GED Science • Science Practices

Evaluate Conclusions Against Evidence

Learn to judge whether scientific conclusions are truly supported by the data presented.

A multi-subject study notebook with math and science symbols for GED preparation
Inside this lesson 10 sections 5 questions 5 figures

SECTION 1

Why Evaluating Evidence Matters

Throughout history, people have made bold claims about the natural world. Some of those claims held up when tested; others crumbled under scrutiny. The ability to evaluate conclusions against evidence is the single most important skill in science — and it is heavily tested on the GED Science exam. Nearly every question on the test asks you to read a passage, look at data, and decide whether a conclusion makes sense. This skill did not appear overnight; it developed over centuries of scientific progress.

~350 BCE • Aristotle's Observations

Aristotle argued that heavier objects fall faster than lighter ones. This conclusion seemed logical, but he never tested it with controlled experiments — an early example of an unsupported claim.

1589 • Galileo Challenges Aristotle

Galileo reportedly dropped objects of different masses from the Leaning Tower of Pisa. His evidence showed they hit the ground at nearly the same time, disproving Aristotle's long-held conclusion.

1847 • Semmelweis and Handwashing

Dr. Ignaz Semmelweis used hospital mortality data to conclude that handwashing reduced deadly infections. His evidence was strong, yet many doctors rejected his conclusion because it conflicted with their beliefs.

1953 • Watson & Crick's DNA Model

Watson and Crick proposed the double-helix structure of DNA. Their conclusion was supported by X-ray diffraction data from Rosalind Franklin and chemical evidence from Erwin Chargaff — a powerful example of evidence-based reasoning.

2025 • GED Science Exam Today

The modern GED Science test asks you to do exactly what these scientists did: look at evidence and decide whether a conclusion is supported, partially supported, or contradicted by the data.

The central question this lesson addresses is straightforward: Does the evidence actually support the conclusion being made? On the GED, you will be given passages, graphs, tables, and diagrams along with one or more conclusions. Your job is to determine whether the data backs up those conclusions — or whether the conclusion goes beyond what the evidence shows.

SECTION 2

Core Principles of Evidence Evaluation

Evaluating a conclusion against evidence is a structured process, not a guessing game. There are clear principles you can follow every time you encounter a scientific claim on the GED. These principles apply whether you are reading about biology, chemistry, physics, or earth science.

1

Identify the Conclusion

Find the specific claim or statement being made. A conclusion is a judgment or interpretation — not a raw fact. Look for phrases like "therefore," "this shows that," "the researcher concluded," or "the data suggest."
2

Identify the Evidence

Locate the data, observations, or experimental results that are presented. Evidence includes numbers in tables, trends in graphs, measurements, and described observations. Separate facts from interpretations.
3

Check the Match

Ask: Does the evidence directly support the conclusion? Does it contradict it? Or is the conclusion broader than what the evidence can prove? A valid conclusion stays within the boundaries of the data.
4

Watch for Overreach

A common trap on the GED is a conclusion that sounds reasonable but goes beyond what the evidence actually shows. If a study tested adults, you cannot conclude the same result applies to children without additional data.
5

Consider Alternative Explanations

Could there be another explanation for the data? If so, the conclusion may be just one possibility. Strong conclusions rule out alternatives; weak conclusions ignore them.
✦

KEY TAKEAWAY

Think of a conclusion as a bridge and the evidence as the supports holding it up. If the supports are strong and placed in the right spots, the bridge holds. If the supports are missing, too few, or in the wrong place, the bridge collapses. Your job on the GED is to look under the bridge and check the supports before you trust it.

SECTION 3

Visualizing the Evidence-Conclusion Relationship

The diagram below shows the decision-making process you should follow every time you encounter a conclusion on the GED Science test. Start at the top by identifying the conclusion, then work through each checkpoint. This flowchart is your mental roadmap for evidence evaluation.

Evidence Evaluation Flowchart1. Identify the Conclusion2. Locate the Evidence (Data)3. Does evidencematch conclusion?NOYESSupportedNotSupportedPARTIAL4. Does conclusionoverreach the data?NOYESOvergener-alizedPartiallySupported5. Always consider: Are there alternative explanations for the data?
This flowchart shows the five-step process for evaluating whether a conclusion is supported, partially supported, overgeneralized, or not supported by the evidence. On the GED, you mentally walk through these steps for each question.

