RM - Probability Flashcards

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1
Q

What are statistical tests based on?

A

Probabilities.

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2
Q

Alternative hypothesis

A

A testable statement about the relationship (difference, association etc.) between two or more variables.

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3
Q

Null hypothesis

A

An assumption that there is no relationship (difference, association, etc.) in the population from which a sample is taken with respect to the variables being studied.

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4
Q

Probability (p)

A

A numerical measure of the likelihood or chance that certain events will occur. A statistical test gives the probability that a particular sample did not occur if the null hypothesis for the population was true, i.e. there was no real effect.

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5
Q

Type I error

A

Occurs when a researcher rejects a null hypothesis that is true.

False positive.

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6
Q

Type II error

A

Occurs when a researcher accepts a null hypothesis that was not true.

False negative.

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7
Q

What does chance refer to?

A

Something with no cause. It just happens.

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8
Q

What level of probability is used in psychology?

A

0.05

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9
Q

What does it mean that in psychology we use a probability level of 0.05?

A

This expresses the degree of uncertainty. It means that there is a 5% chance of the results occurring if the null hypothesis is true (i.e. there is nothing going on). In other words, a 5% chance that the results would occur even if there was no real difference/correlation between the populations from which the samples were drawn. This 5% chance is recorded as a probability (p) = 0.05. In fact the chance is 5% or less which is written as p ≤ 0.05.

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10
Q

What is the symbol for probability?

A

Probability (p)

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11
Q

What does the level of probability express?

A

The degree of uncertainty.

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12
Q

What is the chosen level of p called?

A

The significance level.

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13
Q

What level of significance is used in some studies where psychologists want to be more certain?

A

p ≤ 0.01

1% or less

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14
Q

Why do psychologists generally use the 5% probability level?

A

Because this is a good compromise between being too strict or too lenient about accepting the null hypothesis - or, more formally, a good compromise between a Type I error and a Type II error.

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