Wei-Chin designed a self-report inventory to measure how intimate partners express affection and hostility toward each other. The inventory is a list of positive behaviors (e. g., back rubs, holding hands) and negative behaviors (e. g., slamming doors, raising voices). After a wide range of couples completed the inventory, Wei-Chin found that happy couples endorsed all the affection items and unhappy couples endorsed all the hostile items. Which of the following problems prevents Wei-Chin from concluding that happy couples exchange more affectionate behaviors than unhappy couples?

Question

Kayla Padilla

Social Studies

3 July, 06:51

Wei-Chin designed a self-report inventory to measure how intimate partners express affection and hostility toward each other. The inventory is a list of positive behaviors (e. g., back rubs, holding hands) and negative behaviors (e. g., slamming doors, raising voices). After a wide range of couples completed the inventory, Wei-Chin found that happy couples endorsed all the affection items and unhappy couples endorsed all the hostile items. Which of the following problems prevents Wei-Chin from concluding that happy couples exchange more affectionate behaviors than unhappy couples?

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Summer Alvarez · Answer 1

This question is incomplete, here's the complete question.

Wei-Chin designed a self-report inventory to measure how intimate partners express affection and hostility toward each other. The inventory is a list of positive behaviors (e. g., back rubs, holding hands) and negative behaviors (e. g., slamming doors, raising voices). After having a wide range of couples complete the inventory, Wei-Chin finds that happy couples endorse all the affection items and unhappy couples endorse all the hostile items. Which of the following problems prevents him from concluding that happy couples exchange more affectionate behaviors than unhappy couples?

1. sentiment override

2. item-overlap problem

3. correlation does not imply causation

4. social desirability effect

Answer: 3. Correlation does not imply causation.

Explanation:

Correlation is a statistical technique that evaluates how much two variables are linearly related, meaning they change together. However, two variables being correlated does not necessarily mean that one causes the other. Causation states that any change in a variable will cause a change in another variable.

The fact that happy couples endorsed all the positive behaviors, and unhappy couples the negative ones, shows that there's a correlation, but it doesn't necessarily mean that unhappiness causes couples to exchange more negative behaviors, or vice-versa.