Notice that the flowchart has multiple possible outcomes. On the GED, you will not always be looking for a conclusion that is perfectly supported. Sometimes a question asks you to identify which conclusion is best supported, and the correct answer might only be partially supported — while the other choices are contradicted entirely. Learning to rank the strength of evidence-conclusion matches is key to getting these questions right.

SECTION 4

How Evidence Evaluation Works in Practice

Types of Evidence on the GED

The GED Science exam presents evidence in several forms, and you need to be comfortable with all of them. Quantitative evidence includes numbers, measurements, and data in tables or graphs. Qualitative evidence includes descriptions, observations, and characteristics that don't involve numbers. A passage might describe what happened during an experiment, while a data table shows the measured results. Both types count as evidence, and you need to consider both when evaluating a conclusion.

The Logic of Support

When you evaluate a conclusion, you are checking a logical relationship. Think of it this way: if the conclusion says "X causes Y," then the evidence should show that when X is present, Y happens, and ideally that when X is absent, Y does not happen. If the evidence only shows that X and Y occurred at the same time, the conclusion of causation is too strong — it should say "X is associated with Y" instead. This distinction between correlation (two things happening together) and causation (one thing directly causing another) is one of the most commonly tested concepts on the GED.

Signal Words That Indicate Conclusions

  • Therefore — signals that a conclusion follows from the preceding evidence.
  • This suggests / This indicates — signals an interpretation of data, not a raw fact.
  • The results show that — introduces what the researcher believes the data mean.
  • Based on the data / Based on the evidence — directly links a claim to data, making it easy to check.
  • It can be concluded that — a formal conclusion statement often found in GED answer choices.
💡

GED Tip

When you see a question asking "Which conclusion is best supported by the data?" — go back to the passage or graph and match each answer choice directly to specific evidence. The correct answer will be the one you can point to in the data. If you cannot find evidence for a choice, eliminate it.

SECTION 5

Common Reasoning Errors to Watch For

The GED test designers create wrong answer choices based on common mistakes people make when evaluating evidence. If you learn to recognize these errors, you will be able to eliminate incorrect answers quickly and confidently. The diagram below illustrates the most frequent reasoning errors and how to spot them.

Common Evidence-Conclusion ErrorsOVERGENERALIZATIONEvidence: Drug X helped50 adult patients.Flawed conclusion:"Drug X helps everyone,including children."⚠ Goes beyond the sampleCORRELATION ≠ CAUSEEvidence: Ice cream salesand drownings both risein summer.Flawed conclusion:"Ice cream causes drowning."⚠ Confounding variable: heatCHERRY-PICKINGEvidence: 8 of 10 trialsshow no effect; 2 showa small effect.Flawed conclusion:"The treatment is effective"(citing only 2 trials). REVERSED CAUSEEvidence: Hospitals havemany sick people.Flawed conclusion:"Hospitals make people sick."⚠ Cause and effect reversedINSUFFICIENT DATAEvidence: One studentscored higher aftertutoring.Flawed conclusion:"Tutoring always raises scores."⚠ Sample size = 1
Five common reasoning errors shown with examples. On the GED, wrong answer choices often reflect these exact patterns: overgeneralization, confusing correlation with causation, cherry-picking data, reversing cause and effect, and drawing conclusions from insufficient data.

When you read a GED question, ask yourself: "Is this conclusion making any of these five mistakes?" If so, it is probably a wrong answer. The correct answer will be the one that sticks closely to what the data actually show, without jumping to broader claims, confusing cause and effect, or ignoring parts of the data.

SECTION 6

Worked Example: Evaluating a Conclusion from Data

Let's walk through a GED-style example step by step. Read the passage and data table below, then follow how we evaluate the conclusion.

