L2 basic Stats Flashcards

1
Q

What does more variance indicate?

A

A stronger correlation.

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2
Q

What is variance?

A

Variance represents the amount of variability in the data.

  • 3 main methods of representing variability.
    1) range -simplest one
    2) Standard deviation (S)
    3) Variance (S2)
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3
Q

What is correlation?

A
  • Standardised representation of the association between 2 variables.
  • Can range from-1.0 to 1.0
  • r symbol for correlation
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4
Q

How to calculate variance

A
  • square standard deviation

- square the correlation (coefficient determination)

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5
Q

What are composite variables?

A
  • Test scores based on the sum of 2 or more items.
  • E.g. The Beck Depression Inventory consists of 21 items
  • Items are scored on an ordinal scale from 0 to 3
  • Thus, the range of scores possible on the BDI is 0 to 63. (3x21)
  • Such ‘sum scores’ are known as ‘composite scores’.
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6
Q

The variance of a composite score is a function of:

A
  1. The variance associated with the individual items, and

2. The correlation amongst the items.

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7
Q

As the correlation between items increases (and is positive) what also increases?

A

The magnitude of the corresponding composite variance score.

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8
Q

Binary items (dichotomous items)

A
  • you either provide the correct or incorrect answer.
  • Responses are scored 0 or 1.
  • Frequently used in achievement type tests
  • E.g. Exams and intelligence test items
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9
Q

Binary items: variance

A

-The variance of a dichotomously scored item is maximised when half of the people score 1 and the other half score 0.

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10
Q

What are the most common psychological test score interpretations?

A

1) Relative interpretations - based on the analysis if data
2) Abstract interpretations - based on the research which supports the test scores as valid indicators of a psychological construct.

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11
Q

Relative interpretations - to interpret an individual’s score, we need to:

A

-know the mean and SD

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12
Q

Raw Scores: Limitations

A
  • Although the mean and SD allow us to interpret a particular score in a relative way, it is not a precise method, unless you’re a human calculator.
  • Instead, raw scores can be converted into standardised scores which incorporates information about the mean and SD.
  • The most commonly used standardised score is the z-score.
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13
Q

Z-scores

A
  • Have a mean of 0 and SD or 1.
  • Useful for transforming raw scores into relative scores.
  • Shows us the distance from the mean and so frees us from worrying about the units of the original test score.
  • Can be used to compare scores across tests that are on different sized units.
  • Even if the scales are meaningful, you may want to convert them for the purposes of comparison.
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14
Q

Converted Standard Scores

A
  • Z-scores are great but if you didn’t want to deal with negative numbers you can convert them into alternative standard scores.
  • To do this rescale the scores so that the converted scores have a different mean and SD.
  • The most popular is the T-score
  • With T-scores the mean is always 50 and the SD is always 10.
  • T-scores are not like t-tests; they’re different.
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15
Q

How to create T-scores

A

1) convert the raw scores unto Z-scores

2) Then, convert the z-scores using the formula: T = z(10) + 50

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16
Q

Is this dodgy?

A
  • You may think that applying these conversions is dodgy.
  • However you have to remember that most psychological tests yield scores that have no inherent meaning.
  • They are measured on ordinal scales.
  • They simply yield information in a relative sense.
  • How we scale those raw scores does not alter their inherent relative meaning.
  • In the case of academic marks, there is one aspect to consider.
  • They’re considered “criterion referenced” in a sense.
  • That is you need to achieve 50 to pass.
17
Q

What are percentile ranks?

A
  • Percentile ranks indicate the percentage of scores that are below a specific test score.
  • another way to represent scores in relative terms.
18
Q

What is a reference sample the same as?

A

Normative samples.

19
Q

Probability and Non-Probability Sampling

A
  • Probability samples use procedures that ensure a representative sample.
  • Random sampling is a type of probability sample, as you would expect a random sample from the population to be representative of the population.