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Subjects

Science

Nature and meaning of science

“Nature and Meaning of Science” introduces Class 9 students to science as a systematic way of exploring the natural world, rather than a collection of fixed facts. Within “Exploration: Entering the World of Secondary Science,” students examine how observation, questioning, evidence, measurement, reasoning, experimentation, and communication work together to build scientific knowledge. The topic also highlights curiosity, objectivity, creativity, responsible investigation, and how explanations change when new evidence emerges. It connects science with everyday experiences and prepares learners for inquiry-based study of later concepts.

Expert · Level 1 · 25 questions

TOPIC PRACTICE

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  1. Because a theory is only a guess
  2. Because new evidence may revise its scope or explanation
  3. Because all scientific theories are temporarily wrong
  4. Because theories are unrelated to experiments
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  1. More books definitely cause higher marks
  2. Books and marks are associated but causation is not established
  3. Marks cause students to buy books
  4. There is no relationship between them
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  1. The dependent variable is absent
  2. It cannot be determined which change caused the effect
  3. The control group is too strong
  4. No hypothesis can be formed
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  1. Its predictive power is weak
  2. It must be false
  3. It has become a scientific law
  4. It contains no observation
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  1. High accuracy and high precision
  2. High accuracy and low precision
  3. Low accuracy and high precision
  4. Low accuracy and low precision
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  1. When both groups are under similar conditions
  2. When the control group accidentally receives the treatment
  3. When the dependent variable is measured in both groups
  4. When group sizes are nearly equal
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  1. Large samples cannot contain real effects
  2. Practical significance must also be examined
  3. Statistical analysis is not part of science
  4. Small effects are always measurement errors
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  1. The hypothesis becomes more falsifiable
  2. The hypothesis may become effectively untestable
  3. The experiment becomes fairer
  4. Measurement accuracy increases
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  1. It is accepted as true without testing
  2. It performs the same explanatory work with greater simplicity
  3. Complex models are always wrong
  4. Simple models need no evidence
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  1. An attractive treatment name
  2. An objective and predefined measurement
  3. Fewer participants
  4. Selection of supportive responses only
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  1. Validity is present and accuracy is doubtful
  2. Repeatability is present and reproducibility is doubtful
  3. Reproducibility is present and repeatability is doubtful
  4. External validity is present and ethics is doubtful
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  1. Response bias
  2. Zero error
  3. Random error
  4. Calibration error
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  1. Internal validity
  2. External validity
  3. Precision
  4. Repeatability
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  1. Pre-existing selection differences may affect the result
  2. The dependent variable cannot be measured
  3. The experiment becomes entirely unethical
  4. Every result will be random
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  1. Both only increase sample size
  2. Sampling supports representativeness while assignment supports fair group comparison
  3. Sampling proves causation while assignment measures popularity
  4. Neither has scientific use
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  1. Name of the sample
  2. Variability of the data
  3. Existence of the independent variable
  4. Purpose of the scientist
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  1. Biased selection of results
  2. Increased measurement precision
  3. The sample becoming representative
  4. Independent verification occurring
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  1. So the report appears lengthy
  2. So independent verification is possible
  3. So the result becomes correct automatically
  4. So the hypothesis becomes a law
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  1. Sampling bias
  2. Observer bias
  3. Random assignment
  4. Scientific consensus
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  1. Different evidence may partly compensate for one another's limitations
  2. Different evidence always comes from the same method
  3. If one form is wrong all forms are wrong
  4. The number of evidence alone determines truth
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  1. Declare the result final truth
  2. State major limitations and consider alternative causes
  3. Adjust data to the expected form
  4. Remove the control group
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  1. Consensus has no value
  2. Broad consensus may reflect the evidence without requiring unanimity
  3. Any disagreement makes the claim false
  4. The majority always determines scientific truth
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  1. Improvement may also result from natural change or expectation
  2. The treatment group cannot be measured
  3. A control group is always better than treatment
  4. All improvements are false
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  1. The model proves the complete reality
  2. The model may be useful while retaining explanatory limitations
  3. Accurate predictions have no importance
  4. The model should be rejected immediately
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  1. The difference was not measured reliably
  2. The sample is too large
  3. The hypothesis is too simple
  4. The control group is unnecessary

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