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Statistics > Inferential Statistics > Flashcards

Inferential Statistics Flashcards

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?

A

Ho / Null

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
Q

If we fail to reject the the Ho, it follows that the Ho is “true”. True or false?

A

False

25
Q

If we fail to reject Ho, Ho _____________ as true.

A

Does not follow

26
Q

Words to avoid TCP

A

Truth
Certain
Prove

27
Q

Words to Prefer

A

Indicate
Support
Infer

28
Q

In a random process, we know ____________________, but we don’t know ____________________.

A

What outcomes could happen; which particular outcome will happen

29
Q

Examples of random process

A

Coin toss
Die roll
Ipod shuffle
Stock market

30
Q

probability of event A is

A

P (A)

31
Q

Probability value should be

A

Less than 1 greater than 0

32
Q

If we observed the random process an infinite number of times, the probability of an outcome is

A

The proportion of times the outcome would occur

33
Q

Probability is a subjective degree of belief

A

Bayesian interpretation

34
Q

The Bayesian interpretation is largely popularized by

A

Revolutionary advance in computational technology and methods during the last twenty years

35
Q

As more observations are collected, the proportion of occurrences with a particular outcome converges to the probability of that outcome

A

Law of large numbers

36
Q

Common misunderstanding of law of large numbers

A

Gamblers fallacy (law of averages)..there is no memory

37
Q

Synonym for disjoint events

A

Mutually exclusive

38
Q

Disjoint events

A

Cannot happen at the same time

39
Q

Example of disjoint events

A

Single toss coin
Subject pass or fail
Single card from a deck

40
Q

Events that can happen at the same time

A

Non-disjoint

41
Q

The outcome of a single toss coin is

A

Disjoint outcomes

42
Q

Grade A in stat and eco

A

Non disjoint

43
Q

Formula for disjoint probability

A

P(A and B) = 0

44
Q

Formula for non-disjoint probability

A

P(A and B) not equal to 0

45
Q

If knowing the outcome of one provides no useful information about the other’s outcome

A

Independence

46
Q

P (A|B) = P(A), then A and B are ________________.

A

Independent

47
Q

If A and B are independent, P(A and B) = P(A) x (B).apply. Two tails in a row

A

1/4

Statistics (2 decks)

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