Working Scientifically Flashcards
When evaluating science applications - 5 implications to consider
- personal
- social
- economic
- environmental
- ethical
What’s an ethical issue
A problem where a choice has to be made concerning what is right and what is wrong
How do scientific methods and theories develop over time?
new technology allowing new evidence to be collected and changing explanations as new evidence is found
Why are models helpful (3)
- making scientific ideas easier to understand
- help in making predictions
- help in developing explanations
Representational model
- use familiar objects to describe and explain observations
- e.g. using marbles to model water particles
Spatial models
- represent things that are tiny/ enormous
Descriptive models
- use words and ideas to help imagine something, or describe it simply
- chemical equations to represent reactions
Mathematical models
- use maths to describe systems and make predations
- scientists use these to describe and predict movements of planets and stars
computational model
- a type of mathematical model
- Met Office uses supercomputer used to predict weather
Peer review - meaning
Research that is peer reviewed has been evaluated by other scientists who are experts in that area of science.
What does peer review check (3)
Valid - does it measure what it says it does, was the method designed correctly and appropriately?
Original - has anyone else already carried out similar research, and has their work been credited? Are the results new?
Significant - are the findings of the research important?
Models advantage
Models can help to investigate an idea without ethical or practical difficulties.
International system of units - Sl
What and Why?
- scientists use internationally accepted names, symbols, definitions and units so that scientists everywhere can understand their work
Hypothesis - what (3)
- explanation based on observations
- and backed up by scientific knowledge and creative thinking.
- Must be testable
How scientists answer questions
- Make an interesting observation or notice a problem to solve
- Ask a scientific question
- Develop a hypothesis
- Make a predication based on hypothesis
- Collect evidence to test prediction by doing an experiment and/or making observations and/or searching for data else where
- Analyse the evidence
- Review the evidence - does it support the hypothesis - if no back to (step 3)
- Accept the hypothesis and develop it as an explanation or theory
independent variable
Variable you deliberately change
Dependent variable
Variable you measure for each change of the independent variable
Control variables
Ones that make affect the outcome, as well as the indecent variable.
These variables are kept the same
Continuous variable
Can have any value, and can be measured (e.g. time spent on social media)
Discrete variable
Whole number values
E.g. number of texts
Categoric variable
Values are described by labels
E.g. make and model of a phone
Accuracy is what
How close a numerical result is to the true value
Measuring temp. With a thermometer
- 3 things to do
- using thermometer carefully
- repeating measurements and calculating the mean
- repeating measurements with a different instruments, e.g. a temperature probe anbd checking that the readings are the same
Anomalies
try to explain why the odd result is different - an odd result can be removed if there is a good reason to do so, eg if there is a measurement or recording error
Precision ?
Precise measurements give similar results if you repeat the measurements
- so spread of data set is small
How to get precise data
- use a measuring instrument with high resolution
- the resolution of a measuring instrument is the smallest change in the quantity that gives a change in the reading that you can see
How should all results be recorded when using a measuring instrument
To same number of decimal places
How to see which set of data is more precise?
Check the spreads - subtract smallest measurement from largest
Can data be precise but not accurate
Yh
Repeatable
Measurements are very similar when repeated by the same person or group, using the same equipment and method
Reproducible
Measurements are very similar when repeated by a different person or group, using different equipment and/or methods
If someone else repeats your investigation /
If you do same investigation with different equipment =
Reproducible
Repeat several times using same method and equipment and get similar results, results are ?
Repeatable
Table, which columns for independent variable, which for dependent , where units written ?
- IV in left column
- DV in right column
- write units in column headings, not next to each piece of data
What chart/graph for categoric data?
Bar chart
Cat, dog, Guinea pig
Chart/graph for continuous data
Line graph
Variable on x + y axis
Independent, x
Dependent, y
Scale of y axis =
- scale is even
- chart should be as big as possible
Tell me about outliers
- what it is
- included in mean or no
- any value in a set of results that you judge its not part of the natural variation you expect
- consider outliers carefully, and decide whether or not to include them when calculating mean
Line of best fit (3)
- incl shape
- circle any outliers
- decide whether the LOBF is a straight line or curve
- draw line through middle of points - should be roughly same number of points above the line as there are below it
2 parts of a scientific conclusion
- description of a pattern
- scientific explanation of the pattern, linked to the hypothesis
Relationships between variables
- linear
- positive/ negative
TO EVALUATE an investigation. Think about 2 questions:
- how to improve method
- what is the quality of the data
Quality of data can be evaluated by considering (4)
Accuracy, precision, repeatability, reproducibility
2 types of errors
Confidence in accuracy o results. Data cannot always be relied upon
Random error, systematic error
Random error
Random errors are unpredictable and can be due to human error.
eg in judging when to stop a timer, changes to em or e.g. changes in environmental conditions
Action against random errors
- you cannot control the chase of random errors
- however, you can reduce their effect by repeating measurements and calculating a mean
Systematic errors
Systematic errors cause results to differ from the true value by the same amount each time. These could be due to:
- a fixed error in the measuring instrument, eg not being correctly zeroed (ammeter that doesn’t read zero when no current)
- influence of the environment, eg allowing a reaction to take place at a hotter temperature
- method of observation, eg not reading the volume of a liquid correctly using bottom of the meniscus
Against a systematic error
- if you think you have a systematic error, repeat the measurements with a different piece of equipment
- then compare the two sets of measurements
Uncertainty definition
The interval within which the true value can be expected to lie, with a given level of confidence
I.e. temperature is 65.5 degrees C +- 0.5 C with a confidence of 95 percent
Uncertainties are due to
Measuring instrument
If the smallest scale division is 1 degrees, you can estimate the uncertainty as
+- 0.5 degree
Range and confidence in results
The range describes the difference between the highest and lowest repeat results. The smaller the range, the greater the confidence will be in the accuracy of the results.
