Scientific method

Observe, Record, and Analyze Data

Observations Make clear and accurate observations An observation involves using all 5

senses Scientists use observations to gather

data that will support or disprove their hypothesis.

Two basic types of observations- Qualitative and Quantitative

Quantitative Observations Observations that involve a number in

the form of an amount or measurement. More precise and accurateExample: There are 12 students working in the

library. It takes 13 minutes for vinegar to

dissolve color on red M & M.

Qualitative Observations Observations that use non-numerical

descriptions. Using your five senses to make

observations.Example: Noticing your friends sweater is blue

and green. Students have reusable lunch bags

For homework, make 5 quantitative and 5 qualitative observations. Observe on bus or walk home, dinner time, activities, etc..Write them in your yellow packet on the back of page 10.

5 Quantitative Observations

5 Qualitative Observations

Inferences Good research goes beyond simple

observations. Scientists explain their observations

based on patterns and past experiences.

Inferences (con’t) When you explain or interpret things

you observe, you are making an inference.

Inferences are logical explanations based on what you already know.

There may be several logical explanations for an observation.

They may be changed as new information is obtained.

Observe, Record, analyze Data

Data- Facts, figures, and other evidence gathered through observations.

Scientific observations need to be recorded in an organized way so data can be analyzed.

Making sense of data is called data interpretation.

Data Table organizes data and makes it easier to read and compare.

Record - data table

The effect of different amounts of fertilizer on plant height.

Amount of fertilizer (ml) Height of plant (cm)

0 2

5 10

10 17

15 12.5

Observe, Record, Analyze Data

Final step in scientific method is to draw conclusions.

Conclusion is summary of what you have learned from an experiment.

Important to consider: did you have enough data? Does data support hypothesis or not? Were there any unexpected or unidentified variables that affected outcome?

Conclusions often lead to new scientific questions and experiments.