Science Skills Formative Assessment '25

The variable that is changed by the scientist.

A variable kept constant during an experiment.

The initial observation before any changes.

The variable that is measured in an experiment.

A balance scale for weight measurement.

A graduated cylinder is used for measuring liquids.

A thermometer for temperature measurement.

A ruler for length measurement.

To allow for more variables to be tested.

To make the experiment more complicated.

To speed up the experiment process.

To ensure the experiment is fair and results are valid.

A testable prediction about the experiment's outcome.

A type of graph used in data analysis.

An explanation of why the results occurred.

A summary of collected data from the experiment.

It is the variable that changes during the experiment.

It is the main factor that is being tested.

It measures the independent variable only.

It serves as a standard for comparison against experimental groups.

Counting the number of flowers in a garden.

Describing the color of a flower observed in an experiment.

Measuring the height of plants in centimeters.

Recording the temperature of the soil.

Different units can be mixed without issue.

Units can be added or ignored during analysis.

Only one unit is necessary for all data.

Units should be consistent and clearly labeled throughout.

It is decorative and not necessary for understanding.

It shows what each axis measures in the data set.

It can be ignored without confusion.

It repeats the data points for clarity.

To compare different categories or groups of data.

To show percentage distributions of a single variable.

To portray two related numerical variables.

To track changes over time continuously.

To create confusion about the experiment.

To make the report longer and more detailed.

To maintain accuracy and support reliable conclusions.

To impress others with complex language.

It is a final summary of results obtained.

It restricts creativity in design processes.

It guides the direction of the research and experimentation.

It avoids repetition in experiments conducted.

All variables were adequately controlled.

The hypothesis is likely to be valid based on evidence.

The result is guaranteed to be accurate.

The experiment was executed perfectly.

By distinguishing between qualitative and quantitative types.

By guessing what categories might fit.

By using random labels without structure.

Only by numerical values obtained during testing.

The average value calculated from a set of numbers.

The most frequently occurring number.

The highest value in a data set.

A summary of all data points listed.

Minimizing the effects of variables not being tested.

Creating new variables to test every time.

Maximizing environmental changes in each run.

Making sure results are always the same.

Drawing conclusions without testing.

Identifying the problem or question to be studied.

Making predictions before research is done.

Collecting data before forming a hypothesis.

It complicates the data presentation.

It helps organize data for clearer analysis and comparison.

It is unnecessary in basic experiments.

It serves as decoration for reports.

Ignoring data entirely when reporting results.

By writing lengthy descriptions without visuals.

Using charts or graphs that clearly represent the findings.

Summarizing data in a table without explanation.

Examining data to identify patterns or trends.

Avoiding complex calculations when possible.

Printing data for documentation purposes only.

Reading data without making conclusions.