The probability that a mutual fund will generate a positive return in the next 12 months is called:
Answer(s): B
An unconditional probability takes the form of P(A), the probability that an event (A) will happen. It is unconditional because it is not conditioned on any other event.
For a positively skewed, unimodal distribution, which of the following relationships holds?
Answer(s): C
In a positively skewed distribution, very large values are more common than correspondingly small values. This skews the distribution to the right, moving the mean to the right of the median.
If alpha = .05 for a two-tailed test, how large is the acceptance area?
The acceptance region is the area in between the two critical values. In this case it is 1 - 0.05 = 0.95.
Which of the is/are false?
You can think of the p-value as the maximum probability that the null hypothesis is true despite observing the value of the test statistic that you have in the sample at hand. Thus, the lower the p- value, the greater is your confidence in rejecting the null hypothesis. The significance level represents an upper bound on the probability that the null hypothesis is true given the observed sample and the testing procedure. Hence, if you reject the null at the 5% significance level, for e.g., then the probability that the null is true despite your statistical evidence to the contrary could be as high as 5% (but no more, under the assumptions of the test). A Type II error refers to the event that we will fail to reject the null when it is false. The higher the probability of a Type II error, the lower the chance of rejecting the null when it is false.
Mr. and Mrs. Jones live in a neighborhood where the mean family income is $45,000 with a standard deviation of $9,000. Mr. and Mrs. Smith live in a neighborhood where the mean is $100,000 and the standard deviation is $30,000. What is the relative dispersion of the family incomes in the two neighborhoods?
Answer(s): A
The coefficient of variation = (s*100)/mean. Jones: 9000*100/45,000 = 20%. Smith: 30,000*100/100,000 = 30% .
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