Scientific Investigation (ACT Science)

The Scientific Method

The scientific method is a systematic approach to understanding the natural world:

1. Observation → Notice something interesting
2. Question → Ask what causes it
3. Hypothesis → Propose testable explanation
4. Prediction → State what should happen if hypothesis is true
5. Experiment → Test the prediction
6. Analysis → Examine the data
7. Conclusion → Support or reject hypothesis

Types of Scientific Investigations

1. Controlled Experiments

Purpose: Test cause-and-effect relationships

Key features:

• Independent variable: What you change
• Dependent variable: What you measure
• Control variables: What you keep constant
• Control group: Baseline comparison

Example: Testing if fertilizer increases plant growth

• Independent: Amount of fertilizer
• Dependent: Plant height
• Controls: Water, sunlight, soil type, plant species
• Control group: Plants with no fertilizer

2. Observational Studies

Purpose: Observe without manipulating

Characteristics:

• No variables are changed
• Natural conditions
• Look for patterns/correlations
• Cannot prove causation

Example: Observing bird migration patterns

• Record when birds arrive/depart
• Note weather conditions
• Track population changes

3. Comparative Investigations

Purpose: Compare two or more groups

Example: Comparing reaction rates at different temperatures

• Test at 20°C, 30°C, 40°C, 50°C
• Measure time for reaction completion
• Look for relationship between temperature and rate

Variables in Investigations

Types of Variables

Independent Variable (IV):

• What experimenter changes/controls
• Goes on x-axis of graph
• "Cause" in cause-effect

Dependent Variable (DV):

• What's measured/observed
• Responds to changes in IV
• Goes on y-axis of graph
• "Effect" in cause-effect

Control Variables:

• Kept constant
• Prevents confounding effects
• Ensures fair test

Example Investigation:

"Students tested how light intensity affects photosynthesis rate. They placed plants under lights of different brightness and measured oxygen production."

• IV: Light intensity (what they changed)
• DV: Oxygen production (what they measured)
• Controls: Plant type, temperature, CO₂ levels, water, time

ACT Tip: Identifying Variables

Question pattern: "What was the independent variable in Experiment 2?"

Strategy:

1. Find Experiment 2 description
2. Look for "Students changed..." or "tested at different..."
3. That's your independent variable

Experimental Design Elements

Controls

Why control?

• Isolates effect of independent variable
• Eliminates alternative explanations
• Makes results valid

Types:

• Control group: Receives no treatment (baseline)
• Control variables: Factors kept constant

Example: Testing new medicine:

• Control group: Gets placebo
• Experimental group: Gets medicine
• Control variables: Age, dosage timing, diet

Sample Size

Larger samples = Better reliability

Why?

• Reduces impact of outliers
• Increases statistical significance
• Makes patterns clearer

ACT questions might ask: "How could this experiment be improved?"

Good answer: "Test more subjects" or "Increase number of trials"

Precision and Accuracy

Precision: How close measurements are to each other

• Consistent results
• Small variation

Accuracy: How close measurements are to true value

• Correct results
• Measures what you intend

Improving precision:

• Use better instruments
• Take multiple measurements
• Control environment

Replication

Why replicate?

• Verify results aren't flukes
• Increase confidence in findings
• Identify errors

Two types:

1. Repeated trials: Same researcher, same conditions
2. Independent replication: Different researchers test same hypothesis

Data Collection and Analysis

Data Types

Quantitative: Numbers, measurements

• Example: Temperature = 25°C, Mass = 150g

Qualitative: Descriptions, observations

• Example: Color changed to blue, texture became rough

ACT favors quantitative data — easier to graph and analyze

Organizing Data

Tables:

• Rows and columns
• IV typically in left column
• DV in right column(s)
• Include units!

Graphs:

• IV on x-axis
• DV on y-axis
• Title and axis labels essential
• Show trends clearly

Identifying Patterns

Look for:

Positive correlation: Both variables increase together
Negative correlation: One increases as other decreases
No correlation: No clear relationship
Linear trend: Straight line relationship
Non-linear trend: Curved relationship

Drawing Conclusions

Valid Conclusions

Must be: ✓ Based on data
✓ Specific to conditions tested
✓ Acknowledge limitations
✓ Distinguish correlation from causation

Example of good conclusion: "In this experiment, increasing temperature from 20°C to 50°C decreased reaction time from 60 seconds to 15 seconds."

Poor conclusion: "Temperature always makes reactions faster." (Too general, ignores possible limits)

Limitations

Every investigation has limitations:

Sample size — Might be too small
Duration — Might be too short
Range — Might not test all conditions
Controls — Might miss confounding variables
Measurement error — Instruments have limits

ACT questions: "What is a limitation of this study?"

Strategy: Look for what wasn't controlled, what wasn't tested, or what could affect results

Common ACT Question Types

Type 1: Identify Variables

"In Experiment 1, the independent variable was:"

Strategy:

• Find Experiment 1
• Look for what was changed
• That's the IV

Type 2: Improve Design

"Which change would improve this experiment?"

Common good answers:

• Increase sample size
• Add more trials
• Include control group
• Control additional variable
• Use more precise measuring tool

Type 3: Support/Contradict Hypothesis

"Which result supports Hypothesis A?"

Strategy:

• Understand what Hypothesis A predicts
• Find data that matches that prediction
• Check graphs/tables for confirming evidence

Type 4: Additional Investigation

"To further test this hypothesis, students should:"

Strategy:

• Think about what wasn't tested yet
• Look for logical next step
• Must be testable and related

Common Investigation Flaws (ACT Favorites!)

Flaw 1: No control group

• Can't tell if change was due to treatment

Flaw 2: Multiple variables changed

• Can't tell which variable caused effect

Flaw 3: Too few trials

• Results might not be reliable

Flaw 4: Bias in sample selection

• Results might not be representative

Flaw 5: Improper measurement

• Wrong tool or technique

ACT loves asking: "What is wrong with this experimental design?"

Experimental Ethics (Sometimes Tested!)

Key principles:

Informed consent: Participants know what they're agreeing to
Minimize harm: Don't cause unnecessary suffering
Confidentiality: Protect participant privacy
Honesty: Report results truthfully

Animal research: Minimize pain, use only when necessary

Quick Tips for ACT Science

✓ Read the introduction carefully — tells you what's being investigated
✓ Circle variables — mark IV, DV, and controls
✓ Check sample size — larger is usually better
✓ Look for controls — proper experiments need them
✓ Note units — °C vs °F, cm vs m matters!
✓ Follow the data — don't use outside knowledge
✓ Check axes — make sure you know what graph shows
✓ Process of elimination — often 2-3 choices are clearly wrong

Practice Approach

For investigation passages:

1. Skim for structure — How many experiments? What's the overall question?
2. Read intro — What's the research question?
3. Identify variables — For each experiment, note IV, DV, controls
4. Check graphs/tables — What do they show?
5. Go to questions — Often easier than reading whole passage first
6. Find relevant info — Locate specific experiment or data
7. Answer from passage — Don't overthink!

Remember: ACT Science mostly tests whether you can read and understand scientific information, not whether you've memorized biology or chemistry facts. Focus on understanding the investigation design and what the data shows!