A -score indicates whether a particular value is typical for a population or data set.  The closer the -score is to 0, the closer the value is to the mean of the population and the more typical it is.  The -score is calculated by subtracting the mean of a population from the particular value in question, then dividing the result by the population's standard deviation. 

The -score indicates how close a particular value is to the population mean and whether the value is above or below the mean.  A positive -score is always above the mean and a negative -score is always below it.  Here, we know the value is below the mean because we have a negative -score.

A Z-score indicates whether a particular value is typical for a population or data set.  The closer the Z-score is to 0, the closer the value is to the mean of the population and the more typical it is.  The Z-score is calculated by subtracting the mean of a population from the particular value in question, then dividing the result by the population's standard deviation.

Probability of drawing first ace of hearts:

Probability of drawing second ace of hearts:

Multiply both probabilities by each other:

Start with 52 cards, probability of drawing first king:

Now you have 51 cards. Probability of drawing second king:

Now you have 50 cards. Probability of drawing third king:

Multiply all probabilities:

In a standard deck of cards:

There are cards in a standard deck:  cards in suits.  There are face cards (King, Queen, Jack) in each suit, so there are total face cards.

Thus the probability of choosing a single face card is or .

A box and whisker plot separates the data into quartiles so that each quartile has an equal number of data points. The box indicates the interquartile range, that is, the top line of the box is the third quartile and the bottom line of the box is the second quartile. The line separating the second and third quartiles indicates the median. The lines outside of the box indicate the outer-quartiles (first and fourth).

The data points follow an overall linear trend, as opposed to being randomly distributed. Though there are a few outliers, there is a general relationship between the two variables.

A line could accurately predict the trend of the data points, suggesting there is a linear correlation. Since the y-values decrease as the x-values increase, the correlation must be negative. We can see that a line connecting the upper-most and lower-most points would have a negative slope.

An exponential relationship would be curved, rather than straight.

The range is the simplest measurement of the difference between values in a data set.  To find the range, one simply subtracts the lowest value from the greatest value, ignoring the others.  Here, the lowest value is 155 and the greatest is 720.