Not all types of data analysis help determine how one variable impact the other. In some cases, the researchers use methods suitable for showing that there is a correlation between variables or that there is none. However, this does not provide insight into understanding how one issue may be connected to the other. This paper will discuss the types of research methods, which help determine the cause and effect.
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To explore how researchers can study the cause and effect, one can use a hypothetical experiment, where the goal is to determine if the consumption of carbs leads to obesity. There are multiple research methods one can use to collect data to answer this question. For example, through a questionnaire were respondents with and without obesity answer questions about their eating habits. Although the researchers will receive some data, and in the case of quantitative studies, statistical data, there is a high possibility that the participants were biased or did not accurately account for the number of carbs they eat. Hence, such research may show a negative correlation between the two variables, meaning that the more carbs a person eats, the slimmer they become. Considering the selected research method, potential bias, and the inability of an independent researcher to verify the words of the participants, this study produces results that are questionable because the cause and effect of the negative correlation are unclear. This relationship can be explained by a plethora of factors. For example, the participants may favor carbs and do sports regularly, which allows them to stay fit. Without being able to see the daily routines of the participants and account for all the factors that can modify the results, one cannot be sure if a phenomenon is caused by a specific event.
In a controlled experiment, the researchers get to manipulate the different aspects that may affect the results. The conditions in which the participants are placed are continuously controlled by the scientists. Therefore, using the previous example, scientists can control what food the participants eat, how much they exercise to see if the assumption about the carbohydrates is valid. All of the potential participant bias and the effect of other variables are examined in the study, therefore one can conclude the cause and effect.
This type of research implies that one uses a hypothesis with two variables — independent and dependant. The former is the cause, while the latter is the effect, which helps establish how the two variables are connected. For instance, “if an individual consumes 400 grams of carbs per day, then they will become obese” is an example of a hypothesis for an experiment where the cause and effect are examined. Here, the anticipated cause is a high amount of carbs in the diet, and the result is obesity. To account for all other factors that may cause obesity, the researchers have to observe the participants constantly to verify how many carbs they are eating, which can only be done in a controlled experiment.
One major drawback of the controlled experiments is that the findings cannot be generalized. This is because the conditions in a laboratory where these experiments occur differ from those of the real world. This is because these types of studies do not rely on external validity as an essential procedure. This validity measure is an application of the findings outside of research or checking if the experiment’s results are the same in the real world.
The nature of a controlled experiment does not imply that external validity should be measured. In practice, this means that although the participants who ate more carbs during this experiment were slimmer, in real-life conditions, people may become obese on such a diet. For example, because during the investigation, the researchers controlled the number of calories the subjects consume while in real life, most people do not do this. Therefore, this research method usually has lower validity when compared to other research strategies. Despite this drawback, this type of design is beneficial when establishing the cause and effect relationships. However, it is not used in all studies, mainly to answer all research questions because the nature of the research question may require examining participants in real-life conditions. For example, a study aiming to assess the participant’s view of carbohydrates can be performed as a survey or an interview, since it will allow one to collect the necessary data.
Overall, this essay explores the controlled experiment method as a method for determining the cause and effect relationships. Although other methods can be used to collect data, this type of experiment is the only approach that can be relied on when discussing the cause and effect. Although the design of controlled research allows a conclusion about the impact of one variable on the other, they cannot be generalized for the entire population.
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Today I found out. (2019). The appalling Tuskegee Syphilis experiment [Video]. Web.