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Introduction to Research > Unit 16: Statistical Survey and Scales of Measurement > Flashcards

Unit 16: Statistical Survey and Scales of Measurement Flashcards

1
Q

Four Scales of Measurement:

A
  1. Nominal
  2. Ordinal
  3. Ratio
  4. Interval
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1
Q

Four Scales of Measurement:

A
  1. Nominal
  2. Ordinal
  3. Ratio
  4. Interval
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2
Q
  • Whole numbers
  • Cannot be analyzed mathematically
  • Ex. Jersey number
A

Nominal

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2
Q
  • Whole numbers
  • Cannot be analyzed mathematically
  • Ex. Jersey number
A

Nominal

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3
Q
  • Denote positions in order

* Cannot be mathematically organized

A

Ordinal

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3
Q
  • Denote positions in order

* Cannot be mathematically organized

A

Ordinal

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4
Q
  • Equal distance between values
  • Can be mathematically analyzed
  • Negative numbers
A

Interval

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4
Q
  • Equal distance between values
  • Can be mathematically analyzed
  • Negative numbers
A

Interval

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5
Q
  • Equal distance between values
  • Can be mathematically analyzed
  • No negative numbers
A

Ratio

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5
Q
  • Equal distance between values
  • Can be mathematically analyzed
  • No negative numbers
A

Ratio

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6
Q

Discrete values:

A

Nominal and Ordinal

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6
Q

Discrete values:

A

Nominal and Ordinal

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7
Q

Continuous variables:

A

Interval and ratio

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7
Q

Continuous variables:

A

Interval and ratio

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8
Q

Parametric tests can be done on:

A

Ratio and interval

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8
Q

Parametric tests can be done on:

A

Ratio and interval

9
Q

T-test:

A
  • Comparing means of two different groups

* Increased # of t-tests results in type 1 error

9
Q

T-test:

A
  • Comparing means of two different groups

* Increased # of t-tests results in type 1 error

10
Q

Counteracting the problem of multiple comparisons:

A

Bonferroni Adjustment

10
Q

Counteracting the problem of multiple comparisons:

A

Bonferroni Adjustment

11
Q

Analysis of variance:

  • Means of several groups are equal?
  • Giant t-test
A

ANOVA

11
Q

Analysis of variance:

  • Means of several groups are equal?
  • Giant t-test
A

ANOVA

12
Q
  • Compares between group variance to within group variance

* Will be larger than one

A

F-Static

13
Q

Same participants used in each condition
More statistically powerful than between-groups design
Less error-less individual differences or within-groups variance (trait error)
Half as many people

A

Repeated Measures ANOVA

14
Q

Measuring the impact of more than one independent variable on a dependent variable

A

ANOVA w >1 Independent Variable

Introduction to Research (6 decks)

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