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Biology
Investigating Science
| Question | Answer |
|---|---|
| What makes a good scientific question | It is based on a hypothesis. |
| What must a scientific question be able to do | Be tested by direct observation or scientific tools. |
| What should scientific questions not be based on | Opinions, personal values, or judgements. |
| What must a scientific question be | Specific enough. |
| How many questions should a scientific investigation ask | A single question. |
| What must a scientific question always be | Something that can be tested. |
| What is a prediction | An outcome expected if the hypothesis is true. |
| Why are predictions important | Experiments gather evidence to test predictions. |
| What is a variable | A factor that may change in an experiment. |
| What is an independent variable | The factor changed in an experiment. |
| What is a dependent variable | The factor measured or observed, affected by the independent variable. |
| What is a controlled variable | A factor kept the same to make the test fair. |
| What is reliability | The extent to which repeated experiment findings agree under identical conditions. |
| How can reliability be tested | By repeating the experiment. |
| What is accuracy | How close the value of a measurement is to the actual value. |
| What is precision | How close repeated measurements of the same item are to each other. |
| How can accuracy and precision be improved | Calibrate equipment to be more accurate and precise. |
| Why maintain equipment | To keep it clean and functional. |
| How does choosing correct equipment help | It increases accuracy. |
| Why take multiple measurements | To calculate an average value. |
| What are random errors | Mistakes caused by chance that are unpredictable and do not recur. |
| What are systemic errors | Consistent differences between the observed/measured and the true value of something, caused by faulty or incorrectly used equipment. |
| How can an experiment be made fair | Use a control experiment. |
| Why ensure only one variable is changed | To make the experiment fair. |
| Why choose a large sample size | Larger samples increase accuracy. |
| Why use random selection | To prevent bias. |
| What is the benefit of experiments being easy to replicate | Allows others to test reliability. |
| What is a control experiment used for | A comparison against which the actual experiment is judged. |
| How many differences should exist between control and experimental setups | Only one, the independent variable. |
| What is sample size | The number of subjects or items being tested. |
| Why is a large sample size better | It produces more accurate results. |
| What is random selection | Each person/item has an equal chance of being chosen, preventing bias. |
| What is double-blind testing | Neither tester nor person being tested knows who is receiving the real treatment and who's receiving the placebo. |
| Why is double-blind testing used | To reduce bias from tester or subject. |
| Why is safety important in experiments | To prevent accidents and injury. |
| What are examples of lab safety | Tie back hair, wear a lab coat, wear safety glasses. |
| What is scientific integrity | Obeying all of the rules and values that govern scientific work.( conducting,reporting and applying the results of scientific activities ) |
| Why is integrity important | It keeps reports clear, unbiased, and repeatable. |
| What factors should be considered when choosing equipment | Accuracy, size, safety |
| What is repeatability | Very Similar measurements and results when repeated by the same group using the same method and equipment |
| What is reproducibility | Very Similar measurements and results when repeated by different people/group using different equipment and/or methods |
| What is data | Information or measurements obtained in an investigation. |
| What is qualitative data | Non-numerical descriptive information. |
| Why is qualitative data harder to analyse | It may involve subjective opinions. |
| What is quantitative data | information that can be counted or measured and has a numerical value |
| Why is quantitative data often more reliable | It is objective and not influenced by opinions. |
| What should be done when analysing data | Identify patterns, show relationships |
| What should be recognised during analysis | Anomalous observations. |
| What is the final step of analysis | Draw and justify conclusions. |
| Why is identifying patterns important | Helps predict future events/trends. |
| Where is the independent variable on a graph | On the x-axis. |
| Where is the dependent variable on a graph | On the y-axis. |
| What is correlation | An association between two variables. |
| What is causation | A change in one variable is the direct result of a change in a second variable |
| What is an anomalous result | A result that does not fit the pattern formed by the rest of the results |
| What might cause an anomalous result | Human error, wrong equipment, faulty equipment, poorly controlled variables |
| What should be done if an anomaly occurs | Repeat the reading or experiment. |
| What is a conclusion | A summary of results describing what has been learned. |
| control experiment | is an experimental set up used as a comparison against which the actual experiment can be judged |
| Factors to consider when designing and conducting experiments ( Runners Always Panic Every Friday So Remember Don't Stress It's Science ) | Reliability, Accuracy, Precision, Errors, Fairness ( control experiment), Sample size, Random selection, Double blind testing, Safety, Integrity, Selection of equipment |
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