
Scientific Method and Experimental Error
Authored by Laura [Staff]
Science
9th Grade
Used 2+ times

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26 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are the steps of the scientific method?
Observation, theory, conclusion, analysis
Prediction, observation, conclusion, hypothesis
The steps of the scientific method are: observation, question, hypothesis, prediction, experiment, analysis, and conclusion.
Question, analysis, experiment, theory
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How can experimental errors be minimized in an experiment?
Conducting the experiment in a noisy environment, not using proper controls, and not repeating the experiment
Ignoring safety protocols, using imprecise measurement tools, and not recording the data accurately
Guessing the results, using outdated equipment, and not following the experimental procedure
Using proper controls, repeating the experiment multiple times, and using precise measurement tools
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is a control group important in an experiment?
To provide a baseline for comparison
To make the experiment more complicated
To waste time and resources
To confuse the results
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How do you interpret experimental data to draw conclusions?
Analyze the results and compare with previous knowledge or theories
Ignore the data
Guess randomly
Ask someone else to interpret the data
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Explain the process of forming a hypothesis in the scientific method.
Flipping a coin to make a decision
Making an educated guess or prediction based on observations and research.
Consulting a psychic for guidance
Choosing the answer that sounds the most interesting
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are some examples of systematic errors in experiments?
Human error
Random errors
Perfect experimental conditions
Flaws in the experimental design, equipment, or procedures
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it important to only change one variable at a time in an experiment?
To understand the specific impact of each variable on the experiment's outcome.
To confuse the results
To save time and resources
To make the experiment more complicated
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