Concept:Mean: Mean (average) is the sum of all quantities divided by no of quantities of the data set.Mode: It is the most repeated value in the data set.Median: Median is the middlemost value of the data set.Skewness:The skewness is a measure of the asymmetry of the probability distribution assuming a unimodaldistribution (assuming there is only one peak in the distribution of values). We can say that theskewness indicates how much our underlying distribution deviates from the normal distributionsince the normal distribution has a skewness of 0. Generally, we have three types of skewness.Symmetrical: When the skewness is close to 0 and the mean is almost the same as the medianNegative skew:When the left tail of the histogram of the distribution is longer and the majority of the observations are concentrated on the right tail.In this case, we can use also the term "left-skewed" or "left-tailed" and the median is greater than the mean.Positive skew:When the right tail of the histogram of the distribution is longer and the majority of the observations are concentrated on the left tail.In this case, we can use also the term "right-skewed" or "right-tailed" and the median is less than the mean.Explanation:We know that when the left tail of the histogram of the distribution is longer and the majority of the observations are concentrated on the right tail. In this case, we can use also the term "left-skewed" or "left-tailed". and the median is greater than the mean.So, the frequency curve corresponding to the data obtained is skewed to the left and the graph obtained is as below:For the above left-skewed curve, Mode > Median > Mean.? Mode > Median > Mean for left-skewed curve.