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Data handling and analysis are used by psychologists to interpret the data they collect from their studies. When conducting research, psychologists gather, record, and present information, for example, using graphs and charts, so that other people can interpret it.
How psychologists conduct data handling and analysis depends on the type(s) of data collected. The different types of data are as follows:
Descriptive statistics are graphs, tables, and summaries used to identify trends and analyse research data.
The descriptive statistics used in A-Level psychology are measures of central tendency and graphs.
Measures of central tendency are measures of average values in data sets. They include:
Graphs can be used to summarise quantitative data. There are a number of ways you can represent data using graphs:
Control | Drug condition | |
Mean | 119 | 86 |
Standard deviation | 23 | 98 |
Tables are used to show contrasts between a few sets of data. For instance, the table above shows the difference between control and drug conditions according to mean and standard deviation measurements.
Figure 1. A bar chart displaying data. Source: StudySmarter.
Bar charts show the results of different conditions (or variables) using bars of different heights.
Figure 2. A scattergram displaying data. Source: StudySmarter.
Scattergrams present the strength and direction of a relationship between co-variables. They show results using coloured dots across a graph. Researchers may choose to join the dots to show the correlation between different variables.
Data distribution can tell us much about the outcomes of research. Two important types of distribution are the following:
Normal distribution forms a bell-shaped curve, as most data points are clustered towards the central values, while fewer data points are at the extremes.
Figure 3. Graph showing a normal distribution. Source: StudySmarter.
In skewed distributions, the data set skews to the positive (right) or negative (left) side of the graph.
Figure 4. Graphs showing skewed distributions. Source: StudySmarter.
According to psychologist Stanley Smith, there are four levels of measurement (ways of measuring data). They are:
Other ways to measure data include:
Case studies are a type of psychological study in which researchers investigate a singular, real-life case instead of using artificial studies. Case studies are particularly useful when the psychological phenomenon studied is rare and unusual.
One of the most famous case studies in psychology is Phineas Gage’s brain injury (1848). When Gage suffered damage to his prefrontal cortex, his personality completely changed. This has often been cited as evidence that different areas of our brain are responsible for different things. The prefrontal cortex has been found to be responsible for decision-making and emotional processing.
One of the most common forms of analysis of qualitative research, thematic analysis involves closely analysing research to identify common themes.
For example, a researcher interviewing schizophrenics might notice that hallucinations are a common theme.
Figure 5. A notebook showing notes from schizophrenia research, with ‘hallucinations’ and ‘obsessions’ highlighted. Source: StudySmarter.
Inferential testing uses inferential statistics, which is data that allows you to make predictions or inferences.
One aspect of inferential testing involves probability. The accepted level of probability in psychology is 0.05 (5%), which means that there is a less than a 5% chance that the results occurred due to extraneous variables (by chance) and that the hypothesis can, therefore, be accepted.
The above measure of probability is an example of a statistical test. Other important tests and values when we evaluate our research are:
In parametric tests, the use of averages to interpret data, for instance, implies a knowledge of the existing distribution within the population. It is assumed that the data forms a normal distribution.
Non-parametric tests, on the other hand, don’t make any such assumptions about data distribution among the population.
Data handling and analysis are used by psychologists to interpret the data they collect from their studies.
There are different types of data: qualitative, quantitative, primary, and secondary.
Descriptive statistics are graphs, tables, and summaries used to identify trends and analyse research data.
Descriptive statistics include measures of central tendency, graphs, bar charts, and distributions.
Levels of measurement include ordinal, ratio, interval, and nominal.
We can use case studies to investigate psychological hypotheses.
Thematic analysis is used to analyse qualitative data by finding common themes.
Inferential testing includes probability and significance, statistical tests, and parametric vs non-parametric probability tests.
Data handling and analysis are used by psychologists to interpret the data they collect from their studies.
Data analysis is drawing conclusions from data that has been gathered and presented, using methods, such as graphs and charts.
To interpret data so that it can be employed in useful ways.
There are many types of data analysis, including measures of central tendency, graphs, case studies, levels of measurement, inferential testing, (non-) parametric tests, probability and significance, thematic analysis, and more.
Thematic analysis. This is when a researcher looks at qualitative data and looks for common themes.
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