Graph and scientific method

The information you collect while doing your experiment is called

• conclusions

• data

• hypotheses

• procedures

The variable that is being measured or observed is called the _______________. Hint: this is the variable that is the result or effect

• independent variable

• dependent variable

• control variable

What is being changed in this experiment?

• ramp height
• the speed that the ball rolls
• type of ball

What is the Responding (Dependent) Variable in this graph?

• Plant Growth
• Growth (cm)
• Hours
• 15

Tags

NGSS.MS-LS1-5

NGSS.MS-LS2-1

How many independent variables should you have in an experiment?

• two

• as many as possible

• four

• one

Tags

NGSS.MS-PS2-2

What are the three types of variables in an experiment?

• manipulated variables, responding variables, and controlled variables

• experimental variables, observational variables, and controlled variables

• independent variables, dependent variables, and controlled variables

• independent variables, dependent variables, and manipulated variables

Answer explanation

In an experiment, there are three types of variables: independent, dependent, and controlled variables. The independent variable is the one being manipulated, the dependent variable is the one being measured, and controlled variables are kept constant to ensure a fair test. This corresponds to the correct choice: independent variables, dependent variables, and controlled variables.

Tags

NGSS.MS-PS2-2

Why is it important to have a control group in a controlled experiment?

• To provide a baseline for comparison

• To increase the sample size

• To save time and resources

• To confuse the results

Answer explanation

A control group is crucial in a controlled experiment because it serves as a baseline for comparison. By comparing the results of the experimental group with the control group, researchers can determine the effect of the variable being tested and draw more accurate conclusions.

What is the difference between qualitative and quantitative data?

• Qualitative data is numerical and objective, while quantitative data is descriptive and subjective.

• Qualitative data is based on opinions and feelings, while quantitative data is based on facts and figures.

• Qualitative data is descriptive and subjective, while quantitative data is numerical and objective.

• Qualitative data is collected through surveys and questionnaires, while quantitative data is collected through observations and experiments.

Answer explanation

The difference between qualitative and quantitative data lies in their nature. Qualitative data is descriptive and subjective, focusing on characteristics and qualities that cannot be easily measured or counted. On the other hand, quantitative data is numerical and objective, dealing with measurable quantities and statistics. The correct choice highlights this distinction between the two types of data.

What is the difference between an observation and an inference?

• Observation is a conclusion made based on evidence, while inference is a direct result of using one or more of the five senses to gather information.

• Observation is a direct result of using one or more of the five senses to gather information, while inference is a conclusion or interpretation made based on observations or evidence.

• Observation and inference are the same thing.

• Observation is a prediction made based on evidence, while inference is a direct result of using one or more of the five senses to gather information.

Answer explanation

The difference between an observation and an inference lies in the process of gathering information and drawing conclusions. Observation involves using one or more of the five senses to collect data, while inference is the act of interpreting or making conclusions based on the observed data or evidence. The correct choice highlights this distinction between the two terms.

What are some common sources of error in scientific experiments?

• insufficient sample size, biased sampling, confounding variables

• measurement errors, human error, equipment malfunction, sampling errors, and systematic errors

• lack of control group, lack of randomization, lack of replication

• incorrect measurements, incorrect calculations, incorrect data analysis

Answer explanation

The correct choice highlights various sources of error in scientific experiments, including measurement errors, human error, equipment malfunction, sampling errors, and systematic errors. These factors can significantly impact the accuracy and reliability of experimental results, making it essential for researchers to account for and minimize these errors in their studies.