Presenting & Interpreting Results (OCR A Level Physics)

Presenting Observations & Data

• Data can be presented in a variety of ways, such as on graphs, charts, or tables

• Tables are applicable to any experiment yielding data

• Graphs, on the other hand, are a little trickier depending on the type of data collected e.g. quantitative or qualitative

  • Quantitative data uses numerical values

  • Qualitative data is observed but not measured with a numerical value e.g. colour

Presenting Data in a Table

• When taking readings, a sensible range should be taken, and the values should all be stated to an appropriate number of significant figures or decimal places

  • This is usually the same number as the resolution of the measuring instrument

• The columns in any table should have both a quantity and a unit in their heading

  • When labelling columns, the names of the quantities should be separated from their unit by a forward slash ( / )

• For data displayed in a table:

  • The first column should contain the independent variable

  • The second column should contain the dependent variable

  • If repeat readings of the dependent variable are required, these should be included with a column for the mean value at the end

  • Any columns required for processing data e.g. calculations should come after this

Conventions for presenting data in a table. The length is the independent variable and the frequency is the dependent variable

Presenting Data on a Graph

• All readings, including suspected anomalous results, should be plotted on a graph so that they can be easily identified

• When taking repeat readings, it is the mean value that is plotted

• The way data is presented on a graph depends on what type of data it is

Discrete data

• Only certain values can be taken, normally a whole number e.g. number of students

  • This should be displayed on a scatter graph or bar chart

Continuous data

• Can take any value on a scale e.g. voltage in a circuit

  • This should be displayed on a line or scatter graph

Categorical data

• Values that can be sorted into categories e.g. types of material

  • This should be displayed on a pie or bar chart

Ordered data

• Data that can be put in ordered categories e.g. low, medium, high

  • This should be displayed on a bar chart

Processing, Analysing & Interpreting Experimental Results

• After an experiment has been carried out, sometimes the raw results will need to be processed before they are in a useful or meaningful format

• Sometimes, various calculations will need to be carried out in order to get the data in the form of a straight line

  • This is normally done by comparing the equation to that of a straight line: y = mx + c