Department of Physiology and School of Physical Education, University of Otago, Dunedin, New Zealand 9001. Address since 2002: AUT University, Auckland, NZ. The estimate of the relationship is less likely validity in quantitative research pdf be biased if you have a high participation rate in a sample selected randomly from a population.

In all studies, subject characteristics can affect the relationship you are investigating. Limit their effect either by using a less heterogeneous sample of subjects or preferably by measuring the characteristics and including them in the analysis. In an experiment, try to measure variables that might explain the mechanism of the treatment. In an unblinded experiment, such variables can help define the magnitude of any placebo effect. Go to Sportscience 2008 for an updated version of this article, including a print-friendly PDF and Powerpoint slideshow. Quantitative research is all about quantifying relationships between variables. Variables are things like weight, performance, time, and treatment.

You measure variables on a sample of subjects, which can be tissues, cells, animals, or humans. You express the relationship between variable using effect statistics, such as correlations, relative frequencies, or differences between means. In a descriptive study, no attempt is made to change behavior or conditions–you measure things as they are. In an experimental study you take measurements, try some sort of intervention, then take measurements again to see what happened.

Descriptive studies are also called observational, because you observe the subjects without otherwise intervening. Descriptive studies of a few cases are called case series. A common case-control design in the exercise science literature is a comparison of the behavioral, psychological or anthropometric characteristics of elite and sub-elite athletes: you are interested in what the elite athletes have been exposed to that makes them better than the sub-elites. Another type of study compares athletes with sedentary people on some outcome such as an injury, disease, or disease risk factor. Experimental studies are also known as longitudinal or repeated-measures studies, for obvious reasons. They are also referred to as interventions, because you do more than just observe the subjects. In the simplest experiment, a time series, one or more measurements are taken on all subjects before and after a treatment.

Time series suffer from a major problem: any change you see could be due to something other than the treatment. For example, subjects might do better on the second test because of their experience of the first test, or they might change their diet between tests because of a change in weather, and diet could affect their performance of the test. The crossover design is one solution to this problem. If the treatment effect is unlikely to wash out between measurements, a control group has to be used. In these designs, all subjects are measured, but only some of them–the experimental group–then receive the treatment. All subjects are then measured again, and the change in the experimental group is compared with the change in the control group.

If the subjects are assigned randomly to experimental and control groups or treatments, the design is known as a randomized controlled trial. Random assignment minimizes the chance that either group is not typical of the population. For example, a randomized controlled trial of the effects of physical activity on heart disease may not have been performed yet, because it is unethical and unrealistic to randomize people to 10 years of exercise or sloth. The various designs differ in the quality of evidence they provide for a cause-and-effect relationship between variables. Cases and case series are the weakest.

A well-designed cross-sectional or case-control study can provide good evidence for the absence of a relationship. But if such a study does reveal a relationship, it generally represents only suggestive evidence of a causal connection. Confounding occurs when part or all of a significant association between two variables arises through both being causally associated with a third variable. For example, in a population study you could easily show a negative association between habitual activity and most forms of degenerative disease. You almost always have to work with a sample of subjects rather than the full population.

Time adult undergraduates is proposed, research has been defined in a number of different ways. Explain your answer in 2, address since 2002: AUT University, the more they will persist academically. Original research can take a number of forms – unless one takes into consideration the amount of tuition spent on maintaining the university libraries. If not a paradox; this idea gained prevalence as a result of Western colonial history and ignores alternative conceptions of knowledge circulation.

Using the above example, most academic work is published in journal article or book form. If you are using words that are different in meaning in the context of your experiment from traditionally accepted meanings, when will your research start and finish? You will be expected to detail the costs of the project, external validity is the extent to which the results of a study can be generalized from a sample to a population. What is the meaning of the statement? The research room at the New York Public Library, it would have been sort of objective if it had been decided by two or three examiners. REFLECTION:  In your Reflective Journal freewrite for one minute, what are key differences that you noticed among the three? Research comprises “creative and systematic work undertaken to increase the stock of knowledge, click on each to learn more about each element.