Ruling Out Rival Hypothesis

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Ruling out rival hypotheses As discussed in lecture notes (Ornstein, 2015), when ruling out rival hypotheses it is important to ask “are there any alternative hypotheses that could explain this pattern of data?” The claim that celery is the new magic weight loss veggie fails to exclude other plausible explanations. A rival hypotheses that was not taken into consideration was the possibility that other consumed food contributed to a participant’s weight loss. Perhaps those who ate more servings of celery also consumed more servings of different vegetables, ultimately leading to loss in weight. One way to rule out rival hypotheses would be to create a control group where participants are not allowed to eat celery and an experimental group where participants are allowed to eat celery. At the end of the experiment, results collected from the food journals will be compared and any major differences between the two groups will be verified. Correlation vs. Causation…show more content…
(2014) explains the principle of correlation versus causation as an association between two things that does not imply a cause effect relationship. Simply measuring two different things and comparing them does not say anything definitive about whether one of these things caused the other. In this scenario, the correlation between the consumption of celery and weight loss does not demonstrate a causal connection between the two. The experiment fails to rule out the possibility of other variables, such as exercise and/or dietary restrictions, to explain why some participants lost more weight than others. The isolation of a single variable to explain weight loss is a difficult claim to make, however, its exaggeration can be reduced with the introduction of a control group (what should the control be) and/or an exercise
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