QM Flashcards
(43 cards)
1
Q
assumptions of single sample t test
A
- random sample of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- std dev is unknown
- sample population is at least approximately normally distributed
2
Q
what is the welch t test
A
two sample t test for unequal variances
3
Q
assumptions of a single sample z test
A
- random sample of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- std dev is known
- sample population is at least approximately normally distributed
4
Q
assumptions of wilcoxon signed rank test
A
- random sample of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- sample population should be symmetrical
5
Q
assumptions of matched pair wilcoxon signed rank test
A
- 2 random matched pair samples of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- sampled populations are symmetrical
6
Q
assumptions of the sign test
A
- random sample of independent observations
- variable is quantitative or qualitative
- measurement scale is at least ordinal
7
Q
assumptions of matched pair sign test
A
- 2 random matched pair samples of independent observations
- variable is quantitative continuous
- measurement scale is at least ordinal
8
Q
assumptions of matched pair t test
A
- 2 random matched pair samples of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- sampled population are at least approximately normally distributed
9
Q
assumptions of 2 independent sample t-test
A
- 2 independent random samples of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- sampled population are at least approximately normally distributed
- variances are equal
10
Q
assumptions of welch t-test
A
- 2 independent random samples of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- sampled population are at least approximately normally distributed
11
Q
assumptions of wilcoxon rank sum/ mann whitney u test
A
- 2 independent random samples of independent observations
- variable is quantitative and continuous
- measurement scale is at least ordinal
- sampled populations are identical in shape and spread
12
Q
assumptions of one sample chi square test
A
- random sample of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- sampled population are at least approximately normally distributed
13
Q
assumptions of ftest for 2 independent samples
A
- 2 independent random samples of independent observations
- variable is quantitative and continuous
- measurement scale is interval or ratio
- sampled populations are at least approximately normally distributed
14
Q
assumptions for z test approximation for single sample
A
- random sample of independent observations
- variable is qualitative with 2 mutually exclusive, exhaustive categories
- measurement scale is nominal or ordinal
- sampled population binomially distributed
- np and nq bigger than or equal to 5
15
Q
assumptions of ztest approximation for 2 sample exact test
A
- 2 random independent samples of independent observations
- variable is qualitative with 2 mutually exclusive, exhaustive categories
- measured on nominal or ordinal scale
- sampled populations are binomially distributed
- each samples np’s and nq’s are greater than or equal to 5
16
Q
Write a two variance ftest confidence interval conclusion.
A
With _% confidence, the ratio of the population variances of the
returns on the two investments is between _ and _
17
Q
Assumptions of ANOVA
A
- data is k independent random samples of independent observations drawn from k subpopulations
- variable is quantitive and continuous
- measurement scale interval or ratio
- populations are normally distributed
- have the same variance
18
Q
kruskal wallis assumptions
A
- data is k independent random samples of independent observations drawn from k subpopulations
- variable is quantitive and continuous
- measurement scale at least ordinal
- populations are identical in shape and spread
19
Q
LR assumption 1
A
random sample of n > k+1 statistically independent but identical sets of observations
20
Q
LR assumption 3
A
homoscedastic
21
Q
LR assumption 5
A
multicollinearity
22
Q
LR assumption 6
A
conditional distribution of random error is normal
23
Q
what does Levene’s test test for
A
homoscedasticity
24
Q
what does homoskedastic mean
A
constant variance in error terms
25
what test is used to test homoscadasticity
white test/ studentised breuch-pagan test
26
How to test linear regressions for multicollinearity
* R^2 is very high and slope efficients are not significant in expected direction
* pearson sample correlation coefficients
* variance inflation factor
27
when do you halve p value
* one sided hypothesis test
28
normtest.p null hypothesis
normal
29
white test null hypothesis
Homoskedastic
30
How do you test usefulness of LPM model
percent correctly predicted and fitted values
31
how can you solve autocorrelation
* Use the heteroskedasticity and autocorrelation consistent (HAC) standard errors of Newey and West.
* Estimate an appropriately transformed equation that has the original parameters but independent errors such as through Generalized Least
Squares.
32
whats a unit root
non-stationary time series
33
what is a stationary time series
One where a time series' statistical properties are constant over time eg mean, variance
34
what is autocorrelation
random errors have a non zero correlation over time
35
what is leptokurtic
higher around mean and fatter tails
36
what is platykurtic
flatter around mean and tails
37
what does m mean in the f test formula
number of predictors removed from the original model
38
what is TSLR4
autocorrelation
39
what is the type of linear regression if the dependent variable is a dummy variable
Linear probability model
40
what is the type of linear regression if the dependent variable is quantitative
Ordinary least squares model
41
what are the hypotheses for f test for variance
F = o2/o2=1
42
write a slope interpretation for a log model
% %
43
when do you use percentage points in slope interpretations
when dependent variable in a percentage
