Experimental Design and Data Analysis

Mr. Stratton discusses experimental design in AP Biology, focusing on scientific questioning, hypothesis formulation, and the importance of testable questions. He explains the roles of independent and dependent variables, the need to control confounding variables, and the significance of using control groups. The video also covers data collection, analysis, and interpretation, emphasizing the use of statistical tools and graphical representation. Finally, students are tasked with designing an experiment on photosynthesis in aquatic plants.

What are the three essential outcomes in AP Biology's experimental design?

• Experimentation, peer review, and publication

• Hypothesis testing, data collection, and peer review

• Data analysis, publication, and scientific questioning

• Scientific questioning, data collection, and data analysis

Which of the following is a testable scientific question?

• Is chocolate better than vanilla?

• Does UV radiation increase melanoma in rats?

• Is UV radiation harmful?

• What is the best ice cream flavor?

What is the purpose of an alternative hypothesis?

• To summarize the experiment's results

• To provide a backup plan for the experiment

• To propose a potential outcome of an experiment

• To state that there is no effect

What is the independent variable in an experiment?

• The variable that is dependent on others

• The variable that remains constant

• The variable that is manipulated

• The variable that is measured

Why is it important to control confounding variables?

• To increase the number of variables in the study

• To make the experiment more complex

• To prevent them from affecting the dependent variable

• To ensure the experiment is ethical

What is the role of a control group in an experiment?

• To increase the sample size

• To serve as a baseline for comparison

• To receive the independent variable

• To ensure all variables are tested

Why is a large sample size important in experiments?

• To ensure the results are statistically significant

• To make data analysis easier

• To reduce the number of confounding variables

• To increase the complexity of the experiment

What type of data is preferred for better analysis in experiments?

• Descriptive data

• Subjective data

• Quantitative data

• Qualitative data

What do error bars in a graph represent?

• The standard deviation of the data

• The confidence in the data

• The range of the data

• The mean value of the data

What should a scientist say if their hypothesis is not supported by the data?

• The hypothesis is incorrect

• The null hypothesis is proven

• The hypothesis is not supported

• The experiment was a failure