to or larger than the median. If, on the other hand, there were 100 values, the median would be the average of the 50th and 51st values in the distribution. The median tells you nothing, however, about what values occur "most often" in your distribution. So....There is the mode, which is equal to the value which occurs most often in your distribution. Simply count how many times each of your values occurs, and the mode= the one that occurs most often. The following is an example of a distribution which is highly "skewed" meaning that there are differences between the mean, median and mode for the set of values being observed.MeanThe mean is the most commonly-used measure of central tendency. When we talk about an "average", we usually are referring to the mean. The mean is simply the sum of the values divided by the total number of items in the set. The result is referred to as the arithmetic mean.It is the best average of measures of central tendency.It is used in Stock exchange, Market to calculate the Mean (share) Price in the particular day.Sometimes it is useful to give more weighting to certain data points, in which case the MedianThe median is determined by sorting the data set from lowest to highest values and taking the data point in the middle of the sequence. There is an equal number of points above and below the median. For example, in the data set {1,2,3,4,5} the median is 3; there are two data points greater than this value and two data points less than this value. In this case, the median is equal to the mean. But consider the data set {1,2,3,4,10}. In this dataset, the median still is three, but the mean is equal to 4. If there is an even number of data points in the set, then there is no single point at the middle and the median is calculated by taking the mean of the two middle points.The median can be determined for ordinal data as well as interval and ratio data. Unlike the mean, the median is not influenced by outliers at the extremes of the data set. For this reason, the median often is used when there are a few extreme values that could greatly influence the mean and distort what might be considered typical. This often is the case with home prices and with income data for a group of people, which often is very skewed. For such data, the median often is reported instead of the mean. For example, in a group of people, if the salary of one person is 10 times the mean, the mean salary of the group will be higher because of the unusually large salary. In this case, the median may better represent the typical salary level of the group. ModeThe mode is the most frequently occurring value in the data set. For example, in the data set {1,2,3,4,4}, the mode is equal to 4. A data set can have more than a single mode, in which case it is multimodal. In the data set {1,1,2,3,3} there are two modes: 1 and 3.The mode can be very useful for dealing with categorical data. For example, if a sandwich shop sells 10 different types of sandwiches, the mode would represent the most popular sandwich. The mode also can be used with ordinal, interval, and ratio data. However, in interval and ratio scales, the data may be spread thinly with no data points having the same value. In such cases, the mode may not exist or may not be very meaningful.We have to findout Model value of the particular things.For example shoe Model size =Maximum no of persons used shoe size,likewise shirt size and various products models.When to use Mean, Median, and ModeThe following table summarizes the appropriate methods of determining the middle or typical value of a data set based on the measurement scale of the data.Measurement ScaleBest Measure of the "Middle"Nominal(Categorical)ModeOrdinalMedianIntervalSymmetrical data: MeanSkewed data: MedianRatioSymmetrical data: MeanSkewed data: Median result is called the weighted arithmetic mean
No, it is not necessarily true that the median is always one of the data points in a set of data. The median is found by arranging the data in numerical order and selecting the middle value. This value might be one of the data points, but it could also be the average of two data points if there is an even number of values in the set.
Quartiles.
The median is advantageous because it is not influenced by extreme values, making it a robust measure of central tendency for skewed data sets. It is also easy to interpret and calculate. However, the median may not accurately represent the true center of a dataset if the data is heavily skewed or if there are outliers present. Additionally, the median may not be as efficient as the mean for certain statistical calculations due to its lack of sensitivity to all data points.
yes they are if you have 0 and 10 the mean is 5 and so is the median. The mean and the median can in fact be the same value. But basically to answer your question, One possible way is that if the values are ascending by 1 in the data set, then the number of values left to the median should be the same as the number of values right to the median. e.g. 6+7+8+9+10 6,7 = 2 terms 9,10 = 2 terms median =8 mode = 8
They are called the quartiles. The middle one is also known as the median.
For an odd number of data values, the median is the middle number, the [(n+1)/2]th numberi.e. for 7 data values, (7 +1)/ 2 = 4, and the 4th is the middle value, or median.*For an even number of values, the median is the mean of the two middle numbers,i.e. one-half the sum of the two middle values (add n/2nd value and n/2+1st values and divide by 2).Examples:Median of 1, 3, 2 reordered as 1, 2, 3 = median 2Median of 6, 5, 3, 1 reordered as 1, 3, 5, 6 = median 4 (3+5 divided by 2)
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.
A median can have only one value.
A single, extremely large value can affect the median more than the mean because One-half of all the data values will fall above the mode, and one-half will fall below the mode. In a data set, the mode will always be unique. The range and midrange are both measures of variation.
No. Here's one set of data where the mean is not one of the values: a set of 250,000 numbers. 125,000 of them are "1", 125,000 are "3". The mean of this data set is "2", which is not among the data.
MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.
Mean and median are the measures of central location that always have one value. This is true for a set of grouped or ungrouped data.