Type I And Type II Errors Flashcards

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1
Q

What is a null hypotheses?

A

‘No difference between conditions’

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2
Q

What is an alternative/ experimental hypotheses?

A

There will be a difference between conditions

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3
Q

What hypotheses is rejected for a type 1 error?

A

The null hypotheses is rejected and alternative hypothesis is accepted when it should be the opposite.

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4
Q

Which hypothesis is actually true for a type 1 error?

A

The null hypothesis

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5
Q

What is a type 1 error?

A

A false positive which claims to have found a significant result when there isn’t one.

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6
Q

What hypothesis is accepted for a type 2 error?

A

The null hypothesis is accepted and the alternative hypothesis is rejected when it should be the other way round.

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7
Q

Which hypothesis should actually be accepted for a type 2 error?

A

The alternative hypothesis

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8
Q

What is a type 2 error?

A

A false negative which claims to have not found a significant result when there is one.

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9
Q

When does a type 1 error usually occur?

A

If the significance is too high/ lenient

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10
Q

When does a type 2 error usually occur?

A

If the significance is too strict/ low

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11
Q

What does 0.05 do to the two errors?

A

Balance them

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12
Q

How do you choose a stats test?

A
  • Difference or correlation
  • Experimental design
  • Level of measurement
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13
Q

How do we know if the experiment is difference or correlation?

A

From the hypothesis

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14
Q

What experimental design is used for related design?

A
  • Matched pairs
  • Repeated measures
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15
Q

What experimental design is used for unrelated design?

A
  • independent measures
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16
Q

What are the three levels of measurement which quantitative data can be split into?

A
  1. Nominal data
  2. Ordinal data
  3. Interval data
17
Q

What is nominal data?

A
  • Categorical
  • Discrete = one item can appear in one category
18
Q

What is ordinal data?

A

Data that is ordered in some way

19
Q

What is interval data?

A
  • Based on numerical scales e.g. units of equal, precisely defined size.
  • Usually measurements you’d find in maths or other sciences.
20
Q

What are parametric tests for?

A

Interval data only

21
Q

What do parametric tests deal with?

A

Data with a normal distribution

22
Q

What do parametric tests have?

A

Homogeneity of variance - set of scores in each condition should have similar dispersion or spread

23
Q

Mann Whitney

A
  • Difference
  • Unrelated design
    -Ordinal data
24
Q

Wilcoxon

A
  • Difference
  • Related design
  • Ordinal data
25
Q

Unrelated T-Test

A
  • Difference
  • Unrelated
  • Interval data
  • Parametric test
26
Q

Related T-Test

A
  • Difference
  • Related design
  • Interval data
  • Parametric test
27
Q

Sign Test

A
  • Difference
  • Related design
  • Nominal data
28
Q

Spearman’s Rho

A
  • Correlation
  • Ordinal data
29
Q

Pearson’s R

A
  • Correlation
  • Interval level data
  • Parametric test
30
Q

Chi-squared

A
  • Difference or association
  • Nominal data
  • Unrelated design