Module 1.1 Practical skills assessed in a written assessment Flashcards
Primary research
New data is collected and conclusions are then drawn
Secondary research
Data from other studies is used to draw conclusions
Valid results
Are suitable results that can test the aim
Hypothesis
A prediction using scientific knowledge and trusted information from textbooks, colleagues and papers
Surveys
A type of primary research
Sets out limits to observe something already happening
Meta study
Secondary research
Uses the raw data from a variety of different studies to try to answer a new aim
Mathematical approach using statistics
Allows a large data group to be studied
Quantitative data
Has a numerical value
Requires a measuring instrument to be observed
Qualitative data
Descriptions of what is observed
Resolution
The smallest change in the quantity being measure that can be observed
Accuracy
How close to the true value a measurement is
Independent variable
The factor that you are interested in changing to see the effect in has on another factor
Listed in the first column of the results table
Dependent variable
The factor that you measure or observe in an experiment
This data is added to the results table as the experiment progresses
Control variable
A factor that you must keep constant between each repeat of the experiment so the results can be compared
Not recorded in a result table
Extraneous variable
A factor that may affect the experiment but that you have not measured or controlled
SI units
The International System of Units (SI) states the units that quantities should be measured in
E.g. Distance is measured in metres (m)
Time in seconds (s)
Mass in kilograms (kg)
Method
A step-by-step detailed explanation of how to complete an experiment
Should be written in such a way that anyone can follow it and complete the experiment in the same way
The equipment and reagents need to be listed before the method
Fully labelled diagram
Tables
First column = independent variable, can be completed before experiment
Other columns contain the dependent variable
Each column heading must be labelled with the variable and its unit of measurement
Entries to the table don’t require units as they are recorded in the headings
Continuous variables
A measured value that could be any number
E.g. Temperature
Discrete variables
Values can only be definite numbers
E.g. Atomic number
Categoric variables
A qualitative description
E.g. The colour of a precipitate
Independent variable
X axis (horizontal axis)
Dependent variable
Y axis (vertical axis)
Scatter graph
Both variables must be continuous
Line graph
The independent variable can be discrete or categoric
The dependent variable can be continuous or discrete
Bar chart
The independent variable can be discrete or categoric
The dependent variable can be continuous or discrete
Scatter graphs
Maximise graph paper use so trends are easy to observe
Choose a suitable scale (this may or may not mean starting at the origin)
Independent variable - continuous, on x-axis
Dependent variable - also continuous, on y-axis
Lines of best fit
No pattern = don’t draw a line of best fit
If a data point doesn’t fit the pattern, circle it, ignore the anomalous result
Pattern is a straight line - use a ruler, use a sharp pencil, draw the line, don’t just connect the dots - draw the pattern the data shows
Pattern is a curve - draw a smooth curve - hold pencil firmly on the desk and move the paper to get a smooth curve
Gradient
Change in y DIVIDED BY change in x
Concordant results
Values that are close to each other and therefore represent reliable data
Results that aren’t concordant are anomalous
Only concordant results are used to calculate an average
Accurate
Results close to the true value
Reliable
Results that are similar when they are repeated
A false positive
When a positive result is produced but not due to the desired product being formed
Systematic error
The same error in every measurement
Due to the limits of the equipment e.g. a piece of measuring equipment not being correctly calibrated
Random error
An error that may or may not be present
Different every time
Due to the experience of the scientist e.g. not controlling draughts in a room
Margin for error
Shows the range that a value lies within
Precision
The degree to which repeated values, collected under the same conditions in an experiment, show the same result
Weighing by difference
Mass of container before and after a material is added and the difference between these values is the mass of the material
Percentage error
A mathematical way of comparing the experimental value with the actual value
Margin for error of a 50 cm^3 measuring cylinder
+ or - 0.1 cm^3
Margin for error of a 10 cm^3 measuring cylinder
+ or - 0.01 cm^3
Margin for error of a 50 cm^3 pipette
+ or - 0.05 cm^3
Percentage error of a value
Actual value - experimental value DIVIDED BY accepted value
TIMES BY 100
Percentage error of equipment
Maximum error DIVIDED BY measured value
TIMES BY 100
