Which of the following statements best describes the null hypothesis?
Explanation
The null hypothesis (H0) is the statement to be tested, typically postulating no effect or difference, which the researcher hopes to reject in favor of the alternative hypothesis.
Other questions
A researcher wants to test if the mean return on a portfolio is different from zero. The appropriate set of hypotheses is:
A Type I error is defined as:
The power of a hypothesis test is defined as the probability of:
If the significance level of a test is 5 percent and the probability of a Type II error is 20 percent, the power of the test is:
For a two-tailed test using the standard normal distribution at the 5 percent level of significance, the critical z-values are:
A test statistic is calculated as:
The p-value is best described as:
An analyst conducts a hypothesis test and calculates a p-value of 0.03. If the chosen significance level is 0.05, the analyst should:
Which of the following distributions is appropriate for testing a hypothesis about a population mean when the variance is unknown and the sample is large?
A sample of 25 observations has a mean of 10 and a standard deviation of 4. The researcher wants to test if the population mean is greater than 8 at the 5 percent significance level. The standard error of the sample mean is:
Using the data from the previous question (Mean=10, Hypothesized=8, SE=0.8), the calculated test statistic is:
In a one-tailed test with 24 degrees of freedom at the 5 percent significance level, the critical t-value is 1.711. Based on a calculated t-statistic of 2.50, the researcher should:
The distinction between statistical significance and economic significance implies that:
When testing the difference between two population means using two independent samples, the degrees of freedom for the t-test (assuming equal variances) are calculated as:
A paired comparisons test is most appropriate when:
For a paired comparisons test with 20 pairs of observations, the degrees of freedom are:
To test the hypothesis that the variance of a normally distributed population is equal to a specific value, the appropriate test statistic is based on the:
A sample of 15 observations has a standard deviation of 6. The researcher wants to test if the population variance is equal to 25. The calculated chi-square statistic is closest to:
The F-statistic used to test the equality of two variances is calculated as:
Sample A has a variance of 25 (n=21) and Sample B has a variance of 16 (n=16). The calculated F-statistic to test if the variances are equal is:
To test the hypothesis that the population correlation coefficient equals zero, the appropriate test statistic follows a:
A sample of 42 observations shows a correlation coefficient of 0.35. The researcher wants to test if the correlation is different from zero. The degrees of freedom for this test are:
Nonparametric tests are preferred when:
The Spearman rank correlation coefficient is best described as:
A contingency table is used to test:
In a chi-square test for independence with 3 rows and 3 columns, the degrees of freedom are:
Data snooping bias refers to:
Survivorship bias in mutual fund studies typically leads to:
Look-ahead bias occurs when:
If a test statistic is 1.80 and the critical value is 1.65 (one-tailed upper), the decision is to:
Which test statistic is appropriate to test if the mean of a population is equal to zero when the variance is unknown and n=20?
If the null hypothesis is H0: mean <= 0, the alternative hypothesis Ha is:
The critical value for a two-tailed z-test at the 1 percent significance level is closest to:
A confidence interval for a population parameter can be expressed as:
If a 95 percent confidence interval for a mean does not include zero, then:
When the sample size is small and the population is not normally distributed, which test statistic should be used?
For a test of the equality of two variances, the critical F-value depends on:
A researcher assumes that two samples are independent, normally distributed, and have equal variances. The pooled variance is calculated as:
With 20 tests at the 10 percent significance level, the expected number of false positives (Type I errors) if the null hypothesis is true for all is:
Using a higher significance level (e.g., 10 percent instead of 5 percent) will:
A chi-square test for a single variance is:
If a calculated t-statistic is -2.4 and the critical values are +/- 2.1, the decision is:
In a contingency table, the expected frequency for a cell is calculated as:
Which of the following is an example of a nonparametric test?
If sample data has a t-statistic of 2.363 for a correlation test with 40 degrees of freedom (critical value 2.021), we conclude:
Economic significance differs from statistical significance in that:
When testing if the mean of a single population is 50, the null hypothesis should be stated as:
If a researcher decreases the probability of a Type I error (alpha), the probability of a Type II error (beta) will typically:
The test statistic for the Spearman rank correlation follows which distribution when n > 30?