The Scientific Method
The absolute heart of science the Scientific Method. It can be described in different ways, but basically consists of…
- Hypothesis - Something predicted that will occur
- Experimentation - There must be both Control and Experimental groups with only thing different between the Control and Experimental groups. That "thing" is what's being tested.
- Observation - The experiment is observed without any bias or opinions.
- Analysis of Results - The observed results determine the outcome of the experiment and whether the hypothesis was correct or incorrect (true or false).
- Report Findings - The results are published/shared so that other researchers can replicate the experiment and either support or disagree with the findings.
Built into the scientific method are the following variables:
- independent variable (IV) - this is what the experimenter manipulates; this is the only thing different between the experimental and control groups
- dependent variable (DV) - this is what the IV supposedly influences; this is what is measured
- confounding variables - these are outside factors that might make the experiment go wrong
A student wants to measure the impact of sunlight on the growth of plants. She gets two equal pots, puts in potting soil from the same bag, plants the same type of corn seeds, waters the plants equally. She plans to measure the corn stalks height in inches over 2 months. But, she places a cardboard box over one pot to eliminate sunlight. In this example, the parts of the experiment would be:
- IV - Amount of sunlight - this is what she's manipulating, this is what's different between the control and experimental groups.
- DV - Growth of corn stalks in inches - this is what she's measuring.
- possible confounding variable - Perhaps the temperature in the box is different from the other pot. A different growth rate might then have been caused by the temperature difference and not the light difference. This confounds the results of the experiment.
Approaches to the 3 types of passages
The key here is to let the data speak for itself. Do not interpret what you think the data shows. First, nail down exactly what the question is asking. Secondly, refer to the data (chart or graph or table). Then ask yourself, "What is the data saying?" Don't ask what you think about the data, but what is the data actually saying?
The key here is to follow the statements given and the scientific method. Scientists must only state what the evidence supports. Do not go beyond what the evidence suggests. In this sense, this is the same as Data Representation types of questions.
The key here is, again, to follow the statements made by each scientists and to not "read into" what they're saying. Again, let the statements speak for themselves without inserting your own opinions into them.