Statistics Agresti Flashcards

You may prefer our related Brainscape-certified flashcards:
1
Q

hypothesis

A

statement claiming that a population parameter takes a certain value or lies within a particular range of values

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

significance test

A

summarize the data that is evidence for or against a hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

null hypothesis

A

statements that a population parameter takes a certain value (no effect)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

alternative hypothesis

A

statement that a population parameter takes an alternative value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

test statistic describes…

A

how far the point estimate falls from the population parameter, given the null hypothesis.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

p-value

A

probability that the test statistic equals the observed value or a more extreme value.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

the p value is calculated presuming that H… is true

A

H0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

smaller p values provide stronger evidence…

A

against the H0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

H0 is never about …

A

sample statistics (such as p dakje of x met streepje boven!!!)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

relatie H0 en Ha alsin hoe je het schrijft

A

H0 altijd met = teken, Ha is altijd in relatie tot H0.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

explanatory variable

A

independent

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

response variable

A

dependent

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

proportions 2 groups als…

A

explanatory (indep) = binary, response (dep) = categorical

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

standard error of the difference between sample proportions describes…

A

the difference in population proportions

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

large enough sample bij proportions

A

10 successes and 10 failures

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

CI interval for two population proportions

A

(𝑝̂1− 𝑝̂2) ± 𝑧(𝑠ⅇ)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

CI interpreteren

A
  • als er een 0 in zit: plausibel dat er geen effect is (verschil tussen de twee groepen = 0)
  • als het positief is: p1 > p2
  • als het negatief is: p1 < p2

Dus het gaat echt om het verschil tussen de twee groepen! Dus als deze value dicht bij de 1 zit, is er waarschijnlijk een klein verschil.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

𝑝̂ naam

A

pooled estimate

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

hoe bereken je de 𝑝̂ voor de se formule van z score

A

The number of successes in both groups and then dividing this number by the total number of participants used in both groups (𝑛1 + 𝑛2).

total successes/total n

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

wat is de 0 in de formule

A

de value van de H0!! (H0: p = …)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

quantitative dependent variable (sigaretten -> bloeddruk)

A

Based on the difference in sample means, 𝑥1 − 𝑥2, we want to draw conclusions about the difference
in population means, 𝜇1− 𝜇2

22
Q

verschil o, s en se

A
  • o is standard deviation of population,
  • s is standard deviation of sample,
  • se is the standard deviation of its sampling distribution or an estimate of that standard deviation.
23
Q

wat gebruik je bij quantitative dependent variable

A

de mean!

24
Q

z score is R/L tail, t score is R/L tail

A

z = left, t = right

25
Q

CI for mean difference between two groups

A

(𝑥1 −𝑥2) ± 𝑡.975(𝑠ⅇ)

26
Q

how to calculate the df for means two groups

A

if 𝑠1= 𝑠2 and 𝑛1= 𝑛2, then 𝑑𝑓 = (𝑛1+ 𝑛2− 2).

27
Q

the degrees of freedom will usually fall between…

A

(𝑛1+ 𝑛2 – 2), with a minimum of (𝑛1− 1)and (𝑛2− 1)

28
Q

t test is ook robust bij samples kleiner dan 30

A

oke

29
Q

mean assumptions

A

qualitative, random, large sample

30
Q

if a two-sided test rejects the null hypothesis of the population being equal, then the confidence
interval for the same error probability (e.g. α=0.05 and confidence level is 95%) will not contain 0.

A

oke

31
Q

dependent samples

A

within-group design, repeated measures, matched pairs –> when they use the same subjects (even if it is a pair)

32
Q

independent samples

A

when the observations in one sample are independent from the observations in another sample

33
Q

paired differences

A

use with matched pairs: calculate xd (score 1 - score2)

34
Q

xd is ook gelijk aan….

A

the difference between the means of two samples:
xd = (x̄1 − x̄2)

35
Q

wat is makkelijk aan dependent samples

A

het wordt een one sample analysis, want je kan gewoon de scores van elkaar aftrekken.

36
Q

CI voor dependent samples

A

(xd.) ± 𝑡.975(𝑠ⅇ)

37
Q

z score is … tail

A

left

38
Q

hoe bereken je de p value voor =/=

A
  1. eerst z score (formule met wortel)
  2. norm.s.dist
  3. 1-norm.s.dist
  4. 2 * vorige antwoord
39
Q

hoe bereken je de p waarde voor Ha: p < p0

A
  1. z score berekenen: formule met wortel
  2. norm.s.dist
40
Q

hoe bereken je de p waarde voor p > p0

A
  1. z score (formule met wortel)
  2. norm.s.dist
  3. 1-…
41
Q

als je % ziet dan is het….

A

proportion -> z score!

42
Q

P(type 1 error) =

A

significance level

43
Q

we do not know if a decision is correct, altijd een kans dat het niet zo is.

A

oke

44
Q

type 1 error

A

reject H0 when it is true false positive

45
Q

type 2 error

A

accept H0 when it is not true, false negative

46
Q

CI is more useful than p value

A

want bevat alle plausibele waardes; p value laat alleen zien of de H0 plausibel is

47
Q

p-value definitie nog een keer

A

A p-value measures the probability of obtaining the observed results, assuming that the null hypothesis is true.

48
Q

CI definition

A

For a 95 % confidence interval, if many samples are collected and the confidence interval computed, in the long run about 95 % of these intervals would contain the true mean.

49
Q

P(type 1 error) decreases if…

A
  • bigger sample size
  • parameter moves further away from H0, towards Ha.
50
Q

Power =

A

1-P(type 2 error)

51
Q

3 assumptions t test

A

Data are quantitative and have been produced randomly and have an approximate normal population distribution.

52
Q

when a p value lies underneith 0,05, does the CI contain the H0?

A

No, the interval does not contain H0 in 95% CI if it is rejected by the p value