ℹ

Stimulus Passage

A researcher wanted to test whether a new fertilizer increases tomato plant growth. She set up two groups: Group A received the new fertilizer, and Group B received no fertilizer (control). Each group had 20 plants. After 6 weeks, she measured the average height of plants in each group. The researcher concluded: "The new fertilizer significantly increases tomato plant growth compared to unfertilized plants."
GroupTreatmentNumber of PlantsAvg. Height at Week 6 (cm)
ANew fertilizer2034.2
B (Control)No fertilizer2028.7

Plant growth data after 6 weeks

Evaluating the Researcher's Conclusion

  1. 1

    Step 1 — Identify the Conclusion

    The researcher's conclusion is: "The new fertilizer significantly increases tomato plant growth compared to unfertilized plants." This is a causal claim — she is saying the fertilizer caused the increased growth.
    Conclusion identified: Fertilizer causes increased growth.
  2. 2

    Step 2 — Identify the Evidence

    The evidence comes from the data table. Group A (fertilizer) had an average height of 34.2 cm. Group B (no fertilizer) had an average height of 28.7 cm. The difference is 34.2 − 28.7 = 5.5 cm. The experiment used 20 plants per group, and there was a control group.
    Evidence: 5.5 cm difference between fertilized and unfertilized groups.
  3. 3

    Step 3 — Check the Match

    Does the evidence support the conclusion? The data do show that the fertilized plants grew taller on average. The experiment included a control group, which strengthens the comparison. The sample size of 20 per group is reasonable. The evidence is consistent with the conclusion that the fertilizer helped the plants grow.
    The data do support a difference in growth between the two groups.
  4. 4

    Step 4 — Check for Overreach

    The researcher used the word "significantly." In everyday language, 5.5 cm might seem meaningful. But in science, "significantly" has a specific statistical meaning. The passage does not mention any statistical test. Also, we don't know if other variables were controlled — were all plants in the same soil, same sunlight, same water? Without this information, we should be cautious about saying the fertilizer definitively caused the difference.
    The word "significantly" may overreach — no statistical test is mentioned.
  5. 5

    Step 5 — Consider Alternatives

    Could something else explain the difference? If Group A happened to get more sunlight or better soil, that could account for the taller plants. Without knowing that other variables were controlled, the conclusion is partially supported but not fully confirmed.
    Final verdict: The conclusion is partially supported. The data show a difference, but the claim of causation would require ruling out other variables.

On the actual GED exam, you would not need to write all of this out for a multiple-choice question — but you would need to think through it quickly. For a short-answer question, you would write 3–7 sentences explaining your reasoning in a similar way, pointing to specific data and identifying any gaps.

SECTION 7

Strong vs. Weak Evidence: Knowing the Difference

Not all evidence is created equal. On the GED, you may need to judge whether the evidence presented is strong enough to support a particular conclusion. The table below compares characteristics of strong evidence with characteristics of weak evidence.

FeatureStrong EvidenceWeak Evidence
Sample sizeLarge number of subjects or data pointsVery small sample (e.g., 3–5 subjects)
Control groupProper control group used for comparisonNo control group; nothing to compare against
Variable controlOther variables held constantMultiple variables changed at once
ReproducibilityResults repeated across multiple trialsOnly one trial conducted
Data presentationComplete data shown (all results included)Selective data shown (cherry-picked results)
Conclusion scopeConclusion limited to what was testedConclusion extends to groups or conditions not tested

Comparing strong and weak evidence characteristics

✦

KEY TAKEAWAY

Think of evidence like the foundation of a house. A house built on a wide, deep concrete foundation can support a large structure. A house built on a thin patch of sand can only support a small shed — if that. When a conclusion is a "big house" (a broad claim), it needs a "wide foundation" (lots of strong evidence). When the foundation is small (limited data), only a small, careful conclusion is safe.

SECTION 8

Connecting to Other GED Science Skills

Evaluating conclusions against evidence does not exist in isolation. It connects to every other science practice tested on the GED. The table below shows how this skill relates to the other major science practices you need to master.

Related Science PracticeHow It Connects to Evaluating Conclusions
Comprehending scientific presentationsYou must understand what a passage, graph, or table is saying before you can judge whether a conclusion follows from it. Reading comprehension is the first step.
Evaluating experimental designIf an experiment has no control group or doesn't control variables, the evidence it produces is weaker. Design flaws weaken any conclusion.
Reasoning from dataYou need to read data correctly — trends, values, patterns — before you can match data to a conclusion. Misreading a graph leads to choosing the wrong answer.
Working with scientific theoriesSometimes a conclusion is tested against an established theory. If a conclusion contradicts a well-established theory, you need very strong evidence to support it.
Applying probability and statisticsSample size, variability, and statistical significance all affect how confidently you can support a conclusion. A small sample means lower confidence.

