The mean, as a measure of central location, would be inappropriate for which one of the following

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Question No. 1

The mean, as a measure of central tendency would be inappropriate for which one of the following?

Choose the correct option from the given list.

Incomes of lawyers

Number of pages in textbooks on statistics

Ages of adults at a senior citizen center

None of these answers

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Please find below some common questions that are asked regarding measures of central tendency, along with their answers. These FAQs are in addition to our article on measures of central tendency found on the previous page.

What is the best measure of central tendency?

There can often be a "best" measure of central tendency with regards to the data you are analysing, but there is no one "best" measure of central tendency. This is because whether you use the median, mean or mode will depend on the type of data you have (see our Types of Variable guide), such as nominal or continuous data; whether your data has outliers and/or is skewed; and what you are trying to show from your data. Further considerations of when to use each measure of central tendency is found in our guide on the previous page.

In a strongly skewed distribution, what is the best indicator of central tendency?

It is usually inappropriate to use the mean in such situations where your data is skewed. You would normally choose the median or mode, with the median usually preferred. This is discussed on the previous page under the subtitle, "When not to use the mean".

Does all data have a median, mode and mean?

Yes and no. All continuous data has a median, mode and mean. However, strictly speaking, ordinal data has a median and mode only, and nominal data has only a mode. However, a consensus has not been reached among statisticians about whether the mean can be used with ordinal data, and you can often see a mean reported for Likert data in research.

When is the mean the best measure of central tendency?

The mean is usually the best measure of central tendency to use when your data distribution is continuous and symmetrical, such as when your data is normally distributed. However, it all depends on what you are trying to show from your data.

When is the mode the best measure of central tendency?

The mode is the least used of the measures of central tendency and can only be used when dealing with nominal data. For this reason, the mode will be the best measure of central tendency (as it is the only one appropriate to use) when dealing with nominal data. The mean and/or median are usually preferred when dealing with all other types of data, but this does not mean it is never used with these data types.

When is the median the best measure of central tendency?

The median is usually preferred to other measures of central tendency when your data set is skewed (i.e., forms a skewed distribution) or you are dealing with ordinal data. However, the mode can also be appropriate in these situations, but is not as commonly used as the median.

What is the most appropriate measure of central tendency when the data has outliers?

The median is usually preferred in these situations because the value of the mean can be distorted by the outliers. However, it will depend on how influential the outliers are. If they do not significantly distort the mean, using the mean as the measure of central tendency will usually be preferred.

In a normally distributed data set, which is greatest: mode, median or mean?

If the data set is perfectly normal, the mean, median and mean are equal to each other (i.e., the same value).

For any data set, which measures of central tendency have only one value?

The median and mean can only have one value for a given data set. The mode can have more than one value (see Mode section on previous page).

stats 3

Which measures of central location are not affected by extremely small or extremely large values?

What is the lowest level of measurement that a median can be computed?

What is a unique characteristic of the mean deviation?

For a data set with an odd number of observations that have been sorted from smallest to largest values, where is the median located?

What is a disadvantage of the range as a measure of dispersion?

It is based on only two observations.

The mean, as a measure of central location, would be inappropriate for which one of the following?

Marital status of college students at a particular university

What is the relationship between the variance and the standard deviation?

Variance is the square of the standard deviation.

For any data set, which measures of central location have only one value?

Sometimes, a data set has two values that have the highest and equal frequencies. In this case, the distribution of the data can best be described as __________.

Bimodal (having two modes)

Which measure of dispersion disregards the algebraic signs (plus and minus) of each difference between X and the mean?

Which of the following measures of dispersion are based on deviations from the mean?

Which one of the following is referred to as the population mean?

From the easiest to the hardest "ease of interpretation," rank the measures of dispersion.

Correct Range, mean deviation, variance

Which measures of central location are not affected by extremely small or?

The mean is a measure of the central location for the data. The median is another measure of central location that, unlike the mean, is not affected by extremely large or extremely small data values.

Which of the following is not a measure of central location?

Standard deviation is not a measure of Central tendency. Mean, Median and Mode are the measure of Central tendency.

What measure of central location uses all of the observations in its calculation?

The mean is the most frequently used measure of central tendency because it uses all values in the data set to give you an average.

Which of the following is a major disadvantage of the range as a measure of dispersion?

The main disadvantage in using interquartile range as a measure of dispersion is that it is not amenable to mathematical manipulation.