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# Scientific Data Analysis

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A crucial step in conducting research is scientific data analysis. The researcher must find an appropriate scientific method that is reliable and valid to perform the data analysis. There are various scientific data analysis methods, which we will discuss below.

## What are the levels of measurement?

The levels of measurement are also known as scales of measurement. Levels of measurement in statistics describe and classify types of variables and how to measure them. They are designed to help us understand how to interpret the data, what statistical test to use, and what information the data can give us. There are four levels of measurement in psychological research, and they are as follows:

### Nominal

The nominal level of measurement in psychology consists essentially of measurements of 'named' or 'labelled data'. An example of a nominal level measurement question is 'What is your gender?'. So the answers 'male', 'female' and 'other' are forms of nominal data.

### Ordinal

The ordinal level of measurement in psychology is categorical data, and the values have a fixed set or order. An example of a question with ordinal measurement is 'What socioeconomic class do you belong to?'. So the ordinal data could be 'working class, 'middle class', and 'upper- class'.

The order of the data is important because it shows that one has a lower/higher value than the other, but we cannot determine by how much they differ. This type of method is usually used for qualitative data.

### Ratio

Ratio level of measurement in psychology is a type of data that is classified and ranked, there is a clear difference between one point and the next. Ratio data is measured with continuous data. This measure has an absolute value of 0, meaning that the numerical values cannot be less than 0. Examples of data that use a ratio measure are participant height, age, travel speed. Your height cannot be negative, your age cannot be less than 0, and you cannot be travelling at a minus speed.

### Interval

Similar to ratio measurement, interval data is a type of data that can be classified and ranked, meaning there is a clear difference between one point and the next. This data is measured with continuous data. The difference between the two levels of measurement is that interval level data can be less than 0 (0 is not absolute). An example is temperature, which can be recorded at 0 and below.

Tree diagram showing how we can identify the type of data being measured, Manreet Thind, StudySmarter Originals

## How is scientific data collection and analysis performed?

Case studies use different methods of scientific data collection called triangulation. Because of this, there are several methods that researchers must use for scientific data analysis. Examples of the most common methods are described in the following section.

### Observations

Observations are usually recorded and analysed by trained professionals. An example of an analysis procedure is tally counting. In this analysis procedure, two professionals watch the video and count together to observe a particular behaviour or pattern.

The crucial step is to have two trained individuals do the counting, ensuring that the results are reliable. If the results are similar, the study suggests high inter-rater reliability. Therefore, this would indicate that the scientific data analysis method is appropriate for the research study.

Tally counting, Pixabay

### Interviews

Semi-unstructured interviews use open-ended and closed-ended questions to obtain quantitative and qualitative data. To analyse them, notes are taken from these transcripts, which are categorised by themes. This process is called thematic analysis. Data is usually reported by stating the themes and patterns identified and providing excerpts from the transcript as evidence. This form of analysis provides qualitative data.

It enables the researcher and the reader to understand the phenomena in depth. It can be classified as scientific data analysis as it relies on evidence to support the interpretation of the themes, concepts and patterns identified by the researcher. This increases the validity of the research findings.

Interviews, Pixabay

### Personal records

Personal records such as diaries and letters provide qualitative information. The technique of scientific data analysis is quite different from that used for quantitative data. This is because the simplest and most reliable method of quantitative data interpretation is statistical data. Statistical data can be applied to qualitative data that was quantified if the scientific data analysis method is content analysis.

Content analysis is a method of analysis used to identify words, themes, and concepts in qualitative data, such as diaries, and follows a similar protocol to thematic analysis. However, content analysis quantifies words, themes, and concepts to understand their meaning and relationship. The statistical tests used for quantitative data can then be used.

Content analysis, Artem Podrez, Pexels

## Scientific Data Analysis - Key takeaways

• When carrying out research, a crucial step in scientific data analysis, the researcher needs to find an appropriate scientific method that is both a reliable and valid way to carry out the data analysis.
• There are four levels of measurement: nominal, ordinal, ratio and interval.
• case studies can take multiple approaches to analyse data because this type of study usually uses several methods to gather data, known as triangulation.
• Examples of scientific data analysis methods to gather quantitative data are tally counting and content analysis.
• An example of a scientific data analysis method to gather qualitative data is thematic analysis.

