Research in Physical Education Questions and Answers

Answer: D

The research form is phenomenology.

Phenomenological research seeks to understand how individuals experience a phenomenon, for example what it is like for athletes to return from serious injury. The researcher collects detailed accounts, usually through in-depth interviews, and describes the essence of the lived experience.

Grounded theory aims to generate a theory from data. Ethnography studies the culture of a group, usually through long participant observation. A case study examines a single case, such as a team or programme, in depth, rather than the meaning of an experience.

Answer: D

The sample is a convenience sample.

A convenience sample is made up of the participants who happen to be easily available to the researcher. Here the schools taking part are simply those working on Saturday, the day the researcher chose to conduct the study; they were not selected by any chance procedure, so the sample is one of convenience and may not represent all urban schools.

A random sample gives every member of the population an equal chance of selection, a stratified sample draws from defined subgroups, and a cluster sample randomly selects whole groups such as schools.

Answer: D

Multistage cluster sampling helps in all these situations, so the answer is All of the above.

In multistage cluster sampling the researcher randomly selects large clusters, such as districts, then smaller clusters within them, such as schools, and finally individuals.

This is useful when the population is widely dispersed geographically, because data collection is concentrated in a few selected areas, which saves time and money on travel. And because selection is random at every stage, it remains a probability sample whose results can be generalised to the population. Each statement is a genuine advantage.

Answer: C

A correlation near zero could mean either no relationship or curvilinear one.

The Pearson correlation coefficient measures only the strength of a linear relationship. A value near zero says there is no straight-line relationship, but the variables may still be strongly related in a curve. Arousal and performance, for example, follow an inverted U, which can give a correlation close to zero.

So it is wrong to conclude that no relationship exists, or that the relationship must be curvilinear, and a linear relationship is exactly what a zero correlation rules out. A scatter plot shows which case applies.

Answer: B

A stricter significance level increases the chance of a Type II error.

A Type I error is rejecting a true null hypothesis, and its probability equals the significance level. Moving the level from 0.05 to 0.01 makes it harder to reject the null hypothesis, which reduces the risk of a Type I error.

The price is that a real effect is more likely to be missed: failing to reject a false null hypothesis is a Type II error, so its probability rises. A Type III error, the right answer to the wrong question, is not affected by the significance level.

Answer: D

The population variance is 81.

The variance is the square of the standard deviation:

\[ \sigma^{2} = 9^{2} = 81 \]

The other options come from common slips: 9 repeats the standard deviation, 3 is its square root, and 21 has no basis in the calculation. Remember that the standard deviation is the square root of the variance, so going from standard deviation to variance means squaring.

Answer: C

Body weight is a continuous variable.

A continuous variable can take any value within a range, limited only by the precision of the measuring instrument: a student may weigh 58 kg, 58.4 kg or 58.43 kg. Weight, height, time and distance are all continuous.

A discrete variable takes only separate, countable values, such as the number of goals scored or the number of students in a class. A qualitative variable describes a category rather than an amount, such as gender or playing position. Since weight is a measured quantity that varies continuously, 'None of the above' is also wrong.

Answer: B

The correct code is (iii) (i) (ii) (iv).

• Quantitative observation is standardized: the observer records predefined behaviours in a fixed, countable way.
• Qualitative observation is open-ended, observing all potentially relevant phenomena rather than a fixed checklist.
• Laboratory observation is done in a laboratory, under controlled conditions.
• Naturalistic observation is done in real-world settings, where the behaviour occurs naturally.

All four options agree on (iii) for quantitative observation; options A, C and D then mismatch the laboratory and naturalistic settings or the qualitative type.

Answer: C

This is the Hawthorne effect.

The name comes from the studies at the Hawthorne Works of the Western Electric Company near Chicago in the 1920s and 1930s, where workers' output rose whatever change was made to their conditions, apparently because they knew they were being studied and given attention. In research it is a threat to validity: participants perform differently simply because they are observed.

Reactive effect is a broader term for any change caused by the measurement process itself, and interactive effect refers to the combined effect of two variables. The 'Avis effect' is an informal name for the extra effort of an underdog, not for the effect of being observed.

Answer: B

Theoretical saturation is the point at which a concept is so well developed that no further data collection is necessary.

The term comes from grounded theory (Glaser and Strauss). The researcher keeps sampling and coding data until new data no longer add new properties or dimensions to the categories being developed. At that point the categories are saturated, and further data collection would only repeat what is already known.

It is not about testing a chosen theory repeatedly, which is the deductive approach of quantitative research. It has nothing to do with using too many theories, and statistical tests are not part of qualitative analysis.