0
Still curious? Ask our experts.
Chat with our AI personalities
Lao
Blake
MaxineAdd your answer:
Earn +20 pts
Do outliers make some measures of central tendency better than others?
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.
Why is arithmetic mean considered as the best measure of central tendency?
The arithmatic mean is not a best measure for central tendency.. It is because any outliers in the dataset would affect its value thus it is considered not a robust measure.. The mode or median however would be better to measure central tendency since outliers wont affect it value.. Consider this example : Arithmatic mean dan mode from 1, 5, 5, 9 is 5.. If we add 30 to the dataset then the arithmatic mean will be 10 but the mode will still same.. Mode is more robust than arithmatic mean..
Why are three different measures needed in math measures of central tendency and dispersion?
There are more than three measures. Some are better than others in some situations but not as good in other situations.
How the values of mean and median relate to shape?
The question is how do the mean and median affect the distribution shape. In a normal curve, the mean and median are both in the same point. ( as is the mode) If a distribution is skewed, its tail is either on the right or the left. If a distribution is skewed the median may be a better value to use than the mean since it has less effect on the shape. Also is there are large outliers, the median has less effect and is better to use. So the mean has a bigger effect on the shape many times than the median.
What is the purpose of a stem and leaf plot?
to simply organise your numbers.ajm If you can make a histogram, a dotplot, or even a boxplot; there is no reason to do a steam and leaf plot. It's the worst graph. With a stem and leaf graph, you can see the distribution of data points, and determine whether it's normal distribution or not. As mentioned above, there are better graphs for doing that, though.