## Frequently Asked Questions about Scientific Data Analysis

A crucial step in conducting research is scientific data analysis. The researcher must find an appropriate scientific method that is reliable and valid to perform the data analysis.

In psychology, scientific data analysis should be written per APA (American Psychological Association) regulations.

In psychology, research data analysis is the method researchers use to analyse and understand data concerning phenomena.

The first step is to identify the level of measurement collected from the data and then analyse the data based on the most appropriate, reliable or valid scientific data analysis method. For example, diaries may be analysed using content analysis.

## Final Scientific Data Analysis Quiz

Question

For the following question, what is the appropriate level of measurement that characterises the data: ‘What is your gender’?

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Answer

Nominal.

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Question

What are the characteristics of nominal data?

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Answer

Nominal data is characterised by:

• No order between values – one answer in a questionnaire is as vital as the others, and this is because these data tend not to provide numerical value.
• Nominal values do not overlap – respondents can select only one answer (data that can take only specific values are called discrete data).
• They are not usually used for evaluation calculations but rather for grouping data or participants;
• The common calculations used to represent nominal data are percentages and mode.

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Question

What levels of measurement are used for qualitative data?

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Answer

Nominal.

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What levels of measurement are used for quantitative data?

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Answer

Ordinal.

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Question

What level of measurement is typically used for questionnaires that measure responses using Likert scales?

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Answer

Ordinal data.

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What are the characteristics of ordinal data?

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Answer

• There is no way to measure the numerical value of one response to the next, e.g. researchers cannot determine how much the respondents who answered 3 differ in importance from respondents who answered 5.
• Data based on ranking – there is a difference between the ratings based on the order, but we cannot measure the difference.
• The order of the data is essential, e.g. 1 may reflect a weaker response than 5.

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Question

What type of data is usually available when using a ratio level of measurement?

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Answer

Data that is classified and ranked and that can have an absolute zero.

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Why is ratio data quantitative?

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Researchers can identify the quantifiable difference between the values measured.

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What is the difference between ratio and interval data?

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Answer

The value of 0 is not absolute in interval data, but it is in ratio data.

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What is continuous data?

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Answer

Data that can be of any value.

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What is discrete data?

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Answer

Data that can only have certain values is called discrete data.

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Question

When carrying out research, why is it important to identify the appropriate level of measurement of data?

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Answer

Because it helps us understand:

• how to interpret the data.
• the appropriate statistical test to use.
• the information that the data can give us.

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Question

What is triangulation?

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Answer

Triangulation is using multiple research techniques to collect data.

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Question

What are the different types of scientific data analysis methods for case studies?

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Answer

• Content analysis.
• Thematic analysis.
• Tally counting.

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Question

What is the difference between thematic and content analysis?

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Answer

Thematic and content analysis follow a similar protocol. However, content analysis quantifies words, themes and concepts to understand their meaning and relationship. The statistical tests used for quantitative data can then be used.

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Question

What scientific data analysis method is the most appropriate for personal diaries?

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Answer

Tally counting

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Question

Are there specific data analysis methods for particular data collection methods, e.g., primary sources?

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Answer

No, the type of information the researcher wants to obtain for analysis usually determines the data analysis method.

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Question

Why are two researchers present during tally counting?

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Answer

To ensure inter-rate reliability.

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Question

What are the four levels of measurement?

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Answer

1. Nominal.
2. Ordinal.
3. Interval.
4. Ratio.

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Question

How can we identify if data is ratio or interval?

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Answer

If a variable can have a value of absolute 0, then it can be identified as ratio data. If the value of a variable can be 0 or less than 0, then it is interval data.

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Question

What is scientific data analysis?

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Answer

A crucial step in conducting research is scientific data analysis. The researcher must find an appropriate scientific method that is reliable and valid to perform the data analysis.

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Question

What features are required for the data analysis method to be scientific?

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Answer

Data analysis must be reliable and valid.

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Question

What is the data collection approach case studies take?

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Answer

Triangulation

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How are observations usually analysed?

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Answer

Tally counting

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What is an advantage of tally counting?

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Answer

Due to the presence of two trained professionals the results can be compared, if the same/ similar tallies are found then this means that the scoring is high in inter-rater reliability.

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What is a disadvantage of tally counting?

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Answer

This process requires quantifying qualitative data and so important information concerning the case study may be omitted that may be essential to understanding underlying processes (factors that influence the phenomenon interested in).

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Question

What steps do researchers take to analyse interviews?

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Answer

To analyse interviews, notes are taken from transcripts, which are then categorised based on themes.  The data is usually reported by stating the themes and patterns identified and providing extracts from the transcript as evidence.

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Question

What is the name of the procedure used to analyse interviews?

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Answer

Thematic analysis

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What type of data is generated from thematic analysis

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Answer

Qualitative data

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What is an advantage of thematic analysis?

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Answer

• This process highlights patterns and behaviours that may be an effect or outcome of a situation with evidence. This in-depth information can increase understanding of why certain occurrences happen.
• The researchers may identify unexpected themes, providing guidelines for future research.

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What is a disadvantage of thematic analysis?

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Answer

The data is analysed by the researcher and so themes identified and results may be due to investigator bias, reducing the reliability and validity of findings.

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Question

What is content analysis?

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Answer

Content analysis is an analysis method used to identify words, themes and concepts in qualitative data such as diaries, following a protocol similar to thematic analysis. However, content analysis quantifies words, themes and concepts to understand their meaning and relationship.

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Question

Fill in the blank space. Content analysis is a data analysis method used when                are used as a data collection method.

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Answer

Secondary sources e.g. diaries, letters

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Question

What is an advantage of content analysis?

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Answer

The quantitative data allows easier comparison of results, identification and reporting of trends observed.

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What is a disadvantage of content analysis?

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Answer

Similar to tally counting there are disadvantages of using this analysis method such as potentially omitting data that is vital and researcher bias influencing analysis and reducing the validity of findings.

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Question

What type of data is used in the content analysis?

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Answer

Qualitative.

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What type of data content analysis generates?

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Answer

Qualitative.

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Question

What are examples of data collections when using content analysis as an analysis method?

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Answer

• Interviews.
• Speeches.
• Diaries.
• Letters.

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Question

How many stages of content analysis are there?

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Answer

7

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Question

What sources can researchers use to define categories in their coding system?

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Answer

They can define categories based on the data, previous researchers, and established theories.

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Question

Why is the coding system tested on an extract first?

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Answer

When the researcher tests the coding system on an extract first, they can identify if it is a valid measure of the phenomenon and if any adjustments are needed.

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Question

What is the name of a similar concept to testing analysis systems on an extract first?

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Answer

Pilot study.

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Question

What stage is the data transformed from qualitative to quantitative?

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Answer

Stage 4.

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How is the reliability of the coded data assessed?

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Answer

To do so, it is good to have more than one person do the coding and compare their results to see if they are similar.

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What is done in the final two stages of content analysis?

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Answer

Inferential testing.

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What is an example of how to prepare data for content analysis?

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Answer

Transcribing data.

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Question

What is the difference between content analysis and thematic analysis?

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Answer

The two types of analysis differ in that content analysis quantifies qualitative data (transforms it from qualitative to quantitative), whereas thematic analysis produces qualitative data.

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Question

What are the strengths of content analysis?

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Answer

The strengths of content analysis are:

• The quantitative data allow for easier comparison of results and identification and reporting of observed trends.
• It can have high reliability because the process is standardised, and steps are taken to ensure that multiple researchers coding the data and checking for consistent results do so reliably and in accordance with the established system.
• It is a relatively cheap method.

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Question

What are the weaknesses of content analysis?

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Answer

The weaknesses of content analysis are:

• Researchers may omit vital data if it does not fit into the predetermined theme.
• It is challenging to remain objective in this method:
• There is an increased risk that the researcher bias will influence the analysis, affecting the validity of the results. Researchers actively try to find specific content and may neglect or ignore other content in the hope of searching for their relevant content.
• The context of the data is usually cut out, which can lead to misinterpretation and reduce the validity of the results. When we take out the context, the meaning can change drastically.

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Question

What can inferential tests show?

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Answer

Patterns.

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