How evaluating conclusions connects to other GED science practices

On the actual GED, you will sometimes see questions that combine multiple science practices in a single item. For example, a question might ask you to evaluate a conclusion (this lesson's skill) while also requiring you to interpret a graph (reasoning from data) and consider whether the experiment was well-designed (evaluating experimental design). Building strength in this core skill will help you across the entire test.

SECTION 9

Practice Problems

Question 1: CONCEPTUAL

A study observed that students who eat breakfast score higher on morning tests than students who skip breakfast. The researcher concluded: "Eating breakfast causes higher test scores." Which of the following best describes the flaw in this conclusion?
  • A. The sample size was too small to draw any conclusion.
  • B. The study shows a correlation, but that does not prove breakfast caused the higher scores.
  • C. The conclusion is too narrow; breakfast likely helps with all academic subjects.
  • D. The researcher should have tested afternoon scores instead of morning scores.
Show answer (B)
B is correct. The study only observed that breakfast-eaters scored higher — it did not control for other variables like sleep, study time, or overall health. This is a classic case of confusing correlation with causation. A is incorrect because the passage does not mention sample size as a problem. C is incorrect because it actually makes the overreach worse, not better. D is incorrect because the time of testing is not the flaw — the flaw is assuming causation from an observational study.

Question 2: BASIC CALCULATION

A scientist tested two types of insulation by placing each in a box with a heat source and measuring temperature after 30 minutes. • Insulation A: final temperature 42°C • Insulation B: final temperature 38°C • No insulation (control): final temperature 55°C The scientist concluded: "Insulation B is the better insulator because it kept the temperature lower." Which statement best evaluates this conclusion?
  • A. The conclusion is not supported because neither insulation made a difference.
  • B. The conclusion is supported because 38°C is lower than 42°C, and both are lower than the control.
  • C. The conclusion is not supported because Insulation A had the highest temperature of the two.
  • D. The conclusion is overgeneralized because the test was only 30 minutes long.
Show answer (B)
B is correct. The data show that Insulation B (38°C) kept the box cooler than Insulation A (42°C), and both performed better than no insulation (55°C). The conclusion directly matches the data. A is incorrect because both insulations clearly reduced the temperature compared to the control. C restates the evidence but frames it as a problem — when actually, the lower temperature for B supports the conclusion. D raises a possible limitation, but the conclusion only claims B is better within the conditions tested, which the data do support.

Question 3: INTERMEDIATE

A marine biologist studied fish populations in two lakes over 5 years. Lake 1 was near a factory, and Lake 2 was in a wilderness area. • Lake 1: Fish population declined from 5,000 to 2,100. • Lake 2: Fish population declined from 4,800 to 3,900. The biologist concluded: "Factory pollution caused the fish population decline in Lake 1." Which of the following most weakens this conclusion?
  • A. Both lakes experienced population declines, so the factory may not be the cause of the decline in Lake 1.
  • B. Lake 1 started with more fish, so a larger decline was expected.
  • C. The biologist should have studied birds instead of fish.
  • D. Five years is too short a time period to study fish populations.
Show answer (A)
A is correct. The fact that Lake 2 (the wilderness lake with no factory) also lost fish suggests that something other than factory pollution might be causing declines in both lakes — perhaps climate change, disease, or natural predation cycles. If the factory were the sole cause, you would expect Lake 2's population to stay stable. B is incorrect because the starting populations were nearly equal (5,000 vs. 4,800), so the difference in decline cannot be explained by starting size. C is irrelevant to the conclusion being tested. D is not well-supported — five years is a reasonable timeframe for observing population trends.

