PRACTICAL SKILLS (PHYSICS)

Hypotheses

Predictions supported by explanations used to test the effect of one variable on another and the relationship between them in practical work.

Variable

Any characteristic, number, or quantity that can be measured or counted.

Control Variables

Variables kept constant in an experiment to ensure that the effect on the dependent variable is due to changes in the independent variable.

Risk Assessment

Process involving hazard identification, risk analysis, and control measures to ensure safety in an investigation.

Precision and Uncertainty

Aim to increase precision by using instruments with smaller resolutions and reading to the smallest division possible to reduce uncertainty in results.

Random Errors

Errors caused by incorrect timing or reading of instruments, including reaction time errors and parallax errors, which should be minimized in measurements.

Parallax Error

It is caused by a student not reading the measurement at eye level. It can lead to the reading being too high or too low.

Systematic Errors or Zero Errors

These are caused by faulty equipment that doesn’t reset to zero properly.

Anomalous Results

Outliers in data that do not fit the expected pattern, which can be identified through repeat measurements or a large sample size to improve accuracy.

Graphs and Charts

Tools for visual representation of data, including line graphs, pie charts, and bar graphs, to display relationships and patterns in the data.

Pie Chart

It can be used to show the make-up of something, when compared to the total data. Each section is a category or name and the size of the pie segment represents a percentage of the whole.

Bar Graphs

Are used when the x-axis is a range of categories, names or labels (categorical variables) and the y-axis can take any numerical value (continuous variable).

Line Graphs

Are used when both axes are continuous variables because they can take any numerical value.

Line Graph Construction

Guidelines for creating a line graph with labeled axes, scaled appropriately, and connected points to draw the best line or curve of fit.

Patterns in Graphs

Analysis of data to identify relationships between independent and dependent variables, such as direct proportion, inverse proportion, or positive/negative correlations.

No correlation between variables A and B.

Variable B is independent of variable A.

Direct proportion between A and B.

An example of this might be if A is the resultant force on a dynamics trolley and B is the acceleration of the trolley. The acceleration of the trolley is directly proportional to the resultant force.

A and B are proportional to each other.

An example of this might be if A is a weight added to a spring and B is the length of the spring. The length of the spring is proportional to the weight added to it.

There is an increasing positive correlation between variables A and B.

A increases by a regular amount. B increases at an increasing rate.

There is a decreasing positive correlation between variables A and B.

A increases by a regular amount. B increases at a decreasing rate.

Variables A and B show negative correlation to each other.

A increases by a regular amount. B decreases by a regular amount.

Variables A and B are inversely proportional to each other.

An example of this might be if A was the mass of a dynamics trolley and B was its acceleration. The acceleration of the trolley is inversely proportional to the mass of the trolley.

Strength of Evidence

Evaluation of experimental methods, measuring techniques, and data to judge the reliability of conclusions, considering factors like repeatability and reproducibility.