Chapter 1: A Physics Toolkit

  1. Section 1: Methods of Science
  2. What is Physics?
  3. Science is a process based on inquiry that helps develop explanations about events in nature
  4. PHYSICS – branch of science that involves the study of the physical world
  5. Energy
  6. Forces
  7. Motion
  8. Scientific Method – patterns of investigation procedures
  9. Observation (noticing something and asking “why?” or “how?”) 
  10. Research/ gather information (what is known already?) 
  11. Form and test a hypothesis 
  12. Hypothesis – possible explanation based on what is already known
  13. Make observations
  14. Build a model
  15. experimentation
  16. Analyze data 
  17. Draw conclusions 
  18. Is the hypothesis supported or not?
  19. Do you need a new hypothesis?
  20. Must the experiment be tweaked?
  21. Peer review 
  22. Scientists in the same field of study review your information/ data
  23. Maintain objectivity
  24. Objective – not influenced by personal feelings
  25. Subjective – based on personal feelings, tastes or opinions
  26. Models – representation of an idea, event, structure, or object that helps people better understand it
  27. May and do change
  28. Ex.: J.J. Thompson’s atomic model (1904) = electrons embedded in a ball of positive charges
  29. Ex.: Rutherford’s atomic model (1911) = nucleus of positive charge surrounded by electrons in specific orbit around nucleus
  30. Ex.: Electron cloud model (present day) = nucleus surrounded by electrons in a variety of planes outside the nucleus
  31. Computer simulations for models that are not testable…yet!
  32. Scientific Theories and Laws
  33. Theory – explanation of things or events based on knowledge gained from observations and investigations
  34. Law – statement aboiut what happens in nature and seems to be true all the time
  35. Gravity
  36. Newton’s 1st, 2nd, and 3rd Laws of Thermodynamics
  37. Note: Theories can be used to explain laws but they DO NOT become laws!
  38. Many theories exist and they constantly change
  39. Very few laws exist in nature (therefore, they are special)
  40. Limitations of Science
  41. Science cannot explain EVERYTHING!
  42. Science is a guess that turns out to be “true” or not
  43. MUST BE TESTED!
  44. MUST BE TESTED IN VARIOUS WAYS!
  45. Science is rooted in the OBJECTIVE!
  46. No room for feelings
  47. No room for emotions
  48. No room for opinions
  49. Therefore, it IS or it IS NOT…period!
  50. Section 2: Mathematics and Physics
  51. Mathematics in Physics
  52. Equations are used to show relationships between measurements
  53. Theories  experiments  numerical results  analysis
  54. Ex.: If you drop a penny does it fall? If so, how fast?
  55. Based on the above data, one can create other models to investigate the speed at which other items fall (e.g. bowling balls, tennis balls, trucks, etc.)
  56. Then, one can pick the best model for future experiments…OR, one can scrap all the models and create a new one.
  57. SI Units – units the whole world agrees on (lessens confusion)
  58. Base Units
  59. Length = meter (m)
  60. Mass = kilogram (kg)
  61. Time = second (s)
  62. Temperature = Kelvin (K)
  63. Amount of a substance = mole (mol)
  64. Electric current = ampere (A)
  65. Luminous intensity = candela (cd)
  66. Switching between SI units is easy…just move the decimal!
  67. Smaller
  68. deci- (d) = 1 x 10-1 = 0.1
  69. centi- (c) = 1 x 10-2 = 0.01
  70. milli- (m) = 1 x 10-3 = 0.001
  71. micro- (µ) = 1 x 10-6 = 0.000001
  72. nano- (n) = 1 x 10-9 = 0.000000001
  73. pico- (p) = 1 x 10-12 = 0.000000000001
  74. femto- (f) = 1 x 10-15 = 0.000000000000001
  75. Bigger
  76. Kilo- (K) = 1 x 103 = 1,000
  77. Mega- (M) = 1 x 106 = 1,000,000
  78. Giga (G) = 1 x 109 = 1,000,000,000
  79. Tetra- (T) = 1 x 1012 = 1,000,000,000,000
  80. Dimensional Analysis – a relationship exists between all units and dimensional analysis is a way to surf between those units
  81. A method of treating units as algebraic quantities that can be cancelledin order to predetermine if your physics equations are set up correctly
  82. Ex.: How many grams in a kilogram
  83. 1 Kg = 1 x 103 g / 1 Kg  1,000 g
  84. Ex.: How many cars are in a week? (It can be calculated!!)
  85. Significant Figures – valid digits in a measurement
  86. Measurement is inherently flawed, based on user error and imprecise measurement tool
  87. Therefore, the number of significant figures is determined by how precise one’s measurement is:
  88. Nonzero digits are significant (i.e. 37…2 sig. figs.)
  89. Any zeros between 2 nonzero digits are significant (i.e. 407…3 sig. figs.)
  90. Final zero after decimal are significant (i.e. 37.0…3 sig. figs.)
  91. Space holding zeros are NOT significant!
  92. Ex.: Measure a pen with a ruler. Is it 138 mm? More? Less?
  93. It’s 138 mm and just a “hair more;” so, its 138.1 mm
  94. There is a difference between 138.1 mm and 138.10 mm and that difference is the precision at which the pen has been measured with
  95. Solving Problems
  96. Solving Physics problems will be complex and require strategies to solve.
  97. Ex.: When a car travels 434 km in 4.5 hrs, what is the car’s average speed?

