19. 1:2 Scientific Notation Goals and Objectives: Express numbers in scientific notation. Convert between units using dimensional analysis.
20. Scientific Notation Scientific notation – a method that conveniently restates a number without changing its value. Coefficient – is the first number in scientific notation. (1-10) Exponent – the multiplier of the coefficient by the power of 10.
22. Adding and Subtracting Scientific Notation Exponents must be the same. Convert if necessary. Coefficients are added or subtracted. Change exponent to simplify answer.
24. Multiplication and Division using Scientific Notation Exponents do not need to be the same. Multiply or divide coefficients When multiplying, add exponents When dividing, subtract exponents. (divisor from dividend)
26. Dimensional Analysis Dimensional Analysis – is a systematic approach to problem solving that uses conversion factors to move, or convert, from one unit to another. Example
27. Conversion Factor Conversion Factor - Is a ratio of equivalent values having different units. Examples: 1000m / 1km 1 hr / 3600s 1 ml / 1 cm3
29. 1:3 Uncertainty in Data Goals and Objectives: Define and compare accuracy and precision. Describe the accuracy of experimental data using error and percent error Apply rules for significant figures to express uncertainty in measured and calculated values.
30. Uncertainty in Data Accuracy – is how close a measure value is to an accepted value. Precision - Is how close a series of measurements are to one another. The amount of uncertainty in a measurement More precise = less uncertainty
31. Precision in Measurements When measuring any item, write all digits that are confirmed and one estimated digit. Example
32. Error Error is the difference between an experimental value and an accepted value. Error = experimental value – accepted value Example
33. Percent Error Percent error expresses error as a percentage of the accepted value Percent error =
34. Significant Figures Rules for Significant Digits Nonzero digits are always significant. Zeroes are sometimes significant, and sometimes they are not. Zeroes at the beginning of a number (used just to position the decimal point) are never significant. Zeroes between nonzero digits are always significant. Zeroes at the end of a number that contains a decimal point are always significant. Zeroes at the end of a number that does not contain a decimal point may or may not be significant. Scientific notation is used to clarify these numbers.
35. Significant Figures Rules for Significant Digits Exact numbers can be considered as having an unlimited number of significant figures. In addition and subtraction, the number of significant digits in the answer is determined by the least precise number in the calculation. The number of significant figures to the right of the decimal in the answer cannot exceed any of those in the calculation. In multiplication and division, the answer cannot have more significant digits than any number in the calculation.
37. Rounding Numbers When rounding numbers to the proper number of significant digits, look to the right of the last significant digit. 1-4: round down the last sig fig 5-9: round up the last sig fig.
40. 1:4 Representing Data Goals and Objectives Create graphs to reveal patterns in data. Interpret graphs. Explain how chemists describe submicroscopic matter.
41. Representation of Data Graph is a visual display of data Circle graphs (pie chart) – display parts of a whole. Bar graphs – shows how a quantity varies across categories Line graphs – most graphs used in chemistry
42. Rules for Good Graphing Rules for Good Graphing on Paper: All graphs should be on graph paper. Identify the independent and dependent variables in your data. The independent variable is plotted on the horizontal axis (x-axis) and the dependent variable is plotted on the vertical axis (y-axis). Determine the range of the independent variable to be plotted. Spread the data out as much as possible. Let each division on the graph paper stand for a convenient unit. This usually means units that are multiples of 2, 5 or 10…etc.
43. Rules for Good Graphing Rules for Good Graphing on Paper: Number and label the horizontal axis. The label should include units. Repeat steps 2. through 4. for the dependent variable. Plot the data points on the graph. Draw the best-fit straight or smooth curve line that passes through as many points as possible. Do not use a series of straight-line segments to connect the dots. Give the graph a title that clearly tells what the graph represents (y vs. x values).
44. Rules for Good Graphing Rules for Good Graphing on the Computer: From the insert menu on the Microsoft word program choose insert chart. Identify the independent and dependent variables in your data. The independent variable is plotted on the horizontal axis (x-axis) and the dependent variable is plotted on the vertical axis (y-axis). Insert data in the excel window that opens. Be sure to pay attention to the excel column vs. graph axes location. Through the toolbox menu, give the graph a title that clearly tells what the graph represents. (y vs. x variable). Through the toolbox menu, give the axes in the graph labels that include units.
45. Representing Data Linear relationship – variables are proportionally related Line of best-fit is a straight line but is not perfectly horizontal or vertical.
46. Representing Data Slope – is equal to the change in y divided by the change in x Rise/run Δy/Δx
47. Representing Data Interpolation – the reading of a value from any point that falls between recorded data points When points on a line graph are connected, the data is considered to be continuous.
48. Representing Data Extrapolation – the process of estimating values beyond the plotted points. The line of best fit is extended beyond the scope of the data
49. Representing Data Model – is a visual, verbal or mathematical explanation of experimental data. Example
51. 1:5 Scientific Method and Research Goals and Objectives Identify the common steps of scientific methods. Compare and contrast types of data. Identify types of variables. Describe the difference between a theory and a scientific law. Compare and contrast pure research, applied research, and technology
52. Scientific Method and Research Scientific Method – is a systematic approach and organized process used in scientific study to do research Observation Hypothesis Experiments Conclusion
53. Scientific Method Observation – is an act of gathering information. Qualitative – information that describes color, odor, shape or other physical characteristic Quantitative – information taken in the form of a measurement. Temperature, pressure, volume, quantity, mass
55. Scientific Method Experiments – is a set of controlled observations that test the hypothesis. Independent variable – the variable that is controlled or changed incrementally. Dependent variable – the value that changes in response to the independent variable. Control – is a standard for comparison.
58. Scientific Theory and Law Theory – is an explanation of a natural phenomenon based on many observations and investigations over time. Scientific Law- a relationship in nature that is supported by many experiments.
59. Scientific Research Pure research – is done to gain knowledge for the sake of knowledge itself. Applied research – is research undertaken to solve a specific problem
