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stats > intro to stats > Flashcards

intro to stats Flashcards

1
Q

what is statistics?

A

The science of Collecting,Organising ,Presenting,Analysing and interpreting data

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2
Q

data

A

Data refers to set of values for a variable

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3
Q

variable

A

A variable is any measured characteristic that differs for different subjects

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4
Q

types of variables

A

categorical and numerical/quantitative

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5
Q

Levels of Measurement- NOIR

A

categorical: Nominal Data/ Ordinal Data
numerical: interval data/ ratio data

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6
Q

Nominal Data(categorical)

A

Naming/Labelling variables without any quantitative value. i.e. gender

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7
Q

Ordinal Data(categorical)

A

Ranked data/ Typically measure non-numeric concepts e.g. satisfaction ratings

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8
Q

Interval Data(numerical)

A

we know the order and also the differences between the values.ie. temperature/ can add or subtract

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9
Q

Ratio Data(numerical)

A

Tell us about the order, the difference in value between units and have an absolute zero.i.e. weight, income

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10
Q

population

A

All items or individuals about which you want to
reach conclusions

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11
Q

sample

A

A portion of the population selected for analysis

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12
Q

Why use a sample?

A

less costly/ less time consuming/ more practical

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13
Q

two types of statistics

A

descriptive/ inferential

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14
Q

Descriptive Statistics

A

Used to summarise the main aspects of your dataset using Tables, graphs, simple formulae

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15
Q

Inferential Statistics

A

Methods that use data collected from a sample (small group) to reach conclusions or make predictions or inferences about the population (larger group)

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16
Q

two general classes of descriptive statistics

A

Measures of central tendency/ Measures of variation/dispersion

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17
Q

Central Tendency

A

Central tendency refers to the tendency data has to cluster around the centre point.i.e the average

18
Q

The three main measures of central tendency

A

mean/ median/ mode

19
Q

The Fulcrum Conceptualization

A

the mean might be considered the balancing point or turning point of a lever where the distance from the mean is equal on each side
i.e. The mean is a good central point

20
Q

mean and central tendency

A

Mean is a poor measure of central tendency for this set of data (due to outliers)

21
Q

median

A

The median represents the middle score in a dataset

22
Q

Calculating the median if even number

A

find the average of middle two ranked values

23
Q

the mode

A

he value that appears most frequently in the dataset

24
Q

nomindal data and measures of central tendency

A

Nominal data – you can only use the mode

25
Q

ordinal data and measures of central tendency

A

Ordinal data – you can use the mode or the median

26
Q

both interval and and ratio data/ and measures of central tendency

A

Interval data and Ratio data – you can use mean, median or mode

27
Q

measures of variation

A

The Range/ The Interquartile Range/ The Standard Deviation

28
Q

the range

A

Range = Max Value – Min Value

29
Q

what do Measures of variation tell us?

A

Measures of variation tell us about how scores are dispersed
(distributed) around the central/average score

30
Q

the variance

A

sum of squares

31
Q

standard deviation

A

The standard deviation tells us how much, on average, scores in the dataset deviate from the mean

32
Q

variability

A

describes the distribution of scores

33
Q

Skewness

A

when data is not symmetrically distributed

34
Q

Kurtosis

A

refers to the steepness/shallowness of the distribution

35
Q

how does a small SD describe the distribution of scores ?

A

most scores cluster closely around the mean score

36
Q

how does a big SD describe the distribution of scores ?

A

most scores are spread out a lot from the mean score

37
Q

postive skew

A

more scores to the left of the peak

38
Q

negative skew

A

more scores to the right of the peak

39
Q

what presence of skewness is a problem?

A

value greater than +2 or – 2 is a problem

40
Q

Leptokurtic

A

steep curve

41
Q

Mesokurtic

A

normal curve

stats (9 decks)

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