GCSE Science - Working Scientifically

Hypothesis

A proposal intended to explain facts or observation.

Independent Variable

The variable you change

Dependent Variable

The variable you measure

Control Variable

The variable that stays the same

Theory

An accepted hypothesis

E.g Atomic Theory - John Dalton (1808)

Peer Review

The method used by scientists to test hypothesis

Economic Issues

Issue of scientific development due to money

Eg. Laceamab Drug Costing £20,000 per annum

Social Issues

Issue of scientific development due to perception

Eg. Embryonic Stem Cells stopping fertilisation

Personal Issue

Issue of scientific development due to opinions

Eg. Wind Farm on A Property due to noise and visual pollution

Environmental Issue

Issue of scientific development due to the environment

Eg. Genetically modified crops may have negative side effects on environment.

Risk Assessment

An assessment used to see what precautions can be made to prevent hazards from happening in an experiment.

Hazards

Something that could potentially cause harm

Eg. Electricity causing shocks

Precautions

Things put in place to minimize risk

Eg. Acid (Wearing gloves & goggles)

Repeatable Results

If the same person does an experiment

Reproducible

If someone else does the experiment or a different method or piece of equipment is used, the results will be similar.

Valid Results

Results that are both repeatable and reproducible and answers the hypothesis

Fair Test

An experiment that has valid results

Bigger Sample Size (Advantages)

Easier spotting anomalies

More variation in results

Bigger Sample Size (Disadvantages)

Expensive

Ensuring Repeatability

Repeat each reading (3x)

Ensuring Reproducibility

Use a second set of readings

Use another instrument observer

Accurate Results

A result close to the true value

Eg BP of Water is 100 so 101 would be accurate

Precise Results

A result close to the mean

Eg Mean 98 so 99 would be precise

Resolution

The smallest change a measuring instrument can detect

Eg. 0.1g is a higher resolution than 1g

Random Error

Unpredictable Human error while measuring

Eg. Reading the Value on a measuring cylinder incorrectly

Minimizing Errors (Random)

Repeat Results

Systematic Error

If a measurement is wrong by the same amount each time

Eg. If you didn’t measure at the 0cm on a ruler

Zero Error

A systematic error only caused to equipment not being zeroed properly

Eg. A scale having 0.01g before anything being put on it.

Minimizing Errors (Systematic & Zero)

Resetting the equipment or ruler to the correct value (0)

Subtract or Add the inflated or reduced value.

Anomalous Results

Result that doesn’t fit in with the rest.

Uncertainty

This is the range which is within what the true value is expected to be

Eg. 80±2 = 78-82 5<8<10 = 0±3

Finding Uncertainties

1. Find Mean 100

2. Find Range 100-96 = 4

3. Divide Range 2 4/2= 2

4. Add Mean and New Range Together 100±2

Categoric Data

When the independent variable comes in distinct categories a bar chart is used

Eg. Eye colour, Ice-cream flavours, Skin colour

Categoric Data Checklist

1. Graph Fits ½ Page

2. Include Key

3. Leave consistent gaps

4. Label Axis and Remember Units

Continuous Data

When the independent variable is numerical use a line graph.

Eg. Temperature

Continuous Data Checklist

1. Graph Fits ½ Page

2. Make sure there are crosses instead of dots

3. Label Axis and Remember Units

4. Draw A LOBF

Positive Correlation

One Variable increases so do does the other

Inverse (Negative) Correlation

One Variable increases the other decreases.

No Correlation

No relationship between variables

Tera (T)

10^12

Giga (G)

10^9

Mega (M)

10^6

Kilo (K)

10³3

Deci (d)

10^-1

Centi ©

10^-2

Milli (m)

10^-3

Micro

10^-6

Nano (n)

10^-9

Conclusion Checklist

1. Talk about range means and modes

2. Be specific with data

Evaluation

A critical analysis of the investigation as a whole