Which measure of central tendency is used to determine the average annual percent increase?
Answer(s): E
The formulaic presentation of the geometric mean is suited for calculating percentage changes. The geometric mean of a set of n positive numbers and is defined as the nth root of the product of the n numbers The two main uses of the geometric mean (GM) are:1. To average percents, indexes, and relatives, and2. To determine the average percent increase in sales, production or other business or economic series from one time period to another.
Given the following four points: (-2, 0), (-1,0), (0,1), (1, 1) and (2, 3)What is the standard error of the regression line estimate?
Answer(s): C
For this, you need to create tables with columns for X,Y,XY,X^2,Y' and Y-Y'. This will be as follows.XYXY X^2 Y'Y-Y'-2004-0.40.4-10010.3-0.301001011111.7-0.723642.40.6Sum057100N=5.The regression equation is Y' = a + bX.The standard error of estimate iss = sq. root of [S(Y-Y')^2/n-2] where S stands for "Sum of." S = [0^2/3] = 0.
A study of the opinion of designers with respect to the primary color most desirable for use in executive officesshowed that:Primary Color Number of OpinionsRed 92Orange 86Yellow 46Green 91Blue 37Indigo 46Violet 2What is the probability that a designer does not prefer yellow?
Answer(s): B
There are 400 opinions. 46/400 prefer yellow. So 1 - 46/400 = 177/200 = 0.885 does not prefer yellow.
What is the median of 26, 30, 24, 32, 32, 31, 27 and 29?
Ordering the numbers we have 24,26,27,29,30,31,32,32. Since there is an even number of observations (8), the median is the average of the two middle observations (29 + 30)/2 = 29.5.
If the significance level of a test is the probability of incorrectly rejecting the null hypothesis, then the "power of a test" is defined as which of the following? Choose the best answer.
If the significance level of a test is the probability of incorrectly rejecting the null hypothesis (a Type I error), then the power of the test is defined as the probability of correctly rejecting the null hypothesis. In other words, the power of a test is equal to (1 - the probability of a Type II error). The standard method of hypothesis testing involves stating only the significance level, which is equal to the probability of a Type I error.
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