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Flashcards

Quantitative methods 1

Henry Lynch (NZ) CFA Business Analyst English 19 cards

Cards in this deck (19)

  1. 1Which statistic should you use when sampling from a normal distribution with a known variance, and the sample size is small?z-statistic
  2. 2Which statistic should you use when sampling from a normal distribution with a known variance, and the sample size is large?z-statistic
  3. 3Which statistic should you use when sampling from a normal distribution with an unknown variance, and the sample size is small?t-statistic
  4. 4Which statistic should you use when sampling from a normal distribution with an unknown variance, and the sample size is large?t-statistic (or z-statistic, but t-statistic is more conservative)
  5. 5Which statistic should you use when sampling from a non-normal distribution with a known variance, and the sample size is small?none
  6. 6Which statistic should you use when sampling from a non-normal distribution with a known variance, and the sample size is large?z-statistic
  7. 7Which statistic should you use when sampling from a non-normal distribution with an unknown variance, and the sample size is small?none
  8. 8Which statistic should you use when sampling from a non-normal distribution with an unknown variance, and the sample size is large?t-statistic (or z-statistic, but t-statistic is more conservative)
  9. 9Type 1 errorThe rejection of the null hypothesis when it is true
    (the probability of a type 1 error is the significance level)
  10. 10Type 2 errorWhen one fails to reject the null hypothesis that is actually false
  11. 11The power of a test1 minus the probability of a type 2 error
  12. 12When is the use of the Mann-Whitney U-test and Wilcoxon signed-rank test most appropriate?The Mann-Whitney U-test is most appropriate for tests of differences in means of nonparametric data such as analysts rankings.
    The Wilcoxon signed-rank test is most appropriate for testing the significance of a single mean or mean differences (paired comparisons test) for nonparametric data.
  13. 13Describe when we would use a multivariate distribution...Multivariate distributions specify the probabilities for a group of related random variables. A portfolio of technology stocks represents a group of related assets. Accordingly, statistical relationships must be considered, resulting in the need to use a multivariate normal distribution.
  14. 14The total number of parameters that fully characterizes a multivariate normal distribution for the returns on two stocks is:5
    A bivariate normal distribution (two stocks) will have two means, two variances and one correlation. A multivariate normal distribution for the returns on n stocks will have n means, n variances and n(n – 1)/2 distinct correlations.
  15. 15How many outcomes are possible in a Bernoulli trial?2
  16. 16What is an unbiased estimator?An unbiased estimator is one for which the expected value equals the parameter it is intended to estimate.
  17. 17What is a consistent estimator?A consistent estimator is one for which the probability of estimates close to the value of the population parameter increases as sample size increases. More specifically, a consistent estimator’s sampling distribution becomes concentrated on the value of the parameter it is intended to estimate as the sample size approaches infinity.
  18. 18What is an out-of-sample stest?An out-of-sample test is used to investigate the presence of data-mining bias. Such a test uses a sample that does not overlap the time period of the sample on which a variable, strategy, or model was developed.
  19. 19When evaluating mean differences between two dependent samples, the most appropriate test is a:paired comparisons test

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Business Analyst CFA Flashcards on Quantitative methods 1, created by Henry Lynch (NZ) on 11/10/2021.
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