Quantitative Methods V Flashcards Preview

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Flashcards in Quantitative Methods V Deck (31):
1

Null hypothesis

One you want to reject in order to assume alternate is correct

2

Test statistic
(same for Z and T)

(sample mean - hypothesized mean) / standard error

remember, standard error = stdev / sqrt(n)

3

Two tailed vs. one-tailed

Two tailed is Ho = something

One-tailed is Ho > something

4

Type I error

Rejection of null when it's actually true

5

Type II error

Failure to reject when it is actually false

6

Power of test

1 - probability of type II error

7

Confidence interval (Z-test)

Sample mean - (standard error * critical z-value) < mean < sample mean + (standard error * critical z-value)

8

P-value

Prob of test stat that would lead to a type I error.

9

T-Test

Use if population variance is unknown and either:

1. Sample is large
2. Sample is small, but distribution is normal

10

Z-Test

Use if population is normal, with known variance or when sample is large and population variance is unknown

11

Sample distribution

Sample statistics computed from samples of the same size drawn from the same population

12

Desired properties of estimators (3)

Efficiency, consistency and unbiasedness

13

Data mining

Searching for trading patterns until one "works"

14

Sample selection bias

Some data is systematically excluded (e.g. from lack of availability)

15

Look ahead bias

Study tests relationship using sample data that wasn't available on test date

16

Time period bias

Either too long or too short

17

Chi-squared (X^2)

Used for tests concerning variance of normally distributed population vs. sample

Symmetrical, approaches normal as d.f. increases

Chi is bounded by 0 so test stats can't be negative

18

Chi-squared test statistic

[(n-1) * sample variance] / hypothesized pop. variance

FYI, critical value is for one tail, so you have to adjust for two

19

F-test

Tests equality of variances of two populations via samples of said populations

Populations are normal and samples are INDEPENDENT.

Bounded by 0 (like chi square)

20

F-test: two tailed vs. one-tailed

Two tailed: variance of pop. 1 = variance pop. 2

One-tailed: variance of pop. 1 >= variance pop. 2

21

F-statistic

Variance sample 1 / variance sample 2

Note: always put larger variance in numerator, use d.f. of larger sample and look at right tail.

22

Difference in means test

T-statistic

Two INDEPENDENT samples, normally distributed populations

Formula won't be on test.

23

Paired comparisons test

T-test statistic

Used when samples are dependent.

Sample data must be normally distributed.

24

Paired comparisons test (formula)

Tstat = (sample mean difference - mean) / standard error of mean difference

Sample mean difference = 1/n * sum(mean1 - mean2...)

Standard error = sample stdev / sqrt(n)

25

Elliot wave theory - impulse wave

Direction of the prevailing trend, has five smaller waves

26

Elliot wave theory - corrective wave

Against the prevailing trend, has three smaller waves.

27

Type II Error probability

Calculate probability that you fail to reject the null when is actually false. Here you use the actual M and get the stat of (X-bar - M) / standard error.

28

Treynor Ratio

(portfolio return - risk free return) / Beta

29

Consistent estimator

Gets closer to population as n increases

30

Unbiased estimator

Expected value = true population value

31

Efficient estimator

Has a variance of sampling distributions that is lower than that of any other estimator