maths Flashcards

1
Q

bar charts

A
  • are an easy way of representing data that is not continuous (nominal)
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2
Q

histograms

A
  • show frequency density on the y axis instead of the raw frequency value.
  • This means they represent the data distribution far more accurately.
  • The ​area​ of each bar, that is the height x width, is equal to the ​frequency.
  • The x axis is represented by an interval or group of continuous data values
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3
Q

pie charts

A
  • use percentages to represent segments of a circle as the values associated with data groups.
  • only used for continuousdata
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4
Q

mean

A
  • a measure of central tendency. It shows the average or expected value in a set of data.
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5
Q

strengths of mean

A
  • Easy to calculate mathematically, gives a precise value, useful for statistical tests.
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6
Q

weakness of mean

A
  • Can be affected by outliers (causing skew), can give a value not originally in the data set (unrealistic)
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7
Q

median

A

The middle value in a set of data that is organised by increasing value

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8
Q

strengths of median

A
  • Not affected by outliers, will always give a value originally in the data set
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9
Q

weakness of median

A

Not as useful for other statistical test, requires sorted and ordered data.

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10
Q

mode

A

Provides the most frequent or common value in a data set.

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11
Q

strengths of mode

A
  • A useful way of calculating the average when the data is nominal
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12
Q

weakness of mode

A

There may be multiple modes, there may not be a mode at all, the mode may not represent the spread of the data in an accurate way

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13
Q

range

A

A measure of dispersion - the difference between the highest and lowest value in a set of data

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14
Q

strength of range

A

Easy to calculate and gives a good idea of the spread of data.

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15
Q

weakness of range

A

Is affected by outliers and is not useful for other statistical calculations.

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16
Q

calculate the variance

A
  • Calculate the mean of the data in the table
  • Subtract the mean from every value in the table - this new value is
    called ‘d’
  • Square each value of ‘d’
  • Add up each value of ‘d squared’
  • Divide this number by N - the number of values in the table
17
Q

calculate standard deviation

A
  • Calculate the mean of the data in the table
  • Subtract the mean from every value in the table - this new value is
    called ‘d’
  • Square each value of ‘d’
  • Add up each value of ‘d squared’
  • Divide this number by N - the number of values in the table
  • square root your answer to give SD
18
Q

what correlation is this scatter graph?

A
  • positive correlation
19
Q

what correlation is this scatter graph?

A
  • moderate negative correlation
20
Q

what correlation is this scatter graph?

A
  • strong positive correlation
21
Q

what correlation is this scatter graph?

A
  • no linear relationship
22
Q

positive relationship

A

as one variable increases in value, so does the other
e.g hours of revision and percentage score on a maths test

23
Q

negative relationship

A
  • as one variables increases, the other decreases e.g hours watching television and percentage score on a maths test
24
Q

parametric tests

A

assume that the population that the data is drawn from is normally distributed.

25
non-parametric tests
- used when this assumption cannot be made. - In psychological experiments, these tests are often used due to difficulty in gaining normally distributed populations.
26
what skew is this
normal skew
27
what skew is this
positive skew
28
what skew is this
negative skew
29
interquartile range
- the difference between the upper and lower quartiles - shows the spread within data once separated into 4 equal groups
30
standard deviation
- shows the average difference between the data values and the mean. - The standard deviation can therefore indicate the overall dispersion as a large standard deviation highlights that each value varies quite significantly from the mean. - The standard deviation is a better measure than the range if there are outlying scores as it considers all the items in the distributions and is less affected by anomalous data.
31
quantitiative data
- data that is measured and expressed numerically, such as a value, amount or quantity. - It is usually associated with units. - extremely useful for using directly with statistical tests and usually involves a very structured form of data collection, for example, measurements of temperature.
32
qualitative data
- describes the attributes and qualities of data rather than defining it with measurements. - extremely useful at providing depth of information and can therefore develop a more meaningful understanding.
33
primary data
data collected directly and originally from the researchers themselves with the purpose of using the data in the experiment itself.
34
secondary data
research data that was collected by a third party at a previous time, possibly for use in another experiment, but that is still useful for the research purpose.