sec 1 science chapter 1

• Evidence can be obtained by observing natural phenomena or conducting experiments.
• Qualitative data

  • Useful in helping us visualise an unknown object or learn about its characteristics
  • Expressed in words or drawings
  • Involves five senses
  • Usually descriptive
  • Cannot be measured, only observed
  • Examples: smell, taste
• Quantitative data

  • The numerical quantities of an object or phenomenon
  • Expressed in numbers
  • Involves five senses
  • Can be measured and observed
  • Examples: volume, mass
• Difference between qualitative data and quantitative data

  Qualitative data is observed by five senses, is usually descriptive, and cannot be measured while quantitative data is observed by five senses and can be measured.
• A hypothesis is a proposed explanation that may or may not be true or correct.
• Independent variable = changed variable

  Dependent variable = observed/measured variable

  Control variable = constant variable
• SI units

  • Volume (m^3)
  • Mass (kg)
  • Time (s)
  • Length (m)
  • Temperature (K)
• Accurate readings is when the average reading is closer to the true value of the object.
• Zero error

  • The type of error in which an instrument gives a non zero reading when the measured quantity should be zero.
  • Press the tare function to reset the scale to remove the error
• Parallax error

  • When instruments are used incorrectly, the measurements become less accurate and less precise
  • Parallax error is introduced into the measurement when a marking on an instrument is viewed from the wrong angle.
• Thermometer

  • Position the eye such that the line of sight is level with the top of the meniscus.
• Measuring cylinder

  • Position the eye such that the line of sight is level with the bottom of the meniscus
• Ruler

  • Position the eye such that the line of sight is perpendicular to the marking on the ruler
• Spring balance

  • Position the eye such that the line of sight is perpendicular to the marking on the scale.
• Precise readings is when the readings are closer to one another.
• Consistent/systematic error

  • Predictable
  • Examples: zero error
  • Same error for all measurements/consistently shows an error
  • Reduce systematic error, get more accurate results
• Unpredictable/random errors

  • Causes imprecise measurements
  • Examples: presence of wind
  • Not the same error for all measurements
  • Reduce random errors, get more precise measurements