Final answer:
To assess the central tendency of pay, you would use the a. mean, which is the sum of all values divided by the number of values. In symmetrical distributions, mean, median, and mode coincide, but the median might be more appropriate for skewed distributions. Other measures mentioned like dispersion, standard deviation, quartiles, and deciles are related to the spread of data rather than central tendency.
Step-by-step explanation:
When assessing the central tendency of pay (or any other numerical data), the measure you would use is a. mean. The mean is the arithmetic average and is calculated by adding all the values together and dividing by the number of values.
However, when the data is skewed or has outliers, the mean might not be the best measure of central tendency; in such cases, the median may be more appropriate, which is the middle value when the data is ordered from least to greatest.
In a symmetrical distribution, the mean, median, and mode are all equal. Dispersion, standard deviation, quartiles, and deciles are measures of variability or spread within a dataset, not central tendency. The interquartile range (IQR) is the difference between the third and first quartile and describes the middle 50% of the data set.
To calculate the mean and standard deviation from a given set of data, one would sum up all the data points, divide by the number of data points to find the mean, and then use the mean to calculate the standard deviation, which measures the average distance of data points from the mean. Finally, two standard deviations above the mean can be calculated by adding twice the standard deviation to the mean.