1.8 - Analysing data Flashcards

1
Q

What does a histogram show us?

A

How many times each score occurs

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2
Q

What is the y-axis on a histogram?

A

Frequency

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3
Q

Why are histograms useful?

A

Can assess properties of the distribution of scores

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4
Q

What are 3 characteristics of a normal distribution?

A

Symmetrical across the mean
Bell-shaped curve
Tails touch infinity line either side

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5
Q

What are 2 ways in which distributions can deviate from normal?

A

Skew

Kurtosis

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6
Q

What types of skew are there?

A

Positive

Negative

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7
Q

What does a positively skewed graph look like?

A

Tails end at the positive end of the scale

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8
Q

What does a negatively skewed graph look like?

A

Tails end at the lower end of the scale

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9
Q

What does skew mean?

A

Lack of symmetry

Most frequent scores are clustered at one end of the scale

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10
Q

What is kurtosis?

A

Refers to the pointiness of the graph

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11
Q

What are 3 types of kurtosis?

A

Leptokurtic
Mesokurtic
Platykurtic

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12
Q

What does a platykurtic graph look like?

A

Flat distribution
Thin tailed
Negative kurtosis

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13
Q

What does a leptokurtic graph look like?

A

Pointy
Heavy tailed
Positive kurtosis

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14
Q

What does a mesokurtic graph look like?

A

Relatively normal distribution

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15
Q

What are 3 common measures of central tendency?

A

Mean
Median
Mode

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16
Q

What is the mode?

A

The score that occurs most frequently in a data set

17
Q

How do you spot the mode on a histogram?

A

Tallest bar

18
Q

What does bimodal mean?

A

Distribution with 2 modes

19
Q

What does multimodal mean?

A

Data sets with more than 2 modes

20
Q

What is the median?

A

The middle score when ranked in order

21
Q

What data can median be used for?

A

Ordinal

Also interval and ratio

22
Q

What data can the mode be used on?

A

Nominal

All types

23
Q

What is the mean?

A

Average of scores

24
Q

What is a disadvantage of the mean?

A

Influenced by extreme scores and affected by skewed distributions

25
Q

What data can the mean be used on?

A

Interval and ratio

26
Q

What are quartiles?

A

3 values that split the data into equal quarters

27
Q

What are the 3 quartiles?

A

1st - lower quartile
2nd - median
3rd - upper quartile

28
Q

How do we calculate the interquartile range?

A

Upper - lower

29
Q

Advantage of interquartile range

A

Not affected by extreme scores

30
Q

Disadvantage of interquartile range

A

Lose a lot of data

31
Q

How do we calculate deviance?

A

individual score - mean score

32
Q

How do we calculate sum of squared errors?

A

Square all deviances and add up

33
Q

Why do we square the deviances?

A

To avoid getting zero or negative numbers as our answer

34
Q

What is the problem with using SS?

A

Can’t compare the total of dispersion to other samples that differ in size

35
Q

How do we calculate the average dispersion (variance)?

A

Divide SS by degrees of freedom (n-1)

36
Q

How do we get the standard deviation from variance?

A

Square root the variance

37
Q

What are 3 measures of dispersion?

A

Sum of squares
Standard deviation
Variance

38
Q

What would a standard deviation of 0 indicate?

A

That all the results are the same

39
Q

Is a large or small standard deviation ideal?

A

The smaller the standard deviation score, the more accurate the data is to the mean