data handling types interpretation and display of data

Quantitative data is data in the form of numbers.

a. Quantitative data is relevant to the nomothetic approach. This is useful when researchers wish to apply general laws of behaviour.

Qualitative data is data in the form of words or images.

Qualitative data allows researchers to gain insight into the nature of individual experience, which makes it high in ecological validity.

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. 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.

Secondary data consists of any research findings/results that are pre-existing. They have not been collected at source; they are not original data

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.

c. The level of measurement known as nominal data is data in the form of categories.

b. Ordinal data is data that can be ranked.

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).

False. Raw scores are not presented in a table as they must be converted to descriptive statistics to present an overview of the results.

Discrete data is that which typically only shows information for a particular event, e.g., one testing session.

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 frequency of each category occurring.

Scattergrams are used to display the results of correlations.

A normal distribution is symmetrical around the mean and is known as a bell curve.

c. In a normal distribution extreme outliers fall within the 'tail ends' of the curve.

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.

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).