Inferential Statistics Flashcards

(48 cards)

0
Q

There is something going on

A

Alternative

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1
Q

There is nothing going on

A

Null

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2
Q

2 competing claims are independent

A

Null

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3
Q

2 competing claims are dependent

A

Alternative

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4
Q

Can we “accept the null hypothesis”?

A

No

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5
Q

Can we “fail to reject the null hypothesis”?

A

Yes

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6
Q

What is unusual? Null or alternative?

A

Alternative

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7
Q

The null hypothesis represents the

A

Status quo

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8
Q

Alternative hypothesis represents our

A

Research question

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9
Q

If two variables data happen DUE TO CHANCE, they are

A

Independent

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10
Q

If two variables change DUE TO AN ACTUAL EFFECT ON ONE, this is

A

Dependent

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11
Q

Probability of observing an outcome at least as extreme as the one observed in the original data is the

A

P-value

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12
Q

If the p value is low, the N o should _______ in favor of the alternative

A

Go

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13
Q

What are the four N of null?

A

Nothing new
Nothing different
Nothing changed
Negation of the research question

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14
Q

If the Null is true, then

A

Test it

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15
Q

If the null is rejected

A

Consider alternative

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16
Q

Alternative is known as ACU

A

Assumption
Claim
Unknown

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17
Q

What is the SAG of null

A

Status quo
Assumption
Given

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18
Q

Ho is always ______________ Ha

A

In opposition

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19
Q

Which one contains equality?

20
Q

Which one does not contain equality?

A

Ha / alternative

21
Q

What are three possibilities in Ho and Ha

A

Ho = Ho _

Ha # Ha > Ha <

22
Q

We can ___________ or _____________ the null hypothesis or Ho.

A

Reject ; fail to reject

23
Q

If we reject the Ho, it means that the

A

Ha is supported by data

24
If we fail to reject the the Ho, it follows that the Ho is "true". True or false?
False
25
If we fail to reject Ho, Ho _____________ as true.
Does not follow
26
Words to avoid TCP
Truth Certain Prove
27
Words to Prefer
Indicate Support Infer
28
In a random process, we know ____________________, but we don't know ____________________.
What outcomes could happen; which particular outcome will happen
29
Examples of random process
Coin toss Die roll Ipod shuffle Stock market
30
probability of event A is
P (A)
31
Probability value should be
Less than 1 greater than 0
32
If we observed the random process an infinite number of times, the probability of an outcome is
The proportion of times the outcome would occur
33
Probability is a subjective degree of belief
Bayesian interpretation
34
The Bayesian interpretation is largely popularized by
Revolutionary advance in computational technology and methods during the last twenty years
35
As more observations are collected, the proportion of occurrences with a particular outcome converges to the probability of that outcome
Law of large numbers
36
Common misunderstanding of law of large numbers
Gamblers fallacy (law of averages)..there is no memory
37
Synonym for disjoint events
Mutually exclusive
38
Disjoint events
Cannot happen at the same time
39
Example of disjoint events
Single toss coin Subject pass or fail Single card from a deck
40
Events that can happen at the same time
Non-disjoint
41
The outcome of a single toss coin is
Disjoint outcomes
42
Grade A in stat and eco
Non disjoint
43
Formula for disjoint probability
P(A and B) = 0
44
Formula for non-disjoint probability
P(A and B) not equal to 0
45
If knowing the outcome of one provides no useful information about the other's outcome
Independence
46
P (A|B) = P(A), then A and B are ________________.
Independent
47
If A and B are independent, P(A and B) = P(A) x (B).apply. Two tails in a row
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