- CFA Exams
- 2023 Level I
- Topic 1. Quantitative Methods
- Learning Module 6. Hypothesis Testing
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Learning Outcome Statements PDF Download
| 1. Introduction define a hypothesis, describe the steps of hypothesis testing, and describe and interpret the choice of the null and alternative hypotheses; | |
| 2. Null Hypothesis and Alternative Hypothesis compare and contrast one-tailed and two-tailed tests of hypotheses; | |
| 3. Test Statistic and Significance Level explain a test statistic, Type I and Type II errors, a significance level, and how significance levels are used in hypothesis testing, and the power of a test; | |
| 4. Type I and Type II Errors in Hypothesis Testing explain a test statistic, Type I and Type II errors, a significance level, and how significance levels are used in hypothesis testing, and the power of a test; | |
| 5. The Power of a Test explain a test statistic, Type I and Type II errors, a significance level, and how significance levels are used in hypothesis testing, and the power of a test; | |
| 6. The Decision Rule explain a decision rule and the relation between confidence intervals and hypothesis tests, and determine whether a statistically significant result is also economically meaningful; explain and interpret the p-value as it relates to hypothesis testing; | |
| 7. Multiple Tests and Interpreting Significance describe how to interpret the significance of a test in the context of multiple tests; | |
| 8. Tests Concerning a Single Mean identify the appropriate test statistic and interpret the results for a hypothesis test concerning the population mean of both large and small samples when the population is normally or approximately distributed and the variance is 1) known or 2) unknown; | |
| 9. Tests Concerning Differences between Means with Independent Samples identify the appropriate test statistic and interpret the results fora hypothesis test concerning the population mean of both large and small samples when the population is normally or approximately normally distributed and the variance is (1) known or (2) unknown; identify the appropriate test statistic and interpret the results for a hypothesis test concerning the equality of the population means of two at least approximately normally distributed populations based on independent random samples with equal assumed variances; | |
| 10. Tests Concerning Differences between Means with Dependent Samples identify the appropriate test statistic and interpret the results for a hypothesis test concerning the mean difference of two normally distributed populations; | |
| 11. Testing Concerning Tests of Variances (Chi-Square Test) identify the appropriate test statistic and interpret the results for a hypothesis test concerning 1) the variance of a normally distributed population, and 2) the equality of the variances of two normally distributed populations based on two independent random samples; | |
| 12. Tests Concerning the Equality of Two Variances (F-Test) identify the appropriate test statistic and interpret the results for a hypothesis test concerning 1) the variance of a normally distributed population, and 2) the equality of the variances of two normally distributed populations based on two independent random samples; | |
| 13. Parametric vs. NonParametric Tests compare and contrast parametric and nonparametric tests, and describe situations where each is the more appropriate type of test; | |
| 14. Tests Concerning Correlation explain parametric and nonparametric tests of the hypothesis that the population correlation coefficient equals zero, and determine whether the hypothesis is rejected at a given level of significance; | |
| 15. Test of Independence Using Contingency Table Data explain tests of independence based on contingency table data. |
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