4 Flashcards

1
Q

Hypothesis testing?

A

How unusual is it to get our data if the null hypothesis is true

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2
Q

!!!!How to undergo hypothesis testing?

A

•Imagine if the hypothetical population (null hypothesis H_0 true).
•generating a distribution of

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3
Q

Hypothesis testing usually assumes that sampling is?

A

Random

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4
Q

Null hypothesis?

A

Specific statement about a population parameter made for the purposes of an argument.

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5
Q

Alternative hypothesis?

A

Another possible possibility.

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6
Q

Test statistic?

A

Number calculated to represent the match between a set of data and a null hypothesis. In other words, if n exceeds the test statistic, the null hypothesis can be rejected since the values are extreme.

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7
Q

If the value of the test statistic is approaching y = 0 under the null hypothesis, then?

A

It is surprising.

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8
Q

P-value is the?

A

Probability of getting the data or smth as or more unusual if the null hypothesis were true in a test statistic.

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9
Q

Null distribution?

A

For a test statistic, is the probability distribution of alternative outcomes when a random sample is taken from a hypothetical population in which the null hypothesis is true.

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10
Q

If the null distribution approaches x = +-oo, then?

A

The null hypothesis is more likely to be disproved.

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11
Q

Statistical significance (alpha)?

A

Probability used as a criterion for rejecting the null hypothesis.

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12
Q

Alpha is often set as?

A

0.05, 1/20, which means that its okay for 5% extreme values.

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13
Q

If P < alpha, then?

A

We can reject the null hypothesis.

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14
Q

What does a p value mean?

A

Probability of getting the results if the null hypothesis is true.

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15
Q

Type 1 error?

A

When rejecting a true null hypothesis since the p value calculated was low enough to reject. (Does not depend on sample size because the test takes into account of sample size)

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16
Q

P-hacking

A
17
Q

Type II error?

A

Not rejecting a false null hypothesis. If null hypothesis is false, the probability of a Type II error is beta. The smaller beta, the more power a test has. Beta is lower with a larger sample size.

18
Q

Power?

A

Ability of a test to reject a false null hypothesis.

19
Q

Power = ?

A

1 - beta

20
Q

Why do we usually don’t know beta?

A

Because we don’t know the truth

21
Q

A larger sample size will tend to give an estimate with a larger/smaller confidence interval?

A

Smaller

22
Q

Critical value?

A

Value of a test statistic beyond which the null hypothesis can be rejected.

23
Q

Statistically significant?

A

When p < alpha