ANSWER:
A ) It also increases.
EXPLANATION:
When the measure of angle A increases im the trianes, the measure of angle A on line p also increases. This is angle A in the triangle and angle A on line p are equivalent to each other. Hence, if there is an increase to one of the angle As then there is also an increase to the other.
Therefore, the answer must be:
A ) It also increases.
Answer:
it is b
Step-by-step explanation:
Answer:
-10.2n - 1
Step-by-step explanation:
We have two expressions in variable n and we have to add the two expressions.
An important thing to note is that only like terms can be added. i.e. the term with "n" can only be added or subtracted to the term with "n". Similarly a constant can only be added or subtracted to a constant.
Thus, the two given expressions add up to -10.2n - 1

You wan't to get it into a format of (x+a)(x+b)=0
where a+b = 3 (the one from the 3x)
and where a*b= -4 (from the last -4)
(x+4)(x-1)=0
See how 4+(-1) = 3 and (4)(-1) = -4
now find what values of x would make the equation equal 0
x=-4
(-4+4)(-4-1) = (0)(-5) = 0
x=1
(1+4)(1-1) = (5)(0) = 0
Sampling errorThe natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter.distribution of sample means<span>The collection of sample means for all of the possible random samples of a particular size (n) that can be obtained from a population.</span>sampling distributionA distribution of statistics obtained by selecting all of the possible samples of a specific size from a population.central limit theorem<span>For any population with mean μ and standard deviation σ, the distribution of sample means for sample size n will have a mean of μ and a standard deviation of σ/√n and will approach a normal distribution as n approaches infinity.</span><span>expected value of M</span>The mean of the distribution of sample means is equal to the mean of the population of scores, μ, and is called this.<span>standard error of M</span><span>The standard deviation for the distribution of sample means. Identified by the symbol σ˯M. This standard error provides a measure of how much distance is expected on average between a sample mean (M) and the population mean (μ).</span>law of large numbers<span>States that the larger the sample size (n), the more probable it is that the sample mean is close to the population mean.</span>