Data Analysis and Experimentation Quiz

What is the difference between quantitative and qualitative data?

• Quantitative data is numerical, while qualitative data is descriptive.

• Quantitative data is descriptive, while qualitative data is numerical.

• Both are numerical data types.

• Both are descriptive data types.

Which of the following is NOT a necessary part of a well-constructed graph?

• Title

• Axis labels

• Gridlines

• Legend

Why is it essential to include axis scales in a graph?

• To make the graph colorful

• To clearly understand and compare data points

• To add more data points

• To make the graph look complex

What is the purpose of a control group in an experiment?

• To provide a standard for comparison

• To increase the sample size

• To manipulate variables

• To ensure the experiment is biased

Difference between independent & dependent variable

• The dependent variable is manipulated, while the independent variable is measured.
• Both variables are measured simultaneously without manipulation.
• The independent variable is always constant, while the dependent variable varies.
• Dependent variable is variable measured in an experiment and Independent variable is variable being manipulated

Examples of independent and dependent variable

• Independent variable: study time; Dependent variable: test scores.
• Independent variable: diet; Dependent variable: exercise frequency.
• Independent variable: temperature; Dependent variable: rainfall.
• Independent variable: age; Dependent variable: height.

You measure mass & volume of three liquids to determine density. What is the independent variable in the experiment?

• Temperature of the liquid
• Type of liquid
• Volume of the liquid
• Mass of the liquid

What does it mean to interpolate data from a graph?

• To estimate values between known data points

• To find the maximum value

• To ignore outliers

• To extrapolate future data

What scenario best describes extrapolation?

• Estimating future data based on trends

• Finding average values

• Identifying peaks in data

• Ignoring data points

Why is it important to have a clear hypothesis before beginning an experiment?

• It guides the experiment and helps determine what to measure and observe

• It makes the experiment more expensive

• It ensures the experiment will be successful

• It allows for more variables to be tested