A story on your local news station reports that eating a 1-ounce square of milk chocolate each day reduces the risk of heart disease in rats and that this result is statistically significant. This means that ________.
a. People who eat milk chocolate are healthier than those who do not.
b. The difference between chocolate-eating and chocolate-abstaining rats in heart disease rates was greater than expected by chance.
c. Rats like milk chocolate.
d. Milk chocolate reduces the risk of heart disease.
e. Two ounces of milk chocolate per day is likely to be even better for heart health than 1 ounce.

Verified step by step guidance

1. Step 1: Understand the term 'statistically significant.' In scientific studies, statistical significance means that the observed effect (in this case, the difference in heart disease rates between chocolate-eating and chocolate-abstaining rats) is unlikely to have occurred by random chance. It does not necessarily imply causation or applicability to other populations, such as humans.
2. Step 2: Analyze the options provided. Option (a) suggests a direct comparison between humans who eat chocolate and those who do not, which is not supported by the study since it was conducted on rats. Option (c) is irrelevant to the statistical significance of the results. Option (d) implies causation, which cannot be concluded solely from statistical significance. Option (e) makes an assumption about dosage without evidence from the study.
3. Step 3: Focus on option (b). This option correctly interprets statistical significance in the context of the study, indicating that the difference in heart disease rates between the two groups of rats is greater than what would be expected by chance.
4. Step 4: Eliminate incorrect options based on the study's scope and the meaning of statistical significance. The study does not provide evidence for human health (a), causation (d), or dosage effects (e), nor does it address rats' preferences (c).
5. Step 5: Conclude that the correct interpretation of the study's findings is best represented by option (b), as it aligns with the definition of statistical significance and the context of the experiment.

Key Concepts

Statistical Significance

Statistical significance indicates that the results observed in a study are unlikely to have occurred by chance. In this context, it means that the difference in heart disease rates between rats that consumed chocolate and those that did not is meaningful and not a random occurrence. This concept is crucial for interpreting research findings and understanding their implications.

Correlation vs. Causation

Correlation refers to a relationship between two variables, while causation implies that one variable directly affects the other. The study suggests a correlation between chocolate consumption and reduced heart disease risk in rats, but it does not definitively prove that eating chocolate causes this reduction. Understanding this distinction is essential for evaluating the validity of the claims made in the news report.

Experimental Design

Experimental design involves the planning of a study to ensure that it can effectively test a hypothesis. In this case, the design would include how the rats were assigned to different groups (chocolate-eating vs. non-chocolate-eating) and how heart disease was measured. A well-structured experimental design is vital for drawing reliable conclusions from the data collected.