434 km = 96.4 km/h distance = speed x time  speed = distance

4.5 h time

  1. Measurement – comparison between an unknown quantity and a standard
  2. Unknown Quantity Standard

Mass of a shopping cartgram

Blood pressurerange between 110/60 – 130/90

HeightAverage height (in meters)

WeightAverage weight (in kg)

  1. Comparing Results
  2. Scientists share results 
  3. Other scientists examine results and experiments that produced them 
  4. Results reported without certainty must be within a margin that is in agreement with old measurement
  5. Precision vs. Accuracy
  6. Precision – degree of exactness
  7. Depends on instrument and technique
  8. Number of significant figures shows precision
  9. 67.100 g vs. 67.1 g, which is more precise?
  10. Accuracy – how well the result of a measurement “agree” with the real value
  11. Describes the need for calibration of measuring devices
  12. Ex.: Does a radiation output machine used in cancer treatment put out the right amount of radiation? Too much? Too little? Thus, it must be calibrated to be accurate.
  13. Techniques of good measurement
  14. Use measurement devices accurately
  15. Be aware of the angle it which you measure
  1. Graphing Data
  2. Identifying Variables
  3. When you create and conduct an experiment it is important to only change ONE factor at a time
  4. Independent variable – the factor that is being manipulated
  5. For example, masses of different objects hanging from different springs
  6. Dependent variable – the factor that depends on the independent variable
  7. For example, how much each spring stretches in response to each of the aforementioned masses hanging on them
  8. Line of best fit – a line graph that shows how the dependent variable changes with the independent variable
  9. Better model for predictions than any point along the line
  10. Shows patterns that are not immediately evident

  1. Linear Relationships
  2. When the dependent relationship varies linearly with the independent variable
  3. Equation for the line: y = mx + b
  4. Slope = m = rise/run = Δy/Δx
  5. b = y-intercept
  6. Shows the dependent variable when independent variable is known
  1. Non-Linear Relationships
  2. When the dependent relationship varies non-linearly with the independent variable
  3. 2 types:
  4. Quadratic relationship – when one variable depends on the square of another
  5. Y = ax2 + bx + c
  1. Inverse relationship– a hyperbolic relationship in which one variable depends on the inverse of another
  2. Y = a/x
  1. Predicting Values
  2. When scientists discover relationships like those shown in graphs they make predictions
  3. Ex.: If 10-year-olds, 20-year-olds, and 30-year-olds were weighed and their weights to ages were graphed, scientist could predict how much 25-year-olds weigh
  4. NOTE: It is important to stay within the parameters of the graphs
  5. For instance, in the above age-weight graph, approximating the ages of 90-year-olds would not be prudent, given the graph is missing data points from 31- to 90-year-old persons