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What is quantitative data?
Quantitative data is data in the form of numbers.
How is quantitative data relevant to the nomothetic approach?
b) It can highlight trends and patterns
b) It can convey subjective experience
c) It has explanatory power
a.
Quantitative data is relevant to the nomothetic approach.
This is useful when researchers wish to apply general laws of behaviour.
What is qualitative data?
Qualitative data is data in the form of words or images.
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What is quantitative data?
Quantitative data is data in the form of numbers.
How is quantitative data relevant to the nomothetic approach?
b) It can highlight trends and patterns
b) It can convey subjective experience
c) It has explanatory power
a.
Quantitative data is relevant to the nomothetic approach.
This is useful when researchers wish to apply general laws of behaviour.
What is qualitative data?
Qualitative data is data in the form of words or images.
Qualitative data allows researchers to gain insight into the nature of experience, which makes it high in .
Qualitative data allows researchers to gain insight into the nature of individual experience, which makes it high in ecological validity.
What is primary data?
Primary data is collected first hand by the researcher.
E.g., a researcher collects two sets of scores (from condition 1 and condition 2) after running an experiment.
True or False?
Collecting primary data is expensive and time-consuming.
True.
Collecting primary data is expensive and time-consuming.
This is particularly true compared to the use of secondary data, which can be gathered very quickly and cheaply.
What is secondary data?
Secondary data consists of any research findings/results that are pre-existing.
They have not been collected at source; they are not original data
True or False?
Secondary data cannot provide new insight into existing theories and research.
False.
Secondary data may provide new insight into existing theories and research.
As several studies on the same topic are analysed, this allows the researcher to see patterns that are unlikely to emerge with a single study.
The level of measurement known as nominal data is data in the form of:
a) images
b) percentages
c) categories
c.
The level of measurement known as nominal data is data in the form of categories.
Ordinal data is data which can be:
a) ordinary
b) ranked
c) destroyed
b.
Ordinal data is data that can be ranked.
With interval data, there is an interval between each unit of measurement.
With interval data, there is an equal interval between each unit of measurement.
E.g., centimetres is an example of interval data (the interval between 2 and 3 cm is the same as the interval between 10 and 11 cm).
True or False?
Raw scores are presented in a table.
False.
Raw scores are not presented in a table as they must be converted to descriptive statistics to present an overview of the results.
The data shown on the x-axis of a bar chart is discrete.
Define discrete data.
Discrete data is that which typically only shows information for a particular event, e.g., one testing session.
What is one difference between bar charts and histograms?
a) Bar charts present raw scores, whereas histograms present mean scores
b) Bar charts are used to show differences, whereas histograms show correlation
c) Bar charts have gaps between their bars, whereas histograms have no gaps between their bars
c.
One difference between bar charts and histograms is that bar charts have gaps between their bars, whereas histograms have no gaps between their bars.
On a histogram, the y-axis represents the of each category occurring.
On a histogram, the y-axis represents the frequency of each category occurring.
Scattergrams are used to display the results of .
Scattergrams are used to display the results of correlations.
A normal distribution is around the and is known as a curve.
A normal distribution is symmetrical around the mean and is known as a bell curve.
In a normal distribution extreme outliers fall within:
a) the peak of the curve
b) two standard deviations of the mean
c) the 'tail ends' of the curve
c.
In a normal distribution extreme outliers fall within the 'tail ends' of the curve.
True or False?
A positive skew is one in which most of the values are found towards the right side of the graph, giving a long tail on the left.
False.
A positive skew is one in which most of the values are found towards the left side of the graph, giving a long tail on the right.
A very easy maths test might see most students score at the higher end of the mark scale, which is an example of a:
a) positive skew
b) negative skew
c) normal distribution
b.
A very easy maths test might see most students score at the higher end of the mark scale, which is an example of a negative skew.
As the test is so easy, there are very few in the class who scored towards the left end of the tail (where the low scores reside).