Fill in the blanks to complete the passage about cases in which the independent variable doesn't make much difference in an experiment. If a researcher determines that the independent variable makes no significant difference in the dependent variable, they are concluding a(n) - . This could either be the truth (the variables really are not related) or be due to design flaws in the experiment. There are several design flaws that may produce such a result. A(n) - can occur when the change in the independent variable is not strong enough to affect the dependent variable. Or the dependent variable might not be responsive enough to detect change from the independent variable; in other words, it could be a(n) - . Additionally, scores from the dependent variable can spontaneously cluster near the top of possible scores, known as the - , or near the bottom of possible scores, known as the - these phenomena can make covariance undetectable. ceiling effectfloor effectinsensitive measureinstrumentation threatnull effectdemand characteristicsweak manipulationplacebo effect