Answer:
116°
Step-by-step explanation:
(there are 2 right angles)
90 + 90 = 180
180 + 64 = 244
(a quadrilateral adds up to 360°)
360 - 244 = 116
C is the answer you are looking for.
Q = -60 and P ≠ 32 will result in an equation with no solutions. (Both conditions must be met.)
_____
For Q = -60 and P = 32, there will be an infinite number of solutions. For any other values of Q and P, the solution is
.. x = (32 -P)/(Q +60)
The answer is boxed in. follow the arrows.
In statistics, the standard deviation deviation may be a measure of the quantity of variation or dispersion of a group of values. The margin of error may be a statistic expressing the number of sampling error within the results of a survey. The correlation could be a statistical measure of the strength of the connection between the relative movements of two variables.
Given nothing and that we need to explain standard deviation. margin of error, correlation coefficient .
Standard deviation
In statistics, the standard deviation may be a measure of the number of variation or dispersion of a group of values. an occasional variance indicates that the values tend to be near the mean of the set, while a high variance indicates that the values are detached over a wider range.
Formula: ![\sqrt{(x-x bar)^{2}/N }](https://tex.z-dn.net/?f=%5Csqrt%7B%28x-x%20bar%29%5E%7B2%7D%2FN%20%7D)
where x bar is mean and N is size of population.
Margin of error
The margin of error may be a statistic expressing the quantity of sampling error within the results of a survey. The larger the margin of error, the less confidence one should have that a poll result would reflect the results of a survey of the complete population.
Formula for M=z*s/![\sqrt{n}](https://tex.z-dn.net/?f=%5Csqrt%7Bn%7D)
here z is z value of Z score , s is variance , n is that the sample size.
Correlation coefficient
In statistics, the Pearson parametric statistic ― also called Pearson's r, the Pearson product-moment parametric statistic, the bivariate correlation, or colloquially simply because the coefficient of correlation ― could be a measure of linear correlation between two sets of information.
Formula=∑
∑
∑![(y_{i}-ybar) ^{2}](https://tex.z-dn.net/?f=%28y_%7Bi%7D-ybar%29%20%5E%7B2%7D)
Learn more about correlation coefficient at brainly.com/question/4219149
#SPJ4