This document provides an overview of a chemistry unit on data and measurement. It discusses what data is, how it can be used, and various measurement skills including metric conversions, dimensional analysis, graphing, and calculating with significant figures. The unit covers scientific notation, uncertainty in data through accuracy, precision, error and significant figures. It also discusses representing data through different types of graphs and models, as well as the scientific method, research types, and differences between scientific theories and laws.

1. What is data and
what can it tell us?
Chemistry: Unit 1

2. What is data?

3. What can data tell us?

4. Skills
Metric Conversions
Dimensional Analysis
Graphing
Scientific Notation
Data Pattern Recognition
Calculations with Significant
Figures

5. 1:1 Units and Measurements
Goals and Objectives:
• Define SI base units for time,
length, mass, and temperature.
• Explain how adding a prefix
changes a unit.
• Compare the derived units for
volume and density.

6. Units and Measurements
Base unit – is a defined unit in a system
of measurement that is based on an
object.

7. SI Units
Base Quantity Base Unit Symbol
Length Meter m
Mass Kilogram/gram kg
Time Second S
Temperature Kelvin K
Amount of a
Substance
Mole mol
Electric Current Ampere A
Luminous
Intensity
Candela cd

8. Prefixes
Objective: Explain how adding a
prefix changes a unit.
How important are prefixes?

9. SI Unit Prefixes
Prefixes Symbol Decimal Sc.Notation
Femto- f .000 000 000 000 001 10-15
Pico- p .000 000 000 001 10-12
Nano- n .000 000 001 10-9
Micro- µ .000 001 10-6
Milli m .001 10-3
Centi c .01 10-2
Deci- d .1 10-1
Kilo- k 1 000 103
Mega M 1 000 000 106
Giga G 1 000 000 000 109
Tera T 1 000 000 000 000 1012

10. Units and Measurements
Kelvin – The SI unit for temperature. Based
on Absolute Zero.
•Kelvin – Celsius Conversion Equation
•K = °C + 273

11. Derived Unit
Derived unit – a unit that is defined by a
combination of base units.
• Examples:
•g/ml
•cm3
•m/s2

12. Derived Unit
• Liter – the SI unit for volume.
•1L = dm3
•1ml = 1cm3

13. Density
• Density – is a physical property of
matter and is defined a s the amount
of mass per unit volume.
•D = m/v

14. Practice Problems
• CALM: Unit 1:1
End 1:1

15. 1:2 Scientific Notation
Goals and Objectives:
• Express numbers in scientific
notation.
• Convert between units using
dimensional analysis.

16. 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.

17. Scientific Notation
• Example

18. Adding and Subtracting
Scientific Notation
• Exponents must be the same.
Convert if necessary.
• Coefficients are added or subtracted.
• Change exponent to simplify answer.

19. Adding and Subtracting
Scientific Notation
Example

20. 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)

21. Multiplication and Division
using Scientific Notation
• Example

22. 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

23. Conversion Factor
Conversion Factor - Is a ratio of
equivalent values having different
units.
• Examples:
•1000m / 1km
•1 hr / 3600s
• 1 ml / 1 cm3

24. Practice Problems
• CALM: Unit 1:2
End 1:2

25. 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.

26. 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

27. Precision in Measurements
• When measuring any item, write all
digits that are confirmed and one
estimated digit.
• Example

28. Error
Error is the difference between an
experimental value and an accepted
value.
•Error = experimental value – accepted
value
•Example

29. Percent Error
Percent error expresses error as a
percentage of the accepted value
• Percent error =
error
accepted×value
x100%

30. Significant Figures
Rules for Significant Digits
1. Nonzero digits are always significant.
2. Zeroes are sometimes significant, and sometimes they
are not.
a. Zeroes at the beginning of a number (used just to
position the decimal point) are never significant.
b. Zeroes between nonzero digits are always
significant.
c. Zeroes at the end of a number that contains a
decimal point are always significant.
d. Zeroes at the end of a number that does not contain a
decimal point may or may not be significant.
i. Scientific notation is used to clarify these
numbers.

31. Significant Figures
Rules for Significant Digits
3. Exact numbers can be considered as having an
unlimited number of significant figures.
4. In addition and subtraction, the number of
significant digits in the answer is determined by
the least precise number in the calculation.
a. The number of significant figures to the right of
the decimal in the answer cannot exceed any of
those in the calculation.
5. In multiplication and division, the answer cannot
have more significant digits than any number in
the calculation.

32. Significant Figures
• Examples

33. 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.

34. Rounding Numbers
• Examples:
• 54.3654 to 4 sig figs:
•To 3 sig figs:
•To 2 sig figs:
•To 1 sig fig:

35. Practice Problems
• CALM: 1:3

36. 1:4 Representing Data
Goals and Objectives
• Create graphs to reveal patterns in
data.
• Interpret graphs.
• Explain how chemists describe
submicroscopic matter.

37. 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

38. Rules for Good Graphing
Rules for Good Graphing on Paper:
1. All graphs should be on graph paper.
2. Identify the independent and dependent variables in
your data.
a. The independent variable is plotted on the
horizontal axis (x-axis) and the dependent variable
is plotted on the vertical axis (y-axis).
3. Determine the range of the independent variable to be
plotted.
4. 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.

39. Rules for Good Graphing
Rules for Good Graphing on Paper:
5. Number and label the horizontal axis. The label
should include units.
6. Repeat steps 2. through 4. for the dependent variable.
7. Plot the data points on the graph.
8. 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.
9. Give the graph a title that clearly tells what the graph
represents (y vs. x values).

40. Rules for Good Graphing
Rules for Good Graphing on the Computer:
1. From the insert menu on the Microsoft word program
choose insert chart.
2. Identify the independent and dependent variables in your
data.
a. The independent variable is plotted on the horizontal
axis (x-axis) and the dependent variable is plotted on
the vertical axis (y-axis).
3. Insert data in the excel window that opens. Be sure to
pay attention to the excel column vs. graph axes location.
4. Through the toolbox menu, give the graph a title that
clearly tells what the graph represents. (y vs. x variable).
5. Through the toolbox menu, give the axes in the graph
labels that include units.

41. Representing Data
Linear relationship – variables are
proportionally related
• Line of best-fit is a straight line but is
not perfectly horizontal or vertical.

42. Representing Data
Slope – is equal to the change in y
divided by the change in x
• Rise/run
• Δy/Δx

43. 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.

44. 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

45. Representing Data
Model – is a visual, verbal or
mathematical explanation of
experimental data.
• Example

46. Practice Problems
• No homework
• End 1:4

47. 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

48. Scientific Method and
Research
Scientific Method – is a systematic
approach and organized process used
in scientific study to do research
• Observation
• Hypothesis
• Experiments
• Conclusion

49. 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

50. Scientific Method
• Hypothesis – is a tentative
explanation for what has been
observed.

51. 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.

52. Scientific Method
• Conclusion – is a judgment
based on the information
obtained.

53. Scientific Method

54. 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.

55. 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

56. Practice Problems
• CALM: 1:5

57. What is data?

58. What can data tell us?

59. THE END