Is it scientifically accurate to generalise a sample’s results to the specified target population?

Ideally, to test a hypothesis you would use an entire population as your sample. This would ensure the most accurate results. However this is not feasible in most cases, as participation from every individual is very unlikely to happen. This is why we use samples, as it is a less time-consuming, more cost-effective way of collecting data.

However despite the manual and economical benefits, this process has many weaknesses. Quite often convenience sampling occurs, where students offer themselves to participate. An example of this is how we personally offer our own participation for the third year projects on SONA. Although this is a quick and easy way to gather participants, it is certainly not scientifically accurate, as people who proactively offer to participate in studies may have certain characteristics that do not represent those of the whole population.

A different approach is random sampling, a procedure where each member of the population has an equal chance of being chosen. Although this prevents sample bias, it is found that quite often a study will want to look at the diversity in a population, and therefore maximum variation sampling is used which finds unusual and extreme participants.

The vast range of sampling methods makes it difficult for researchers to find which technique will give them the results than can be most accurately generalised to the rest of society. One major issue is sampling bias, where a specific section of the population is over-represented due to its dominance (e.g. an age group or race).  As anticipated, a larger sample prevents this.

Piaget’s influential work on children’s cognitive development highlights some of the sampling issues. His theory was primarily based on the development of his own three children. He used this minute sample to generalise his theory to children across the world, and although evidence has shown his timeline for cognitive development occurs in industrialised societies (Goodnow, 1969), in other countries where education is poor the children reach each stage later than Piaget suggested (Dasen, 1975).

It is not to say however that the bigger the sample the ‘better’ the findings. Although large samples do increase the statistical strength of your hypothesis, studies with small samples (e.g. case studies) can provide us with valuable insight into psychological conditions and ideas. Although case studies such as Freud’s do not provide us with theories to be generalised to the wider population, the extensive detail produced opens doors for future research on a larger scale. Funding will always be more accessible to those who have prior research showing their ideas producing results.

Inevitably, the generalisation of a sample’s result is continuously done in psychology. It allows us to make predictions about the wider society that one simply doesn’t have the time and money to do accurately. As long as one recognises the issues of over-generalisation, and perhaps sometimes accepts that not all samples can represent all of the population and restricts conclusions because of this, accepted and universal theories can still be created.

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Is it possible to prove a hypothesis?

A hypothesis is a statement or idea that gives an explanation to a series of observations. Therefore at first glance, one would assume that the ability to prove a hypothesis is not just possible, but a regular occurrence in psychology.

However as psychologists we know this is not entirely correct. In fact, a hypothesis can never be proved, but simply fail to be disproved. This idea comes from Karl Popper, a philosopher who brought in the idea that inherent testing of a hypothesis is what makes it scientific. For example the idea that “All swans are white” seems plausible and supported; however the sighting of one black swan disproves the whole theory.

This idea of disproving theories to develop more advanced replacements can only be done if the hypothesis is falsifiable. This is the notion that a theory can be disproved, and through this method improvements have broadened our understanding throughout psychology. An example of this is through the advances to Atkinson and Shiffrin’s multi-store model (1968) through falsification, as more recent models have shown an improvement upon it’s inadequacies (Baddeley and Hitch’s working memory model).

At the end of every research process new hypotheses are created, thus perpetuating the scientific process. This in itself can be an advantage, as it allows psychology to progress to deeper levels. However the problem arises when a theory isn’t falsifiable. An example of this is Maslow’s hierarchy of needs, as the vast amount of assumptions of how humans develop is based on Maslow’s interpretations. Therefore if the theory cannot be disproven, some may consider accepting it. This is not scientific as it cannot go through rigorous testing like other theories can. As Popper said, “Those among us who are unwilling to expose their ideas to the hazard of refutation do not take part in the game of science”, and for that reason they cannot be scientifically accepted.

As Einstein said “Under what conditions would I admit that my theory is untenable?” Throughout his career he would continuously put his theory on the line by stating what exactly could falsify his work, as although a hypothesis may seem certain and proven at the time, a single observation in the future can completely change that.

However to many this approach may seem extremely uninspiring, and the idea of never having an accepted hypothesis, instead one that will constantly be falsified doesn’t correspond with the success many psychologists experience due to their ideas. Skinner’s operant conditioning for example has been widely accepted throughout psychology, and although elements of his work have been improved upon by others, is it appropriate to ‘reject’ such astonishing discoveries that have lay the foundations for the behaviourist approach?

Although the idea is pessimistic, the reality is that if one was able to ‘prove’ a hypothesis, it could stilt future research that could have developed from the theory. A hypothesis should not be thought of as labour from an individual, but a development from the previous, and a foundation for the future.