Research in Physical Education Questions and Answers

Answer: B

The hypothesis that predicts a relationship is the alternative hypothesis.

In hypothesis testing, the null hypothesis states that there is no relationship or difference between the variables, and the alternative (research) hypothesis states that there is one. The test is designed to see whether the evidence is strong enough to reject the null in favour of the alternative.

The null hypothesis predicts the opposite, no relationship. A descriptive hypothesis describes the characteristics of a single variable. 'Correlation hypothesis' is not a standard category of hypothesis.

Answer: C

Classification by mother tongue is qualitative classification.

Data are classified qualitatively when they are grouped by an attribute that cannot be measured numerically, such as language, religion, sex or occupation. Mother tongue is such an attribute: people can be counted in each language group, but the language itself is not a number.

Geographical classification groups data by place (state or district), chronological by time (year or month), and quantitative by a measurable variable such as age, height or income.

Answer: C

The data should be analysed with a chi-square test.

The researcher has only counts (frequencies) of people in each of four categories of a single nominal variable. The chi-square goodness-of-fit test compares these observed frequencies with the frequencies expected under the null hypothesis (for example, an equal preference for each type):

\[ \chi^{2} = \sum\frac{(O - E)^{2}}{E} \]

A t-test and a one-way ANOVA compare means of a measured (interval or ratio) variable between groups, and regression predicts one measured variable from another. With category counts, there are no means or scores to compare.

Answer: D

The correct option is (A) is false but (R) is true.

The Reason is the correct definition of the mode: the score that occurs with the greatest frequency.

The Assertion is false. The mode is the least reliable measure of central tendency: it is based on a single most frequent value, can change sharply with small changes in the data, may not be unique, and fluctuates more from sample to sample. The mean is the most reliable (stable) measure, because it uses every score.

So any option calling the Assertion true is wrong.

Answer: D

The correct option is only II is true.

Statement II is correct: the standard error of the mean is the standard deviation of the sampling distribution of the mean.

Statement I is false. The standard error falls with the square root of the sample size, not in direct proportion to it:

\[ SE_{M} = \frac{\sigma}{\sqrt{N}} \]

so a sample four times larger halves the standard error. Statement III is also false: a statistic is a characteristic of a sample, while a characteristic of a population is a parameter. Every option including I or III is therefore wrong.

Answer: B

The correct match is a-iii, b-iv, c-i, d-ii.

• The F-test is the test statistic of the analysis of variance (ANOVA).
• The median is a measure of central tendency.
• A test of correlation uses the coefficient of correlation.
• The standard deviation measures variability.

The other codes pair at least one concept wrongly, for example the F-test with the correlation coefficient or central tendency with the standard deviation.

Answer: C

The keyed answer is both (A) and (R) are true and (R) is the correct explanation of (A).

The Assertion is true: statistical prediction of one variable from another is done with a regression equation, such as \(Y' = a + bX\), fitted to paired data.

The Reason is true: how accurate those predictions are depends on the size of the correlation. The standard error of estimate is

\[ SE_{est} = \sigma_{Y}\sqrt{1 - r^{2}} \]

so it shrinks to zero as \(r\) approaches 1 and equals the full standard deviation when \(r = 0\). Because the regression equation is built from the correlation, and its usefulness for prediction rests on it, the key treats the Reason as explaining the Assertion. The options calling either statement false are wrong.

Answer: D

The technique is purposive sampling.

The population of interest is a small, specific group: U-19 national-level kabaddi players. The researcher deliberately selects participants who have exactly these characteristics, which is purposive (judgemental) sampling. It is used when the study needs a particular kind of subject rather than a cross-section of a large population.

Random, stratified and cluster sampling are probability methods for drawing representative samples from a large, defined population, in which every member has a known chance of selection; they are not needed when the target group itself is narrow and specially chosen.

Answer: B

The purpose of a pilot study is to test research instruments.

A pilot study is a small-scale trial run of the planned research on a few subjects. It checks whether the questionnaires, tests and procedures work as intended, whether instructions are clear, how long testing takes and what problems arise, so they can be corrected before the main study.

Final data are collected in the main study, not the pilot. Analysing data and reporting findings are later stages of research; a pilot may give a rough idea of the analysis, but that is not its purpose.

Answer: A

Observational studies are most useful when you want to gather detailed insights on behaviors in natural settings.

In an observational study the researcher watches and records behaviour as it occurs, without manipulating it, for example how pupils interact during a physical education lesson or how players behave in a match. This gives rich, realistic information about behaviour in its natural context.

Collecting numerical data quickly is better done with questionnaires or tests, open-ended answers come from interviews or questionnaires, and controlling all variables is the aim of an experiment, the opposite of observing in a natural setting.