1,2,2,3 What is the mean, median and mode of this thing:
Mean= 2
Median = 2
Mode = 2
Now if you have 1,2,2,3,1000
Then we gotta have three measures as
Mode remains = 2
Median shifts slightly toward three
Mean becomes 201.6
So you can see that three measures are required to capture the tendency of a data set in a more complete fashion.
Although the mean does have this problem of being distorted by outliers (extreme values), it is the best measure of central tendency if more sophisticated analyses are required. This is because the properties of the mean, itself, are better understood. This means there is a wide range of powerful statistical techniques that can be applied to data using the mean.
Both are measures of central tendency. But, the mean has mathematical properties that are better understood.
iDK! do your homework! or even better! pay attention in class! i learned that the hard way.
Mode
Given that the study manager wants the QC efforts to be focused on selecting outlier values, whose method is a better way of selecting the sample
It depends on what you want. If it is simply to know what the "average" value is, then the mode may be the best in these circumstances. But if you want to do anything else - eg determine the spread of the data, or test any hypothesis about the data, you will be much better off with the mean. That is because the mean has been studied much more comprehensively than other measures of central tendency and its characteristics are incorporated into many statistical tests.
Both are measures of central tendency. But, the mean has mathematical properties that are better understood.
There are more than three measures. Some are better than others in some situations but not as good in other situations.
iDK! do your homework! or even better! pay attention in class! i learned that the hard way.
Mode
Given that the study manager wants the QC efforts to be focused on selecting outlier values, whose method is a better way of selecting the sample
Yes. Central tendency is the way data clusters around a value. Even if the distribution of the value is skewed, the median would be the best indicator of central tendency because of the way the data is clustered.
mean
There is no single number. There are several different measures of central tendency - different ones are better in different circumstances. Then there are several measures of spread or dispersion, skewness and so on. All of these are characteristics of the data and they cannot all be summarised by a single number.
The main measures of central tendency are the mean, the median and the mode. For a normal distribution, they are identical. For other distributions, they can vary quite a bit. Since the mode is the most-frequent element of the distribution, you can have more than one mode, which is not particularly helpful in most probability computations. The median is the level which 50% of the values are below (also known as the 50th percentile). The mean is the sum of the values divided by the number of values. Between the median and the mode, the median is less variable, and so is generally a better measure of overall central tendency. However, when computing statistical probabilities, the mean is often more useful in the mathematical formulas, which are generally oriented toward computing the probability that a given value is different from a different value.
It depends on what you want. If it is simply to know what the "average" value is, then the mode may be the best in these circumstances. But if you want to do anything else - eg determine the spread of the data, or test any hypothesis about the data, you will be much better off with the mean. That is because the mean has been studied much more comprehensively than other measures of central tendency and its characteristics are incorporated into many statistical tests.
If the distribution is positively skewed , then the mean will always be the highest estimate of central tendency and the mode will always be the lowest estimate of central tendency (If it is a uni-modal distribution). If the distribution is negatively skewed then mean will always be the lowest estimate of central tendency and the mode will be the highest estimate of central tendency. In both positive and negative skewed distribution the median will always be between the mean and the mode. If a distribution is less symmetrical and more skewed, you are better of using the median over the mean.
In Statistics, the measure of spread tells us how much adata sample is spread out or scattered. We can use the range and the interquartile range (IQR) to measure the spread of a sample. Measures of spread together with measures of location (or central tendency) are important for identifying key features of a sample to better understand the population from which the sample comes from. The range is the difference between a high number and the low number in the samples presented. It represents how spread out or scattered a set of data. It is also known as measures of dispersion or measures of spread.