This question asks what can be concluded from an observational study finding people who spent more time outdoors reported higher happiness. The data shows an association between outdoor activity and self-reported happiness levels. Answer B correctly identifies this as a correlation without claiming causation. Option A inappropriately claims causation, option C makes an absolute statement about all happy people, and option D claims outdoor activity is the sole determinant of happiness. Observational studies can identify correlations but cannot establish that one variable causes changes in another without experimental manipulation and controls.

This question asks what conclusion is most appropriate from a positive correlation between study hours and GPA. The data shows that students who study more hours tend to have higher GPAs, indicating a positive association between these variables. Answer D correctly identifies that while there is an association, causation cannot be determined from correlational data alone. Options A and C incorrectly claim causation (that studying more causes higher GPA), while option B suggests reverse causation, but none of these causal claims can be supported by correlation data. When dealing with correlational studies, always remember that correlation does not imply causation.

This question asks which limitation affects the conclusion in a diet and weight loss study. The study found that people eating under 1500 calories lost weight faster, but this doesn't account for other factors that might influence weight loss. Answer A correctly identifies that not considering exercise habits is a major limitation, as exercise could be a confounding variable affecting the results. Options B incorrectly claims the study proves causation, option C makes an unsupported assumption about diet consistency, and option D describes participant motivation rather than a methodological limitation. When evaluating study limitations, look for important variables that weren't controlled or measured.

This question asks which statement about survey data on exercise habits and health status is justified. The question doesn't specify what the survey found, but based on the answer choices, we can infer it found some relationship between exercise and health. Answer B correctly states there is a correlation, which is the most that can be concluded from observational survey data. Options A and D make causal claims that cannot be supported by survey data alone, while option C makes an absolute claim ('all') that would be nearly impossible to support from any real-world survey. Survey data can reveal associations but not prove causation.

This question asks what can be concluded from a survey finding higher job satisfaction among employees with flexible hours. The data shows an association between flexible work arrangements and job satisfaction levels. Answer C correctly identifies this as an association without claiming causation. Option A incorrectly claims causation, option B makes a claim about preferences that wasn't measured, and option D makes an absolute statement ('all') that survey data cannot support. Observational studies like surveys can reveal associations but cannot establish that one variable causes changes in another.

This question asks which statement is justified by survey data finding daily coffee drinkers report higher alertness levels. The data shows a relationship between coffee consumption habits and self-reported alertness. Answer B correctly describes this as an association without implying causation. Option A claims that coffee consumption causes increased alertness, option C makes an absolute statement about all alert individuals, and option D claims coffee is the only factor, all of which cannot be supported by observational survey data. Survey findings can reveal associations but cannot prove causal relationships.

This question asks for the most appropriate conclusion from a study finding that people sleeping 8+ hours reported feeling more energetic. The data shows an association between sleep duration and self-reported energy levels. Answer B correctly identifies this as a correlation without claiming causation. Option A inappropriately claims that sleeping 8 hours causes increased energy, option C makes an absolute statement about all energetic people, and option D claims sleep is the only factor affecting energy. Observational studies can reveal correlations but cannot establish causal relationships without experimental controls.

This question asks which statement is justified by data showing a moderate positive correlation between coffee consumption and stress levels in 200 adults. The study found an association where higher coffee consumption is linked to higher reported stress levels. Choice B appropriately describes this correlation using "tend to report," which accurately reflects the observational nature of the data without claiming causation. Choice A incorrectly implies causation ("increases"), choice C makes an unsupported intervention claim, and choice D contradicts the finding of a positive correlation. In correlational research, the key is distinguishing between demonstrating an association versus proving a cause-and-effect relationship.

This question asks for the most appropriate conclusion based on a study of 150 teenagers showing a strong negative correlation between social media usage and sleep quality. The data indicates that teenagers who spend more time on social media tend to have worse sleep quality. Choice B correctly describes this relationship using "tend to have," which appropriately reflects the correlational finding without implying causation. Choice A incorrectly suggests a causal intervention effect, choice C claims social media is the only cause of sleep problems, and choice D makes an unsupported universal recommendation. Strong correlations still only demonstrate associations, so avoid language that implies one variable directly causes changes in another.

This question asks what conclusion can be drawn from a study of 500 people showing that pet owners reported lower depression scores on average. The data demonstrates an association between pet ownership and lower reported depression levels in this sample. Choice B correctly states this finding using "are less likely," which appropriately describes the observed pattern without claiming causation or making intervention recommendations. Choices A and C incorrectly imply that pets cause reduced depression or can cure it, while choice D makes an inappropriate universal recommendation based on observational data. When analyzing comparative studies, focus on describing the observed differences between groups rather than inferring causal mechanisms.