This section tests your ability to work with data, solve measures of central tendency and spread problems, as well as identify data relationships in order to make predictions. You need to know the difference between correlation and causation and solve simple probability problems.
Let’s discuss some concepts that will more than likely appear on the test.
The Mathematics test will require you to work with measures of central tendencies, such as mean, median, and mode. For an example, take a look at the following question:
This list shows the price of jackets in a store last month: $34, $45, $46, $48, $56
This is the current list of jacket prices: $4, $45, $44, $48, $56
In the second list, which price is the outlier? Does the outlier change the mean, the median, or the mode?
In this example, the $4 price is the outlier, because it is drastically different from the other prices. The outlier does not affect the mode (frequency of appearance) of the prices. It also does not affect the median (midpoint) price, because the number of prices remains the same on both lists. It does, however, affect the mean (average) price. The mean price of the jackets in the first list is $45.80, and the mean price of jackets in the second list is $39.40. You can find the mean of each list by adding the price of each jacket and then dividing the sum by the number of items in the list (5).
In statistics, a probability distribution is used to describe the likelihood of an outcome.
A discrete probability distribution may appear as a formula or a table listing all values that a discrete variable could be. Discrete variables have a finite and countable number of values and continuous variables do not.
Cumulative probability distributions describe the probability that the value of a variable will fall within a specific range.
A uniform probability distribution describes a situation in which every value of a random variable has an equal chance of occurring. For example, flipping a coin would have a uniform probability distribution. Each of the two outcomes (heads or tails) is equally likely to occur. Here’s an example.
Imagine that you will flip a coin twice.
What value would correctly replace a in the distribution table?
The value .5 would correctly replace a because the probability values would then equal 100%.