Data collected during an experiment and its repetitions are used to develop a conclusion. Data can either support the hypothesis or not support it. If your experimental results do not match your hypothesis, this does not necessarily mean your hypothesis is wrong. Perhaps you could redesign your experiment or find sources of error.

When asked to identify conclusions based on investigation descriptions, data tables, graphs, and drawings, remember to do the following:

• Look back at the hypothesis.
• Identify the independent and dependent variables.
• Look at the data carefully!!!
• Look for an overall trend in the data.
• Determine if the data support or reject the hypothesis.
• Write a statement that sums up the results and reflects on the hypothesis or if multiple choice.
• Determine if the data supports the statement and if the statement is relevant to the investigation.

* Please note, that a good conclusion does not usually contain the words - best, worst, always, never… these words do not reflect on a hypothesis and often connect to an opinion, and are not measurable. Conclusions should be based on the data collected during the investigation and should be opinion and inference free.

Let's try making a valid conclusion together.

Read the description of the investigation and then analyze the graph.

A student conducted a comparative investigation to see which fertilizer would have the greatest affect on the growth of a plant. She grew 10 plants of the same type in the same type and size of planter. She watered the plants the same amount, and each plant received the same amount of sunlight. She gave each plant the same amount of fertilizer, but she gave 5 of the plants fertilizer A and the other 5 plants fertilizer B. She measured the growth of the plants each week. Displayed in the graph below is the average growth of the plants each week.

Which conclusion below is best supported by the data?