Reading 6: Hypothesis Testing
50 questions available
Errors are an intrinsic part of testing. A Type I error involves rejecting a true null hypothesis, with the probability denoted by alpha (the significance level). A Type II error involves failing to reject a false null hypothesis. The power of a test is the probability of correctly rejecting a false null hypothesis. The relationship between confidence intervals and hypothesis tests is also explored; a two-tailed test at the alpha significance level is complementary to a (1 - alpha) confidence interval.
Key Points
- Null hypothesis (H0) represents the 'no effect' or status quo and includes the equality condition.
- Alternative hypothesis (Ha) is what the researcher typically wants to prove.
- Type I error: Rejecting H0 when it is true (Probability = alpha).
- Type II error: Failing to reject H0 when it is false (Probability = beta).
- Power of a test = 1 - Probability of Type II error.
- A statistically significant result does not necessarily imply economic significance.
Key Points
- The p-value is the probability of obtaining a test statistic as extreme as the one observed, assuming H0 is true.
- Reject H0 if the p-value is less than the significance level (alpha).
- Use z-statistic when population variance is known.
- Use t-statistic when population variance is unknown (df = n - 1).
- For large samples (n >= 30), the t-test and z-test produce similar results.
Key Points
- Difference in means test (independent samples) uses a t-statistic based on pooled variance if variances are assumed equal.
- Degrees of freedom for independent means test: n1 + n2 - 2.
- Paired comparisons test is used for dependent samples (e.g., before/after).
- The paired test analyzes the mean of the differences (d-bar) against a hypothesized difference (usually 0).
- Degrees of freedom for paired test: n - 1 (where n is the number of pairs).
Tests for correlation determine if the population correlation coefficient differs from zero, using a t-statistic with (n - 2) degrees of freedom. The section also introduces the Spearman rank correlation coefficient for nonparametric tests of correlation. Finally, the chi-square test for independence uses a contingency table to determine if two categorical characteristics are independent.
Key Points
- Test for single variance uses the chi-square statistic (df = n - 1).
- Test for equality of two variances uses the F-statistic (s1 squared / s2 squared).
- Parametric test for correlation uses a t-statistic (df = n - 2).
- Spearman rank correlation is a nonparametric test for ranked data.
- Test for independence uses a chi-square contingency table analysis.
Questions
Which of the following statements best describes the null hypothesis?
View answer and explanationA researcher wants to test if the mean return on a portfolio is different from zero. The appropriate set of hypotheses is:
View answer and explanationA Type I error is defined as:
View answer and explanationThe power of a hypothesis test is defined as the probability of:
View answer and explanationIf 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:
View answer and explanationFor a two-tailed test using the standard normal distribution at the 5 percent level of significance, the critical z-values are:
View answer and explanationA test statistic is calculated as:
View answer and explanationThe p-value is best described as:
View answer and explanationAn analyst conducts a hypothesis test and calculates a p-value of 0.03. If the chosen significance level is 0.05, the analyst should:
View answer and explanationWhich of the following distributions is appropriate for testing a hypothesis about a population mean when the variance is unknown and the sample is large?
View answer and explanationA 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:
View answer and explanationUsing the data from the previous question (Mean=10, Hypothesized=8, SE=0.8), the calculated test statistic is:
View answer and explanationIn 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:
View answer and explanationThe distinction between statistical significance and economic significance implies that:
View answer and explanationWhen 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:
View answer and explanationA paired comparisons test is most appropriate when:
View answer and explanationFor a paired comparisons test with 20 pairs of observations, the degrees of freedom are:
View answer and explanationTo 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:
View answer and explanationA 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:
View answer and explanationThe F-statistic used to test the equality of two variances is calculated as:
View answer and explanationSample 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:
View answer and explanationTo test the hypothesis that the population correlation coefficient equals zero, the appropriate test statistic follows a:
View answer and explanationA 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:
View answer and explanationNonparametric tests are preferred when:
View answer and explanationThe Spearman rank correlation coefficient is best described as:
View answer and explanationA contingency table is used to test:
View answer and explanationIn a chi-square test for independence with 3 rows and 3 columns, the degrees of freedom are:
View answer and explanationData snooping bias refers to:
View answer and explanationSurvivorship bias in mutual fund studies typically leads to:
View answer and explanationLook-ahead bias occurs when:
View answer and explanationIf a test statistic is 1.80 and the critical value is 1.65 (one-tailed upper), the decision is to:
View answer and explanationWhich test statistic is appropriate to test if the mean of a population is equal to zero when the variance is unknown and n=20?
View answer and explanationIf the null hypothesis is H0: mean <= 0, the alternative hypothesis Ha is:
View answer and explanationThe critical value for a two-tailed z-test at the 1 percent significance level is closest to:
View answer and explanationA confidence interval for a population parameter can be expressed as:
View answer and explanationIf a 95 percent confidence interval for a mean does not include zero, then:
View answer and explanationWhen the sample size is small and the population is not normally distributed, which test statistic should be used?
View answer and explanationFor a test of the equality of two variances, the critical F-value depends on:
View answer and explanationA researcher assumes that two samples are independent, normally distributed, and have equal variances. The pooled variance is calculated as:
View answer and explanationWith 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:
View answer and explanationUsing a higher significance level (e.g., 10 percent instead of 5 percent) will:
View answer and explanationA chi-square test for a single variance is:
View answer and explanationIf a calculated t-statistic is -2.4 and the critical values are +/- 2.1, the decision is:
View answer and explanationIn a contingency table, the expected frequency for a cell is calculated as:
View answer and explanationWhich of the following is an example of a nonparametric test?
View answer and explanationIf sample data has a t-statistic of 2.363 for a correlation test with 40 degrees of freedom (critical value 2.021), we conclude:
View answer and explanationEconomic significance differs from statistical significance in that:
View answer and explanationWhen testing if the mean of a single population is 50, the null hypothesis should be stated as:
View answer and explanationIf a researcher decreases the probability of a Type I error (alpha), the probability of a Type II error (beta) will typically:
View answer and explanationThe test statistic for the Spearman rank correlation follows which distribution when n > 30?
View answer and explanation