1.4
Results of an experiment may suggest that the independent and dependent variables are related.
The relationship between variables, the correlation, can be positive, both variables increase or decrease together. Or negative, one increases and the other decreases.
Additionally, there may be no relationship between the variables. To determine if an apparent correlation reflects a direct cause-and-effect association, a causal relationship, additional control experiments must be performed.
For example, consider an ecosystem where geckos, parasitic ticks, and crows coexist. Crows prey on geckos, and ticks feed on animal blood.
A researcher examines five different gecko populations and finds that the number of geckos without tails decreases as the number of parasitic ticks increases, showing a negative correlation.
Based on this negative correlation alone, the researcher cannot tell whether the parasite directly causes tail loss.
However, if the researcher had counted the number of crows at each location, he may have found a positive correlation between the number of crows and the number of tailless geckos.
And after examining the crows' stomach contents, he would have also found the missing gecko tails.
Together, these observations suggest that crows cause tail loss in geckos.
But a correlation between two variables does not necessarily establish causation. A third variable may affect both variables, creating a correlation between them.
통계적 검정은 독립변수와 종속변수 사이에 관계, 즉 상관관계가 있는지를 계산할 수 있습니다. 변수 사이의 관계는 상관관계를 나타내지만, 원인과 결과를 나타내지는 않습니다. 직접적인 원인-결과 관계를 확인하려면 추가적인 통제 실험이 필요합니다. 변수 사이에 일관된 관계가…
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