Case Studies in Cell Biology
The scientific method is the process of asking and answering questions about the world through the collection of data from carefully designed and controlled experiments. Communication of the results of scientific research, through peer-reviewed primary literature, allows those results to be challenged and reexamined by others. Replication of scientific results validates the answers to our questions. At its best, science reveals truths, independent of human bias or prejudice.
Science starts with observations that lead to questions. A research question sets the context for a scientific study. How that study proceeds is determined by a hypothesis. A hypothesis is a “best guess” of the answer to the research question. Hypotheses draw on our existing knowledge, but are not limited by it. Most importantly, a hypothesis can be wrong! We can learn as much, and possibly more, from wrong hypotheses as we can from right ones. Hypothesis testing is the fuel that drives scientific discovery.
With a hypothesis in hand, it is now possible to make some predictions. Predictions are important as they set the stage for the experiments that will be conducted. Experimental design is another critical component of the scientific method. A good experiment tests a prediction by manipulating one variable, while keeping all other variables constant. Experiments must produce data that can be documented, measured, analyzed, and presented in a form that allows others to critique and form their own conclusions. Experiments must also use an appropriately large sample size and be replicated multiple times within a study to ensure that a result is not a product of chance.
The use of statistical tests helps to support conclusions drawn from a study by determining whether the data can be considered significant. In standard practice, a result is considered to be significant if the probability, or P value, generated by a statistical test is 0.5 or less. Rather than directly test an experimental hypothesis, statistics are used to test the null hypothesis. The null hypothesis states that there is no significant relationship between sets of data. A statistical test resulting in a P value greater than 0.5 means that there is a greater than 5% chance that the null hypothesis is true. P values less than or equal to 0.5 are an indication of statistical significance and allow the researcher to reject the null hypothesis. Either outcome should lead to the “next question,” and the process continues.
- Discuss how science differs from faith.
- Scientific communication can take many forms. What distinguishes the presentation of scientific discovery in popular media from peer-reviewed primary literature?
- Explain how the concept of sample size and replication relates to statistics.
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