Practical Skills

• Absolute Uncertainties


  The interval that a value is said to lie within, with a given level of confidence
• Accuracy


  A measure of how close a measurement is to the true value
• Analogue Apparatus


  Measuring apparatus such as rulers, beakers and thermometers that rely on the experimenter reading off a scale to determine the measurement
• Anomalies


  Data points that don't fit the pattern of the data. You should determine why an anomalous result has occurred before removing it. Repeat readings help remove anomalies
• Control Variables


  Variables that must remain the same throughout an experiment so as to not affect the results
• Dependent Variables


  The variable being measured in an experiment. It is dependent on the independent variable. The dependent variable should be plotted on the y-axis of a graph
• Digital Apparatus


  Measuring apparatus such as ammeters, voltmeters and digital calipers that digitally measure and display a measurement
• Fiducial Marker


  A thin marker, such as a splint, that is used to ensure readings are taken from the same place each time. They are used to improve the accuracy of measurements
• Gradient


  The change in the y-axis value over the change in the x-axis value between two points. If the graph is curved, a tangent can be drawn to calculate the gradient at a specific point
• Independent Variables


  The variable that is changed by the experimenter in an experiment. The independent variable should be plotted on the x-axis of a graph
• Line of Best Fit

  A line drawn on a graph to demonstrate the pattern in the plotted data points
• Percentage Uncertainties


  The uncertainty of a measurement, expressed as a percentage of the recorded value
• Precision


  A measure of how close a measurement is to the mean value. It only gives an indication of the magnitude of random errors, not how close data is to the true value
• Prefixes


  Added to the front of units to represent a power of ten change
• Random Errors


  Unpredictable variation between measurements that leads to a spread of values about the true value. Random error can be reduced by taking repeat measurements
• Repeatable


  The same experimenter can repeat a measurement using the same method and equipment and obtain the same value
• Reproducible

  An experiment can be repeated by a different experimenter using a different method and different apparatus, and still obtain the same results
• Resolution


  The smallest change in a quantity that causes a visible change in the reading that a measuring instrument records
• Resolution of Forces

  The splitting of a force into its horizontal and vertical components
• Scalar Quantities

  A quantity that only has a magnitude, without an associated direction. Examples include speed, distance and temperature
• SI Units

  The standard units used in equations. They are: metres, kilograms, seconds, amps, Kelvin and moles
• Significant Figures

  A measure of a measurement's resolution. All numbers except zero are counted as a significant figure. When zeros are found immediately after a decimal place, they too are counted
• Systematic Errors

  Causes all readings to differ from the true value by a fixed amount. Systematic error cannot be corrected by repeat readings, instead a different technique or apparatus should be used
• Triangle of Forces

  A method of finding the resultant force of two forces. The two forces are joined tip to tail and the result is then the vector that completes the triangle
• Vector Quantities

  A quantity that has both a magnitude and an associated direction. Examples include velocity, displacement and acceleration
• Vernier Scales

  The type of scale used on calipers and micrometers, that involve reading from a fixed scale and a moving scale to produce accurate measurements
• Zero Errors

  A form of systematic error, caused when a measuring instrument doesn't read zero at a value of zero. This results in all measurements being offset by a fixed amount
• Planning an experiment


  1. Identify the apparatus required

  2. Know the range and resolution of all measuring instruments

  3. Calibrate instruments

  4. Measure the variables using appropriate instruments and techniques

  5. Identify control variables and keep them constant

  6. Know whether to take repeats

  7. Identify, discuss or resolve health and safety issues

  8. State a hypothesis

  9. Apply the data to the situation to determine a conclusion and whether the data supports the hypothesis, identify sources of uncertainty and talk about how they could have been reduced
• Measuring instruments


  Purpose and how to use them
• Measurements should be given to appropriate units, prefixes help make understanding data easier
• Prefixes and their meanings

  • Tera (T) - 10^12
  • Giga (G) - 10^9
  • Mega (M) - 10^6
  • Kilo (k) - 10^3
  • Deci (d) - 10^-1
  • Centi (c) - 10^-2
  • Milli (m) - 10^-3
  • Micro (μ) - 10^-6
  • Nano (n) - 10^-9
  • Pico (p) - 10^-12
• Data presentation


  • First column is independent variable, next n columns are n repeats of dependent variable, columns after that are for processing data
  • Data in a column should be to the same number of significant figures as the resolution of the measuring instrument
  • Quantitative data uses numbers, qualitative data is observed but not measured with a numerical value
• Types of data


  • Discrete - only certain values can be taken
  • Continuous - can take any value on a scale
  • Categoric - values that can be sorted into categories
  • Ordered - data that can be put in ordered categories
• How to display different types of data

  • Discrete - scatter graphs and bar charts
  • Continuous - line or scatter graph
  • Categoric - pie or bar chart
  • Ordered - bar chart
• Processing, analysing and interpreting results

  1. Find the mean of repeat results

  2. Mean = sum of results / no. data points

  3. Mean should be to the same number of significant figures as the data used to calculate it
• Scatter graphs


  • Used to determine correlation, each point is plotted and a line of best fit drawn through them, an appropriate scale is one that is easy to read and allows the data to fill at least half of the page
• Positive correlation


  If one variable increases, the other increases
• Negative correlation


  If one variable increases, the other decreases
• No correlation


  No relationship between the variables
• Straight line graphs


  Always in the form y = mx + c, where m is the gradient, c is the y-intercept, and x and y represent the x and y coordinates at a point on the graph