Lecture 4 Flashcards

1
Q

What does the notation ‘n’ mean

A

Total number of scores/ participants

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2
Q

What does that notation ‘𝛴’ mean?

A

It means sum of all X

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3
Q

Define frequency distribution

A

Counts of values within categories of a variable. Can be shown in table form (tally chart) or in a bar chart

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4
Q

Define historgram

A

Bar chart for continuous variables to see the shape of a data distribution.

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5
Q

What does the peaks of a histogram tell you?

A

The highest peak = the mode

The number of peaks = the modality

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6
Q

What does the spread of data in a histogram tell you?

A

The variability/ variance

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7
Q

Define measures of central tendency

A

Numerical vaues referring to the centre of a distribution

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8
Q

When are the mean, median and mode all the same?

A

When the distribution is symetric and unimodal?

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9
Q

Evaluate the mode as a measure of central tendency

A

√ - Higher probability that randomly drawn value is the mode than the chances of it being another value
√ - applicable to nominal, ordinal, interval and ratio
X - May not represent central tendency at all, e.g. if distribution is skewed.

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10
Q

Evaluate the median as a measure of central tendency

A

√ - unaffected by extreme scores

X - not ideal as a basis for inferential statistics

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11
Q

Evaluate the mean as a measure of central tendency

A

√ - simple formula - most commonly used
√ - good estimator of population mean - forms the basis of inferential stats
X - requires at least interval level measurement
X - sensitive to extreme scores - distorted by outliers

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12
Q

Name one way of reducing outlier impact

A

Carrying out transformations

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13
Q

What are the 3 measures of central tendency?

A

Mean, median and mode

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14
Q

What are the 4 measures of variability?

A

The Range, the SD, the IQR and the Variance

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15
Q

Evaluate the range as a measure of variability

A

X - depends entirely on extreme values

X - Very sensitive to outliers

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16
Q

Evaluate the SD as a measure of variability

A

√ - easier to understand than variance

17
Q

How do you calculate the SD?

A

Sqaure root of the variance

18
Q

Evaluate the IQR as a measure of variability

A

X - discards data, which itself is arbitrary

19
Q

How do you calculate the variance?

A

Take away each value from the mean and square it, then divide it by N-1
E.g. If the data is 3,6,9. To work out the variance you would do: (3-6)²+(6-6)²+(9-6)² / 2

20
Q

Evaluate the variance as a measure of variability

A

√ - Very important in inferential stats

X - Quite hard to understand