Question 4: APPLIED

2 pts
Read the following scenario and data: A nutritionist studied whether drinking green tea helps adults lose weight. She recruited 200 adults aged 25–50 and randomly assigned them to two groups: • Group 1 (100 people): Drank 3 cups of green tea daily for 12 weeks. • Group 2 (100 people): Drank 3 cups of water daily for 12 weeks. Both groups were asked not to change their diet or exercise habits. Results: • Group 1 average weight loss: 2.3 kg • Group 2 average weight loss: 0.8 kg The nutritionist concluded: "Drinking green tea helps adults lose weight." In 3–7 sentences, evaluate whether this conclusion is supported by the evidence. Identify specific strengths and any limitations of the evidence.
Show answer
Rubric (2 points): Point 1 (Evidence supports the conclusion): The response identifies that the green tea group lost more weight (2.3 kg vs. 0.8 kg), and the study had strengths including a control group, random assignment, a reasonable sample size (200 total), and a specific time frame (12 weeks). Point 2 (Identifies a limitation or nuance): The response identifies at least one valid limitation, such as: participants may not have reported diet/exercise changes accurately (self-reporting bias); the study only tested adults aged 25–50, so results may not apply to other age groups; or the difference (1.5 kg) may or may not be statistically significant. A strong response notes that the conclusion is largely supported but acknowledges at least one limitation. Sample response: The conclusion is mostly supported by the data. The green tea group lost 2.3 kg compared to 0.8 kg in the water group, a difference of 1.5 kg. The study was well-designed with random assignment, a control group, and 100 people in each group. However, one limitation is that participants were only asked not to change their habits — there was no way to verify they actually complied. Also, the conclusion only applies to adults aged 25–50, since that is who was studied.

Question 5: CRITICAL THINKING

3 pts
A research team measured air pollution levels and asthma rates in 10 U.S. cities over a period of 3 years. Their data are summarized below: | City | Avg. Air Pollution Index | Asthma Rate (per 1,000 people) | |------|------------------------|---------------------------------| | A | 85 | 42 | | B | 72 | 38 | | C | 91 | 45 | | D | 60 | 31 | | E | 78 | 35 | | F | 95 | 48 | | G | 55 | 29 | | H | 68 | 44 | | I | 88 | 41 | | J | 50 | 25 | The team published two conclusions: Conclusion 1: "Higher air pollution levels cause higher asthma rates." Conclusion 2: "There is a positive correlation between air pollution levels and asthma rates." Using the data above, evaluate both conclusions. Which conclusion is better supported by the evidence, and why? Identify specific data points to support your analysis. Also identify at least one piece of information that would be needed to support the stronger conclusion.
Show answer
Rubric (3 points): Point 1 (Identifies the trend in the data): The response describes the overall positive correlation — as pollution index increases, asthma rate generally increases. It references specific data: City J (lowest pollution at 50, lowest asthma at 25) and City F (highest pollution at 95, highest asthma at 48). It may note that City H is an exception (moderate pollution of 68 but relatively high asthma rate of 44). Point 2 (Correctly evaluates both conclusions): The response explains that Conclusion 2 (correlation) is better supported because the data show two variables moving in the same direction across most cities, which establishes correlation. Conclusion 1 (causation) is not fully supported because correlation alone does not prove causation — there could be confounding variables (poverty, access to healthcare, smoking rates, indoor allergens). The response correctly distinguishes correlation from causation. Point 3 (Identifies what additional evidence would be needed): The response identifies at least one type of additional information that would help support the causation claim, such as: a controlled experiment isolating pollution exposure, data on confounding variables (income, healthcare access, smoking rates), longitudinal data tracking individuals who moved between cities, or results from cities that reduced pollution and subsequently saw lower asthma rates. Sample response: The data generally show that cities with higher air pollution indexes tend to have higher asthma rates. For example, City J has the lowest pollution (50) and the lowest asthma rate (25), while City F has the highest pollution (95) and the highest asthma rate (48). However, City H is an outlier — it has moderate pollution (68) but a relatively high asthma rate (44), suggesting other factors may be at play. Conclusion 2 (positive correlation) is better supported because the overall trend is clear. Conclusion 1 (causation) goes too far — this study only observed cities, it did not manipulate pollution levels experimentally. Other factors like poverty, smoking rates, or access to medical care could explain the pattern. To support the causal claim, researchers would need controlled data — such as tracking asthma rates before and after a city implemented pollution controls, while accounting for other variables.

SUMMARY

Lesson Summary

Summary

Evaluating conclusions against evidence is the cornerstone skill of the GED Science exam. You now know a clear process: identify the conclusion, locate the evidence, check whether they match, watch for overreach, and consider alternative explanations. Strong evidence features large samples, control groups, controlled variables, and reproducible results. Weak evidence suffers from small samples, missing controls, or selective reporting.

Watch out for the five common reasoning errors: overgeneralization, confusing correlation with causation, cherry-picking, reversed cause and effect, and insufficient data. These are the traps the GED uses in wrong answer choices. When you spot these errors, you can eliminate wrong answers with confidence. Remember: a supported conclusion stays within the boundaries of the data — it says what the evidence shows, and nothing more.

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