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CFA Level 1 - Quantitative Methods > Hypothesis Testing > Flashcards

Flashcards in Hypothesis Testing Deck (17)
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1
Q

The statistical assessment of a statement or idea regarding a population

A

Hypothesis Testing

2
Q

The hypothesis that the researcher wants to reject, denoted Ho

A

Null Hypothesis

* The hypothesis that is actually tested and is the basis for the selection of the test statistics.

3
Q

Two-tailed test for the population mean

A
Ho = u = uo,
Ha = u =/ uo
4
Q

One-tailed test for the population mean

A

Ho: u <= uo
Ha: u > uo

5
Q

Statistic calculated by comparing the point estimate of the population parameter with the hypothesized value of the parameter specified in Ho.

A

Test Statistic

6
Q

Test-Statistic Calculation

A

(Sample Statistic - Hypothesized Value) / SE of sample

7
Q

2 Types of Errors in Hypothesis Testing

A

Type 1: The rejection of null hypothesis when it is actually true, alpha == % that Type 1 happens
Type 2: The failure to reject the null hypothesis when it is actually false, 1-alpha == % that Type 2 happens

8
Q

The probability of obtaining a test statistic that would lead to a rejection of the null hypothesis, assuming the null hypothesis is true,

A

P-value

9
Q

If sample, n<30, and the distribution is non-normal, we have no reliable statistical test.

A

10
Q

T-statistic Calculation

A

t = (Xbar - uo)/ (s/n^(1/2))

11
Q

Used with t-statistics for testing the means of two normally distributed populations are equal, when the variances of the population are unknown but assumed to be equal.

A

pooled variances

12
Q

Test used for hypothesis testing concerning the variance of a normally distributed population.

A

Chi-square Test

*Asymmetrical and approaches the normal distribution in shape as the degrees of freedom increases.

13
Q

Chi-Square Calculation

A

ChiSquare = (n-1)s^2 / sigma^2

s= sample variance
sigma^2 = hypothesized population variance
14
Q

Test concerned with the equality of the variances of two populations, used when the populations are normally distributed.

A

F-Test

*Is right skewed

15
Q

F-Test Calculation

A

F = s1^2 / s2^2

s1 = Variance of s1
s2 = Variance of s2
16
Q

Tests that rely on assumptions regarding the distribution of the population and are specific to population parameters

A

Parametric Tests

ex. z-test

17
Q

Tests that do no consider a particular population parameter or have few assumptions about the population that is sampled.

A

Nonparametric Tests