Which cup features seemed to matter most during your fair test?

• Type of material

• Color of the cup

• Shape of the cup

• Size of the cup

Why is it important to keep certain conditions the same in a fair test of cup features?

• To ensure accurate comparison

• To make it easier to record data

• To test different theories

• To use different types of cups

What patterns do we notice in the class data?

• Certain features consistently affect the temperature change of the cups.

• There are no clear patterns in any of the data.

How do you analyze your data after completing the test?

• Identify patterns in the data

• Guess the likely outcome

• Ignore data without clear patterns

• Only consider the highest and lowest temperatures

What can you conclude if your group’s test results are similar across different trials?

• The test is likely reliable.

• The test is too difficult.

• The test needs more variables.

• The test is irrelevant.

During data analysis, what might it indicate if no clear pattern is observed?

• There may be additional factors affecting the results.

• The data is perfect.

• The test was unnecessary.

• The temperature readings were incorrect.

Which cup features seemed to matter the most when discussing how to keep a drink cold?

• Insulation material

• Cup size

• Color of the cup

• Lid type

Which cup features are most important for keeping a drink cold?

• Insulation and material

• Color and size

• Handle and shape

• Design and patterns

Why is it important to use a control cup in your experiment?

• To compare the results against a standard version

• To have a cup to use in case the other one breaks

• To see how many cups are necessary

• To measure the volume of the liquid inside

What is one pattern you might look for in your data analysis?

• Which cup features are related to temperature change

• How many people participated

• The color of the cups used

• The number of notes taken