Final answer:
A histogram is right skewed if the tail extends to the right, with most data clustering on the left, and the mode, median, and mean increase in that order. This indicates that the higher values are more spread out.
Step-by-step explanation:
To determine if a histogram is right skewed, observe where the majority of the data points lie and the direction in which the tail extends. A right-skewed histogram, also known as a positively skewed histogram, will have a tail that extends to the right. In other words, the greater values are more spread out, and the bulk of the data clusters to the left, with fewer, higher-value outliers pulling the mean to the right.
The characteristics of a right-skewed distribution often include a mode that is less than the median, which in turn is less than the mean. Therefore, by calculating these three statistics, you can gain insights into the skewness of the data. Graphically, if the left side of the graph appears more compact and the right side looks stretched or 'pulled out', then the data are skewed to the right.
For example, if you have a dataset with the values 6, 7, 7, 7, 7, 8, 8, 8, 9, 10, you'll likely find that the mode is 7, while the median and mean are greater than 7, pointing towards a right-skewed distribution.