What measure of central tendency best describes the center of the distribution skewed right?

  • A third another statistic that has been proposed (in addition to the mean and median) to estimate the center of a dataset: the 5%-trimmed mean: throw out the bottom 2.5% and top 2.5% of the observations, then compute the sample mean of the remaining observations.

  • The median and the 5%-trimmed mean are resistant statistics because they are resistant to outliers.

  • If there are less than 2.5% outliers on the left and less than 2.5% outliers on the right, then the trimmed mean is more efficient for estimating the center of the histogram than the median is.

  • A family of more esoteric statistics to estimate the center of a dataset are the M-estimators. They are weighted averages, which give heavier weight to the observations close to the median and less weight to the observations in the tails.

  • To obtain M-estimators with SPSS, select
      Analyze >> Descriptive Statistics >> Explore... Click the Statistics button and check the M-estimators box.
  • What measure of central tendency best describes the center of the distribution skewed right?

    The mean, mode, and median can help us summarize the findings of a study. In this guide, we will learn how these three measures of central tendency are used.

    Definition: Central tendency

    Measures of central tendency is a summary measure that describes a data set with a single value that represents the middle of the distribution. Here are the three most common measures of central tendency:

    • Mean – This represents the average of the data set.
    • Median – This represents the middle value.
    • Mode – This is the most commonly occurring value in a data set.1

    When performing descriptive statistics, it is also crucial to understand measures of variability. You can also summarize the data set by describing its distribution.2

    What measure of central tendency best describes the center of the distribution skewed right?

    Central tendency: Distributions

    In statistics, a data set is defined as a distribution of n number of values or scores.

    Normal distribution

    In a normal distribution, the data is distributed symmetrically. In this case, the values of the mean, median, and mode would be the same. Here is an example of a normally distributed data set:

    Shoe size Frequency
    4 1
    5 4
    6 8
    7 4
    8 1

    Skewed distributions

    In a skewed distribution, more values will fall on one side of the center than on the other. In such cases, the mean will be greater than the median, and the median will be greater than the mode.

    In a negatively skewed distribution, the mode would be greater than the median, and the mean will be less than both of these values.

    The mode is the value that appears most frequently in a distribution. To get the mode, you have to arrange the values in ascending or descending order, and then you can find the middle value. Depending on the nature of the data set, you may get one mode, multiple modes, or no mode at all. In a frequency table, the mode would be the variable with the highest frequency. If you choose to use a bar graph, you simply need to check the highest bar, as it represents the mode. Let’s consider this example:

    Shoe size Frequency
    4 1
    5 4
    6 8
    7 4
    8 1

    In this case, the mode is 6 because most people reported this as their shoe size.

    When to use the mode

    Mode is commonly used with nominal data since this form of data is classified into mutually-exclusive categories. When dealing with ratio data, it is not necessary to use the mode since you will be dealing with many variables. Here is an example of ratio data:

    Height Frequency
    154 1
    156 1
    158 1
    161.2 1
    164 13

    The median refers to the middle value in a data set, and you can find this value by arranging the data in ascending or descending order.

    Income level Frequency
    $0-$2,000 2
    $2,001-$4,000 5
    $4,001-$6,000 20
    $6,001-$8,000 5
    $8,001-$10,000 1

    By ordering the data from low to high, you will be able to see that the exact middle point is at $4,001-$6,000.

    Median of an odd-numbered data set

    In an odd-numbered data set, you can find the median by locating the value at the  position. The  in the formula represents the number of values featured in the data set. In the above example, the total number of values is 33, so you can apply the formula as follows:4

    By finding the value at the 17th position, you will be able to locate the median.

    Median of an even-numbered data set

    If the data set has an even number of variables, you will have to find the  and values. After that, you can add the two numbers and divide them by two. In a data set with 60 values, the median will be the mean of the values at these positions:4

    and 

    Central tendency – Mean

    The arithmetic mean is the most commonly used measure of central tendency. It represents the average of the data set and is calculated by adding up all the values and dividing the product by the number of values. On the other hand, the geometrical mean is calculated as the n-root of the product of all the values. In the data set (3,4,6,8,14), the arithmetic mean can be calculated by adding up all the values. You can find the mean by dividing this number by n, which equals 5 in this example.4

    Outlier effect on the mean

    Data outliers are values that lie very far from the other values in a data set. These values can make the mean significantly higher or lower than the other values. For example, in the data set (3,5,7,9,300), the mean is 64.8, and this doesn’t represent the data set accurately.5

    Population vs. sample mean

    You can find the mean of a sample or a population. Population vs. sample mean are calculated in the same way, but the notations are different. For example, the ‘n’ symbol represents the number of variables in the sample data set, and the ‘N’ symbol represents the number of variables in the population.6

    All three measures of central tendency are meant to be used together since they have different strengths and limitations. However, in some cases, you may not be able to use one or two measures of central tendency.

    • The mode can be applied to all four levels of measurement, but it’s mostly used with nominal data and ordinal data.
    • The median can only be used with ordinal data, ratio data, and interval data.
    • The mean can only be used with interval or ratio levels of measurement.

    Levels of measurement Examples Measure of central tendency
    Nominal Gender, nationality Mode
    Ordinal Education level, satisfaction rating Mode, median
    Interval and ratio IQ grading, temperature Mode, median, mean

    When choosing a measure to use in a particular data set, you have to consider the distribution of the data. If it is normally distributed, you can use mean, median, or mode as they would all have the same value. For skewed data, you should use the median.

    FAQs

    Sources

    1 Australian Bereau of Statistics. “Statistic Language – Measures of Central Tendency.” Accessed September 20, 2022. https://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Statistical+Language+-+measures+of+central+tendency.

    2 Hayes, Adam. “Descriptive Statistics.” Investopedia.  August 01, 2022. https://www.investopedia.com/terms/d/descriptive_statistics.asp.

    3 Vetter, Saha, Frost, and Sullivan. “Ratio Data: Definition, Examples, Survey Questions & more.” Voxco. March 19, 2021. https://www.voxco.com/blog/ratio-data/.

    4 Browniee, Jason. “Arithmetic, Geometric, and Harmonic Means for Machine Learning.” Machine Learning Mastery. December 17, 2019. https://machinelearningmastery.com/arithmetic-geometric-and-harmonic-means-for-machine-learning/.

    5 Zach. “How DO Outliers Affect the Mean?.” Statology. January 29, 2020. https://www.statology.org/how-do-outliers-affect-the-mean/.

    6 S., Surbhi. “Difference Between Sample Mean and Population Mean.” Key Differences. December 12, 2019. https://keydifferences.com/difference-between-sample-mean-and-population-mean.html.

    7 Laerd Statistics. “FAQs – Measures of Central Tendency.” Accessed September 20, 2022. https://statistics.laerd.com/statistical-guides/measures-central-tendency-mean-mode-median-faqs.php.

    What is the best measure of center for a skewed right distribution?

    In a skewed distribution, the median is often a preferred measure of central tendency, as the mean is not usually in the middle of the distribution.

    What is the best measure of Center for right skewed histogram?

    If a histogram is skewed, the median (Q2) is a better estimate of the "center" of the histogram than the sample mean.

    What is the best measure of central tendency for a skewed right histogram Why?

    In skewed distributions, the median is the best measure because it is unaffected by extreme outliers or non-symmetric distributions of scores.

    What is the center of a skewed distribution?

    The median is the value in the center of the data. Half of the values are less than the median and half of the values are more than the median. It is probably the best measure of center to use in a skewed distribution.