Answer:
1.5% x 412 = 618?
Step-by-step explanation:
Answer:
x=63
Step-by-step explanation:
<em>Subtract by 150 from both sides of equation.</em>
<em>150-x-150=87-150</em>
<em>Simplify.</em>
<em>87-150=-63</em>
<em>-x=-63</em>
<em>Divide by -1 from both sides of equation.</em>
<em>-x/1=-63/-1</em>
<em>Simplify, to find the answer.</em>
<em>-63/-1=63</em>
<em>x=63 is the correct answer.</em>
<em>I hope this helps you, and have a wonderful day!</em>
Answer:
The reason why standard deviation of the entire class is greater than standard deviation of males and females considered separately, is that mean values for males and females are different from each other.
Step-by-step explanation:
The concept of mean is well represented by the following formula
mean = , where x1, x2, xn are the observations and N is the number of observations (population).
Standard deviation represents the distance between each observation and the mean of the population (all observations). The formula for this parameter is:
Standard deviation =√[((x1 - x)² + (x2-x)² + ....+ (xn-x)²)/N-1], where x1, x2,..., xn are the observations and x is the mean value.
In this case you have that each height registered is an observation and the number of observations represents the N value. As you can see if the mean for males is different from that of females their standard deviation will be different too. Usually males have heigths greater than that of females (1.77 vs 1.64, in USA for example), and heights inside each group will be more similar than between groups. Then, when you mix all observation there will be an increase in standard deviation, because you are mixing very different heigths
Answer:
The correct answer is letter "B": You use information from a first sample for collecting a subsequent subsample for further study.
Explanation:
Multi-phase sampling is a strategy by which a large number of data under study is taken, then a subsample of that pool is taken, and after that, another smaller subsample is taken in an attempt to count with samples that best might represent the whole population. Usually, the process takes collecting two different samples, but it can be applied as many times as necessary.