Correlation between x & y is 0.6125.
In probability theory and statistics, the cumulative distribution function of a real-valued random variable X, or simply the distribution function of X weighted by x, is the probability that X takes a value less than or equal to x.
The cumulative distribution function (CDF) of a random variable X is defined as FX(x)=P(X≤x) for all x∈R. Note that the subscript X indicates that this is the CDF of the random variable X. Also note that the CDF is defined for all x∈R. Let's look at an example.
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S is independent variable and T is the dependent variable
Answer:
It's -9/4 or -2 1/4. please mark me brainliest <3
Step-by-step explanation:
1) label x1, y1, x2, and y2.
x1 y1 x2 y2
(-12, 16) (-4,-2)
2) Remember the formula is y2-y1
--------
x2-x1
3) substitute
-2-16
--------
-4-(-12)
4) two minuses (negatives) is a positive (+)
so,
-2-16 -18
---------= --------
-4+12 8
5) simplify
-18 divided by 2 -9
----- = ------- or -2 1/4
8 divided by 2 4
Y is the easiest to fix because it has no coefficient, and is therefore the easiest to set on the other side of the equation by itself