The median is the most appropriate center when the distribution is very skewed or if there are many outliers.
median
The binomial distribution.
mean (average) temperature median income, mediian home prices, salary, etc. mode is the most likely occurence of an event. If the distribution of outcomes is symmetrical, then mean median mode
Interval-Ratio can use all three measures, but the most appropriate should be mean unless there is high skew, then median should be used.
Of these three, the median is most resistant.
The most appropriate measures of center for a data set depend on its distribution. If the data is normally distributed, the mean is a suitable measure of center; however, if the data is skewed or contains outliers, the median is more appropriate. For measures of spread, the standard deviation is ideal for normally distributed data, while the interquartile range (IQR) is better for skewed data or when outliers are present, as it focuses on the middle 50% of the data.
In this dataset, the median and mode are both appropriate measures of center. The median is the middle value when the numbers are arranged in numerical order, while the mode is the value that appears most frequently. The mean, or average, can also be calculated for this dataset, but it is not mentioned in the given options.
median
The binomial distribution.
It depends on what you mean by a centre. The most likely answer is a median.
Plotting data in a frequency distribution shows the general shape of the distribution and gives a general sense of how the numbers are bunched. Several statistics can be used to represent the "center" of the distribution. These statistics are commonly referred to as measures of central tendency.
A positively skewed or right skewed distribution means that the mean of the data falls to the right of the median. Picturewise, most of the frequency would occur to the left of the graph.
We have three measures of center—mean, median, and mode—because they each provide different perspectives on data sets. The mean offers an average value, the median gives the middle point, and the mode identifies the most frequently occurring value. Together, they help capture the data's distribution, especially when it contains outliers or is skewed. This comprehensive view aids in better understanding and analysis of data.
The mode is the most probable value. Often, you determine the mode by plotting the experimental probability distribution, and finding the peak value. The mode is not necessarily the same as the mean nor the median, unless the distribution is symmetrical.
You may be most familiar with the normal distribution (the Bell-shaped curve). The mean, mode and median of this distribution are all the same because it is symmetric. If, however, you take a sample from a distribution that is asymmetric in some way then the mean, mode and median will differ. You would need to decide which of these more effectively characterises the population. Then you would compute that descriptive statistic.
mean (average) temperature median income, mediian home prices, salary, etc. mode is the most likely occurence of an event. If the distribution of outcomes is symmetrical, then mean median mode
median