Question 1: Explain what a correlational study aims to investigate and how it differs from an experimental study.

Answer: A correlational study investigates whether there is a relationship between two variables by measuring both without manipulating them. Unlike an experimental study, it does not establish cause and effect because variables are not controlled or changed.

Question 2: Describe a scenario in which a researcher might use a correlational study to explore the relationship between sleep duration and academic performance.

Answer: A researcher measures students' average hours of sleep per night and their recent exam scores to see if there is a relationship between sleep and performance, without trying to change students' sleep habits.

Question 3: Identify two variables that could be examined in a correlational study about physical activity and happiness levels.

Answer: Variables could include the amount of physical activity (e.g., hours of exercise per week) and happiness levels (e.g., scores on a happiness questionnaire).

Question 4: What does a positive correlation between two variables indicate? Provide an example.

Answer: A positive correlation indicates that as one variable increases, the other also increases. For example, more hours of study might be associated with higher exam scores.

Question 5: What does a negative correlation between two variables indicate? Provide an example.

Answer: A negative correlation indicates that as one variable increases, the other decreases. For example, increased screen time might be associated with lower sleep quality.

Question 6: Describe a limitation of correlational research when it comes to understanding cause-and-effect relationships.

Answer: Correlational research cannot establish causality because it only shows that two variables are related, not whether one causes the other or if a third factor influences both.

Question 7: A study finds a strong positive correlation between ice cream sales and outdoor swimming pool attendance. What might this suggest, and what should researchers be cautious about?

Answer: It suggests that both increase together, possibly due to warm weather. Researchers should be cautious not to assume that eating ice cream causes swimming or vice versa; a third factor (hot weather) could be influencing both.

Question 8: Draw a scatter plot showing a perfect negative correlation between variables X and Y. Label the axes and describe what the points would look like.

Answer: A scatter plot where the points form a downward slope from top-left to bottom-right, indicating as X increases, Y decreases. The axes should be labeled appropriately, e.g., 'Hours of Exercise' and 'Stress Levels'.

Question 9: Sketch a simple diagram of how you might represent a positive, negative, and no correlation between two variables using scatter plots. Include three large blank spaces for each plot.

Answer: Three scatter plots: one with an upward-sloping line (positive correlation), one with a downward-sloping line (negative correlation), and one with points scattered randomly around the plot (no correlation).

Question 10: Explain why it is important to not infer causality from a correlational study, using an example involving diet and health.

Answer: Because correlation does not imply causation, even if a study finds that healthier diets are associated with better health, it does not mean the diet causes the health improvement. Other factors, like exercise or genetics, might influence both.