Research methods are essential game plans designed to answer research questions in the sport sciences. These designs are selected according to the questions of interest, and statistical analyses are also linked to specific types of designs.
Descriptive studies simply reveal "what is". Descriptive studies are may examine opinions, perceptions, knowledge, and the like. Surveys, qualitative studies, case studies, and trend studies fall into this category. Example: Baseball coaches' opinions and perceptions of drug testing protocols.
Correlational studies describe the extent of relationships or associations between variables, but the relationships noncausal. For example, The relationship between training volume and mile run performance.
Experimental studies show causal relationships between two or more variables. The effect of two weight training programs on 60 meter dash time is an example. It would allow researchers to test the null hypothesis, there is no significant difference between the two methods.
There are numerous types of experimental designs, ranging from pre-experimental (little control) to a variety of true experimental designs that offer considerable control, such as the Solomon's four-group designs.
Causal comparative, or ex post facto (after the fact) designs, compare the effects of two or more attributes (qualities that do not change) variables on dependent variables. For example, the effect of gender on endurance. Causal comparative studies do not explain why outcomes happen the way they do, they just compare differences.
In recent years more and more qualitative research has been conducted in behavioral and social areas of the sport sciences. There is an important distinction between these methods.
Quantitative studies assume that variables and the relationships between them can be identified and objectively measured. The purposes include making causal explanations, predictions, and generalizations. Statistical analyses are at the root of answering the research questions and testing hypotheses.
Qualitative studies assume that variables are complex and interwoven. Accurate measurement is deemed difficult within the social structure. It seeks to understand the athlete's perspective and behaviors. The scientist is the instrument who becomes immersed in a natural setting. Such studies address such areas as personal motivation in exercise adherence or in-depth studies of athletes' experiences during the Olympic Games.
The graphic below, published by The Marketing Directors, summarizes the pros and cons of qualitative vs. quantitative designs.
For more, check out Research Methods for Sport Studies: an excellent resource that is straightforward.