QUESTION: 993

A researcher has rejected the null hypothesis. The p-value in the test must be:

less than the significance level.
more than 1-significance level.
less than 1-significance level.
more than the significance level.

Answer(s): A

Explanation:

The lowest significance level at which the null hypothesis can be rejected is called the p-value of the test. Thus, if the p-value is less than the significance level, the null hypothesis can be rejected at that significance level. To fix this in your mind, think about 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. For e.g., suppose the p-value for a given sample turns out to be 3%. Then, if you reject the null, the probability that you have made an error in rejecting it is at most 3%. Clearly, if a critic asked you, "Is the probability that you have made an error less than 5%?" your answer would be, "yes." The critic will then conclude that your test is significant at the 5% level and perhaps even at a lower level.

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QUESTION: 994

What deposit today is needed to have $2,000 in 4 years, assuming the money will earn interest at 5% per year, compounded monthly?

$2,000.00
$1,290.81
$584.57
$1,638.14
$1,934.02

Answer(s): D

Explanation:

On the BAII Plus, press 48 N, 5 divide 12 = I/Y, 0 PMT, 2000 FV, CPT PV. On the HP12C, press 48 n, 5 ENTER 12 divide i, 0 PMT, 2000 FV, PV. Make sure the BAII Plus has the P/Y value set to 1.

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QUESTION: 995

An economic researcher estimates the following regression between the annual income, I, of a family and the amount it spends on consumption goods, C:
C = 2,000 + 0.65 I + error term
If the R-square of the regression is just 0.3, estimate the amount that a family with an income of 50,000 will spend on consumption.

34,500
none of these answers
32,500
2,000

Answer(s): A

Explanation:

With the given regression, the amount that a family with an income of 50,000 will spend on consumption equals 2,000 + 0.65*50,000 = 34,500.

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QUESTION: 996

Which of the following is/are true?

For a given level of significance, it becomes harder to reject the null hypothesis as the sample size decreases.
II. For a given sample size, it becomes harder to reject the null hypothesis as the significance level decreases.
III. It is easier to reject the null hypothesis the lower the R-square.
I only
II only
I, II & III
III only
I & III
II & III
I & II

Answer(s): G

Explanation:

As the sample size increases, it becomes easier to test whether the null hypothesis can be rejected at the specified significance level (Intuitively, it is harder for a false hypothesis to hide its falsity when there are a larger number of observations testing its veracity). In fact, the critical t-statistic required to reject the null decreases as the sample size increases for a given level of significance.
A higher significance level makes it easier to reject the null hypothesis. This is because you are enforcing a looser standard on rejecting the null (recall that the significance level represents the probability thatyou have rejected the null when, in fact, it is true). In fact, significance level and critical t-statistic are inversely related.
R-square is not used in hypothesis testing but in regression analysis, though it does not measure the significance of a regression. A regression with a very low R-square can be highly significant; the low R-square only implies that the behavior of the dependent variable is governed largely by random noise.

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Free CFA-Level-I Exam Braindumps (page: 249)

QUESTION: 993

Explanation:

QUESTION: 994

Explanation:

QUESTION: 995

Explanation:

QUESTION: 996

Explanation: