1 Research: An introduction

In this chapter, you will learn to:

  • identify quantitative and qualitative research.
  • identify the steps in the quantitative research process.

1.1 How do we know what we know?

People once believed that all life commonly and regularly arose spontaneously from non-living matter ('spontaneous generation').

Furthermore, any life form could be created on-demand from non-living things by following recipes.

J. B. van Helmont26 gave this recipe:

If a soiled shirt is placed in the opening of a vessel containing grains of wheat, the reaction of the leaven in the shirt with fumes from the wheat will, after approximately twenty-one days, transform the wheat into mice.

--- Translation of van Helmont27

We now know that this isn't true... But how did van Helmont reach this conclusion?

By observing.

This is what van Helmont had observed, and he proposed a possible explanation (a scientific hypothesis) to explain that observation. And why was his hypothesis rejected? Because of the scientific process.

Spontaneous generation was proposed after making observations. van Helmont then proposed a possible explanation (a scientific hypothesis), but this hypothesis was then rejected when evidence contradicted the hypothesis. So, a new hypothesis was proposed and tested, based on further evidence. Briefly, this is the evidence-based, scientific process.

More recently, cigarette smoking was declared harmful by applying the scientific process. As recently as 1978, the verdict on the dangers of smoking was still being debated:

...many eminent persons, committees and commissions have unanimously concluded that lung cancer 'is almost entirely due to cigarette smoking'. I once shared this view, but having now studied the evidence in more detail and from new angles I feel unable to reach a definitive conclusion...

--- P. R. J. Burch,28 p. 456

All scientific knowledge emerges in a similar way: Observations lead to hypotheses, which are tested against the evidence.

The hypothesis is then either:

  • rejected if the hypothesis is not consistent with the available evidence; or,
  • temporarily accepted if the hypothesis is consistent with the available evidence.

Notice the approach: the hypothesis is temporarily accepted if it fits the available evidence. This acceptance is only temporary, as contradictory evidence may eventually emerge in the future.

Hypotheses that have been supported by large amounts of evidence, over a long period of time, are sometimes referred to as laws, often within a given scope of application (for example, the 'law of conservation of energy'). In other words, these laws could be amended, contradicted or their scope changed as new evidence emerges.

Knowledge in all scientific disciplines is based on a similar process:

  • How do we know the gestation length for Gilbert's Potoroo?29
  • How do we know that paracetamol eases pain?30
  • How do we know that exercise is good for us?31
  • How do we know if permeable pavement technology is effective in reducing runoff?32

1.2 The purpose of research

Every scientific discipline has changed in the last 10 years. Likewise, the next 10 years will also bring change. Scientists, engineers and health practitioners need to know how to adapt to this change.

Every discipline changes, develops, improves, and adapts---usually through research. To remain current with developments in your discipline, you need to understand research, even if you will not be conducting research yourself.

Everyone in science-based disciplines must know the language, tools, concepts and ideas of research: Research is the foundation of science.

Research seeks to

...confirm, refute or extend previous findings, and potentially reveal new findings...

--- Eleni Anastasiadis, Prabhakar Rajan, and Catherine L. Winchester,33 p. 410.

Scientific research formally answers questions that arise by observing the world through the use of data; that is, science requires evidence-based answers.

While analysis of the data is often viewed as the hardest part of research, sometimes the hardest part is knowing what data to collect, and how to collect it (that is, the study design).

We study both the study design and the analysis of data in this book.

1.3 Evidence-based research

'Evidence-based research' refers to research conclusions based on evidence, rather than hunches, feelings, intuition, hopes, or tradition.

Research conclusions are based on evidence, which comes from analysing the collected data.

Definition 1.1 (Data) Data refers to information (observations or measurements) obtained from a study, as numbers, labels, recordings, videos, text, etc.

Data can come from previously-published studies (Chap. 37). Even so, studies usually leave questions unanswered, or technology develops and new ideas need to be tested, or existing ideas need to be adapted to new technologies, situations and knowledge.

In these cases, data comes from new evidence, through research.

Definition 1.2 (Data set) A data set refers to a structured collection of data from a study.

1.4 Using software in research

Many people use spreadsheets (such as Microsoft Excel) for analysis of data in research.

Using spreadsheets for research requires extreme care; many extremely expensive and dangerous errors have been made due to using spreadsheets,34 including problems when reporting the 2020 COVID-19 pandemic.

These problems may emerge for many different reasons:

  • Spreadsheets can automatically alter the entered data (for example, reformatting entries as dates if the spreadsheet thinks the data should be a date), even when not appropriate. This has had dire consequences.35

  • Spreadsheets may include formulas with errors,36 that are incredibly difficult to locate and hence fix.37

  • Spreadsheets do not leave a record of how the data have been analysed or prepared; for example, formulas can be very difficult to understand and parse.

    Keeping a record of the analysis, preparation of variables, and other operations with the data are part of what is called reproducible research.38 Reproducibility ensures, among other advantages, that the results can be checked by the researchers and by others, for accuracy.

  • Excel has bugs39 even in very basic operations.40 After trying to fix these bugs, sometimes they are made even worse.41

Spreadsheets can be used for research and analysis... but you must be very careful!

Many problems with using spreadsheets are due to human error, but spreadsheets make the errors hard to find. Some errors emerge because Excel is being used for purposes it is not really designed for (i.e., scientific analysis).

Using statistical software (such as jamovi, SPSS, R, SAS, etc.) helps avoid many of these problems:

  • They are designed for large data sets.
  • They encourage reproducible research.
  • They allow high-precision formatting and graphics.
  • They are powerful; with some programming skills, almost anything is possible.
  • They are designed specifically for performing statistical analyses and working with data.

In this book, output from the statistical software packages jamovi42 and SPSS43 is sometimes shown.

1.5 Example: Research in action

During 1988/1989, an unusually high number of cases of the Legionella longbeachae infection were observed in South Australia. Why? What could be done to prevent more instances?

The researchers wanted to identify the source of the infection. They noticed that many of those infected were regular gardeners who had recently handled potting mix.

So the researchers proposed a hypothesis, that

... L. longbeachae infection was associated with handling of commercial potting mix.

--- B. A. O’Connor et al.44 p. 35

They designed a study, then gathered data (using a survey) from 100 people: 25 people with the L. longbeachae infection, and 75 similar ('matched', or similar) people without the infection

The researchers described and summarised their data, then analysed the data to reach an evidence-based conclusion: the potting mix was partially responsible for the increase in infection numbers, but other factors were also involved.

The researchers then communicated their recommendations to reduce the future risks of people contracting the infection:

Raising people's awareness of a possible health risk when using potting mix should continue in order to protect against L. longbeachae infection.

--- O’Connor et al.45 p. 39

In the rest of this book, we learn about the six components of research. See if you can arrange the steps of research into the correct order.

1.6 The components of research

The research process typically follows the process in Fig. 1.1. This is not always possible or practical, and the process is not always linear (researchers may jump from step to step as necessary). Nonetheless, following this process is good practice when possible.

The six basic steps in research

FIGURE 1.1: The six basic steps in research

All these steps are discussed in this book:

  • Asking the question: Chap. 2.
  • Designing the study: Chaps. 3 to 9.
  • Collecting the data: Chap. 10.
  • Describing and summarising the data: Chaps. 11 to 14.
  • Analysing the data: Chaps. 15 to 36.
  • Reporting the results: Chaps. 37 and 38.

In the rest of this book, we learn about the six components of research. Click on the purple plus-sign to learn more about each step.

1.7 Types of research

Research is a formal, evidence-based approach to learning or creating new information. The two main types of research are qualitative and quantitative research.

These two types of research are different and complementary (Table 1.1, which is a gross generalisation!).

TABLE 1.1: Comparing qualitative and quantitative research
Qualitative Aspect Quantitative
Feelings, opinions What Objective data
Suggest hypotheses Why Tests hypotheses
Detailed Conclusions General
Words, pictures, ... Data Numbers, statistics
Small number Size Can be large numbers
Time-consuming Time More efficient
Rarely generalisable Applicability Sometimes generalisable
Interviews, focus groups, diaries Examples Experiments, surveys measurements

Both methods have advantages and disadvantages, and both can be, and often are, used together: using a combination of qualitative and quantitative research is called mixed methods research.

The decision to use qualitative, quantitative or mixed methods approaches should depend on the research problem, not the skills of the researchers.

Briefly, qualitative research leads to a deeper understanding of what is being studied, usually about a very narrowly-defined group. Meanings, motivations, opinions or themes often emerge from qualitative research. Approaches to qualitative research46 include grounded theory, action research, and ethnography.

Briefly, quantitative research summarises and analyses data using numerical methods, such as averages and percentages. Specific examples of quantitative research approaches include observational studies and experimental studies.

In quantitative research, typically information about a larger group of interest (a population) is found from a subset of the population (a sample)

... quantitative data gets you the numbers to... [support] the broad general points of your research. Qualitative data brings you the details and the depth to understand their full implications.

--- SurveyMonkey website, October 2019.

Definition 1.3 (Quantitative research) Quantitative research summarises and analyses data using numerical methods, such as producing averages and percentages.

This book focuses on quantitative research.

Example 1.1 (Types of research) Suppose we wish to learn about the perceived benefits and barriers for adopting electric vehicles (EVs) (C. Angelo Guevara, Esteban Figueroa, and Marcela A. Munizaga;47 also see Ona Egbue and Suzanna Long48).

A qualitative research study might use a focus group to interview:

  • A small group of people who have purchased EVs.
  • Another small group of people who have not purchased EVs.

The researchers ask about their perceived benefits and barriers for adopting EVs.

A quantitative research study might survey a larger number of buyers and non-buyers of EVs, and ask the buyers' age, sex, and car purchased.

The survey may ask respondents to identify attributes of car buying (such as energy costs; maintenance costs; range; purchase price; etc.) as either as advantages, disadvantages, or as indifferent when purchasing an EV.

The survey responses could be analysed by numerically summarising, and comparing, the responses for buyers and non-buyers of EVs.

A mixed methods study (such as Guevara, Figueroa, and Munizaga49) may combine both of the above.

1.8 Quick review questions

Consider the research questions below.

Which are likely to be answered using quantitative research studies, and which are likely to be answered using qualitative research studies?

  1. What percentage of the population experiences minor side-effects from this medication?
  2. What is the average number of roof-top solar panels installed on domestic properties?
  3. Why do people opt to purchase an electric car?


  1. The RQ requires numerical summaries of the data: 'What percentage...' This RQ would be answered using a quantitative RQ.
  2. The RQ requires numerical summaries of the data: 'What is the average...' This RQ would be answered using a quantitative RQ.
  3. The RQ does not require numerical summaries of the data. This RQ would be answered using a qualitative RQ.

1.9 Exercises

Selected answers are available in Sect. D.1.

Exercise 1.1 Consider the research question: 'Which of three different junctional tourniquets are quickest, on average, to apply?'

Is this RQ likely to be answered using a quantitative research study, or a qualitative research study?

Exercise 1.2 Consider the research question: 'Why do people dump rubbish in mangroves? '

Is this RQ likely to be answered using a quantitative research study, or a qualitative research study?