Week 2 descriptives Flashcards

1
Q

Nominal data

A

Categorical data eg gender

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2
Q

Ordinal data

A

Orders people, objects or events along some continuum. No information is given about the differences between the points in the scale

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3
Q

Interval scales

A

Equal intervals between objects represent equal differences.

No absolute/true zero point

Cannot make ratio comparisons

Eg time, temp and IQ

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4
Q

What does no true zero point mean

A

It’s not nothing.

E.g 0 Celsius is not as lack of temperature, it is a degree and means something

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5
Q

Ratio scales

A

True zero point

Higher level of measurement - more detailed

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6
Q

What is the goal of Descriptive statistics

A

Characterize a numerical dataset efficiently

Condense meaningful information

Minimize the inevitable error involved during condensation

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7
Q

What is the goal of inferential statistics

A

infer the characteristics of the whole population are from a sample

Going beyond the information given to make likely assertions rather than certain ones

Sample statistics (English letters) are used to estimate population parameters ( Greek letters)

Key ideas: theoretical sampling distributions composed of innumerable random samples

key indices - p-value and confidence intervals

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8
Q

measures of central tendency

A

mean, median and mode

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9
Q

mean

A

average - add all and divide by how many present

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10
Q

cons of using the mean

A

inaccurate description and extreme scores influence mean

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11
Q

what does a histogram tell us

A

if the data is symmetrical and if the mean is appropriate to describe the sample

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12
Q

median

A

the score in the middle when are scores are arranged from smallest to largest

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13
Q

pro of using median

A

not affected by extreme scores

more accurate representation of data

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14
Q

mode

A

the most frequent score

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15
Q

what central tendency can nominal data only use

A

mode

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16
Q

what does measure of variability describe

A

the degree to which values vary

17
Q

what are the measures of variability

A

range, interquartile range, variance and SD

18
Q

range

A

difference between max and min scores

19
Q

pros of using range

A

straightforward to calculate and easy to interpret

20
Q

cons of using range

A

unstable across different samples

easily distorted by outliers

21
Q

what does interquartile range use

A

percentiles

22
Q

what are percentiles

A

cut off point that divides the data into percentage chunks

23
Q

variance

A

a measure of how much the scores vary in terms of distance from the mean

the average of each scores squared deviation from the mean score

24
Q

when do you use population formula for variance

A

when you have a whole population and don’t want to generalize scores

25
when do you use sample variance formula
when you want to estimate variance for population and generalize scores
26
standard deviation
the square root of the average of each scores squared deviation of the mean score = the square root of variance bigger value - more spread out
27