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Is Mean is more sensitive to skewness than the median?
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.
What are the best measures of central tendency?
It depends on the particular set of numbers. Which is closest to the majority of the numbers.If all are random or completely Different numbers maybe the median?If they are really different, median is the best.If they are close to the same, the mode is better.There is no measurement better than the other, unless the data contains outliers.Mean is the most common, but if the data set contains outliers then consider using median or mode.In ADDITON:Which is better between mean, median and mode also depends on which type of data are we considering. There are basically 3 kinds of data:Nominal Data (qualitative data). For eg, marital status can be married, single, divorced or de facto.Ordinal data = the data are actually ranked, for eg Google is the number 1 search engine and yahoo is the no 2 search engine.Interval (numerical): for example: age, height, length, breadth etc.If we are looking at an interval(numerical) data, we can use any mean, median or mode. Mean is generally the best measure for statistical interference if there are no extreme values. When there are extreme values it is better to use median. Mode is very rarely used.If we are looking at nominal data, we cannot calculate mean. Like in the given example, marital status can be married, single, divorced or de facto. Now look at the following tableStatus FrequencyMarried 40Single 60Divorced 20De facto 10In this case we have to choose mode. The same is applicable for shoe size, waist size etc.If we are looking for an ordinal data, where data are ranked, the best measure of central tendency will be median.Apart from the type of data, nature of investigation in hand also affects which measure should be choose. In such cases, a personal judgment should be applied. An example is, if we are tying to compare how good a class did, in comparison with other classes, the best measure of central tendency would be mean. however, if we are looking inside a class and trying to compare how well we did in our class, median would be the best measure of central tendency. Unless the data is nominal, it is very rare that mode is the best measure of central tendency.
How do you measure egg to g?
Using a balance able to measure 0,1 g.
How do you find the measure of an angle to the nearest degree?
You can measure it. Or you can measure some other quantities (for examples, the lengths of the sides of a triangle), and calculate the angle using trigonometry.
Why do you multiply by 1.5 in a box and whiskers plot?
When John Turkey was inventing the box-and-whisker plot in 1977 to display these values, he picked 1.5*IQR (inter-quartile range) as the demarcation line for outliers. This has worked so well, so we've continued using that value ever since.
What are the criteria for choosing measure of central tendency and measure of variation?
Central tendency is measured by using the mean, median and mode of a set of numbers. Variation is measured by using the range, variance and standard deviation of a set of numbers.
What is an advantage to using the median when examining a set of data?
The median or mode should be used instead of the mean in distributions with extreme outliers. In such cases, the mean can be a misleading measure of central tendency and the median value or the mode value are typically more accurate measures.
What are the advantages and disadvantages of measures of central tendency?
One advantage to using central tendency is the fact that is represents all data. A disadvantage to using central tendency is the fact that extremes can skew the data.
When is using the mean as a measure of central tendency useful?
When your data is symmetric and narrowly spread about it.Each measure of central tendency has strengths and weaknesses. The mean takes every piece of numeric data and treats them all as equally weighted. Outliers will have equal weight with any other measure. In the long run, when you want to estimate a value that is least different from all values, use the mean. If you want your estimate to be closest to absolutely correct or to be absolutely correct most often, use the mode, and if you want your estimate to be as likely to be above the true value as below, use the median.
What is central tendency?
Though mean, median, and mode is central tendency, it is hard to put this into words.For an example:Your average grade in math class is an A. Though, how did you calculate that average? Well, since average means mean, you calculated that average using the method of central tendency, or in this situation, you found the mean.In other words, central tendency is just a method (mean, median and mode) to find the average, middle, and most occurring score or number in a set of data.I hope this helped! ;D~Lovingless
What an example of the uses of the measures of central tendency in everyday life?
An example of using measures of central tendency is in using mean; an example is using rating system to score a person. Also in median, which is used in subjects such as economics.
Why are there three measures of Central Tendency What if anything makes one better than the others?
Answer with an exampleIf you have a data series like: 1,2,2,3 What is the mean, median and mode of this thing:Mean= 2Median = 2Mode = 2Now if you have 1,2,2,3,1000Then we gotta have three measures asMode remains = 2Median shifts slightly toward threeMean becomes 201.6So 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.
What is central tendency of a data?
The term central tendency refers to the middle value or a typical value of the data. It is measured using the mean, median, or mode of the data. Each of these processes is found using different methods, and the one that should be used depends on the situation. I truly hope this helps.
What two data characteristics are usually measured using numerical descriptive measures?
Variability and Central Tendency (Stats Student)
Can you safely remove outliers from scatter charts?
You can only do it if either the outliers are way out - so far that they must be odd, so far that there can be no argument, no need for statistics to prove them to be outliers, or you need to prove that they are outliers using statistics - something like Grubb's test. To do that, the simplest way is software.
Is Mean is more sensitive to skewness than the median?
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.
What is the primary disadvantage of using the range to compare the variability of data sets?
The range is very sensitive to outliers. Indeed if there are outliers then the range will be unrelated to any other elements of the sample.
