Scientific Investigation + CER

35 essential vocabulary flashcards covering key concepts of scientific investigation, experimental variables, data analysis, and CER framework.

Scientific method order

Observation -> Question -> Hypothesis -> Experiment -> Data Collection -> Conclusion

Observation

Information gathered directly using your senses or scientific tools.

Inference

A logical explanation based on observations and prior knowledge.

Observation vs. inference

Observation = directly noticed/measured. Inference = explanation based on what was observed.

Testable question

A question that can be answered by collecting measurable or observable data.

Hypothesis

A testable, falsifiable prediction about what will happen in an investigation.

Hypothesis format

If [IV changes], then [DV will change], because [scientific reason].

Independent variable (IV)

The factor intentionally changed or manipulated by the researcher. Think: I change it.

Dependent variable (DV)

The measurable outcome or response. Think: Data I measure.

How does X affect Y?

Usually $X$ = independent variable and $Y$ = dependent variable.

Controlled variables / constants

Conditions kept the same across all groups or trials.

Why keep constants?

So changes in the DV are more likely caused by the IV, not another factor.

Control group

The baseline comparison group that does not receive the experimental treatment.

Experimental group

The group that receives the treatment or tested level of the IV.

Control group vs. constants

Control = comparison GROUP. Constants = CONDITIONS kept the same.

Why change only one IV?

So you can tell which factor caused the change in the dependent variable.

Replication

Repeating trials or repeating the experiment to check whether results are consistent.

Why use a larger sample size?

It reduces the effect of unusual individuals and usually makes results more reliable.

Random sampling

Selecting subjects by chance so eligible members have a fair chance of being chosen.

Why use random sampling?

It reduces selection bias and helps the sample better represent the population.

Bias

A systematic influence that unfairly affects data collection, analysis, or conclusions.

Qualitative data

Descriptive, non-numerical observations such as color, texture, odor, or behavior.

Quantitative data

Numerical measurements or counts such as mass, time, temperature, length, or number.

Qualitative vs. quantitative

Qualitative = qualities/descriptions. Quantitative = quantities/numbers.

Reading a data table

Check the title, row/column labels, units, exact values, and overall patterns.

Graph x-axis

Usually shows the independent variable.

Graph y-axis

Usually shows the dependent variable.

Increasing vs. decreasing trend

Increasing: $Y$ rises as $X$ rises. Decreasing: $Y$ falls as $X$ rises.

Outlier

A data point noticeably different from the overall pattern; investigate before removing it.

Source of error

Something that can make results less accurate or reliable, such as human or equipment error.

CER

Claim-Evidence-Reasoning: a structure used to explain scientific results.

Claim

A clear, concise statement that answers the investigation question.

Evidence

Specific measurements, observations, or graph/table data that support the claim.

Reasoning

Explains how and why the evidence supports the claim using scientific principles.

Evidence vs. reasoning

Evidence = what the data show. Reasoning = why those data support the claim.