Question

2. a) Why must all of the other known variables be kept constant during an experiment?

b) What is the first thing you should do if the data that you collected does not support your hypothesis?

Answer 1

Q.1

Ans. (A) It's important for a scientist to try to hold all variables constant except for the independent variable. If a control variable changes during an experiment, it may invalidate the correlation between the dependent and independent variable. When possible, control variables should be identified, measured and recorded. Although control variables may not be measured (although they are often recorded), they can have a significant effect on the awareness of control variables can lead to faulty results or what is called "confounding variables". Noting control variables makes it easier to reproduce an experiment.

(B) The solution is simple and clear, you reject the hypothesis. Hypothesis and theories depend on data and experiment. The data horse leads the theory cart, not the reverse. If the data consistently do not support the hypothesis, then clearly, the hypothesis is not a reasonable explanation of what you are investigating. The hypothesis is rejected and we search for a new hypothesis, a new interpretation that supports the experimental data.