This document outlines topics in writing and analytical resources including dimensions and units, graphing, plotting data, reporting data in text or tables, and representing random error. It discusses choosing appropriate units and expressing the dimensions of quantities. Graphing techniques like selecting plot types, scales, and legends are covered. The purpose of plotting data and conditions where plotting is not needed are addressed. Methods for writing data numerically or in tables are described. Random error and use of error bars to indicate uncertainty are also summarized.

1. Lecture 10
Writing and Analytical
Resources
Abdisalam Issa-Salwe
Taibah University
College of Computer Science & Engineering
Computer Science Department
Outline
1. Dimensions and units
2. Graphing
3. Plot
4. Reporting data in text or tables
5. Random Error
2
1

2. Dimensions and units
We usually consider quantities like mass,
length, time, and perhaps charge and
temperature, as fundamental dimensions.
We then express the dimensions of other
quantities like speed, which is length/time,
in terms of the basic set.
Every quantity which is not explicitly
dimensionless, like a pure number, has
characteristic dimensions which are not
affected by the way we measure it.
3
Dimensions and units (cont…)
Units give the magnitude of some
dimension relative to an arbitrary standard.
For example, when we say that a person is
six feet tall, we mean that person is six times
as long as an object whose length is defined
to be one foot.
In contrast to dimensions, of which only a
few are needed, there is a multitude of
units for measuring most quantities.
4
2

3. Dimensions and units (cont…)
Dimensionless quantities should be easier,
in that they do not have units at all, but in
some ways they are more complicated.
Some examples: Ratios, Angles,
Pressure,
5
Graphing
To be useful, the results of a scientific
investigation or technical project must be
communicated to others in the form of an oral
presentation, technical report, journal article or
monograph.
Effective communication often requires figures,
such as photographs, drawings, or graphs, in
addition to words and equations.
When choosing the type of figure to use, start
with the type of data you have collected or
intend to collect, and the type of information that
you intend to convey.
6
3

4. Graphing (cont..)
If a graph is appropriate, you need to make conscious
decisions regarding several features in order to maximize its
effectiveness.
Decide exactly what type of relationship you want to depict
- what would be the purpose of the figure?
Examine the data, identify the independent and
dependent variables and the units Select a plot type
Select an appropriate scale for each axis and plot the data
Adjust axis proportions to optimize effectiveness of the
figure
Check plot symbols, add a descriptive line and/or error
bars if appropriate Prepare a legend if necessary
Write out and place the caption
If computer graphics are used, check the figure carefully
and remove any features that do not belong
7
Plot
The purpose of plotting scientific data is to
visualize variation or show relationships
between variables, but not all data sets
require a plot.
If there are only one or two points, it is
easy to examine the numbers directly, and
little or nothing is gained by putting them
on a graph
8
4

5. Reporting data in text or tables
Assuming that you have a normal
distribution, a set of data for a single
sample can be written in text or in a table
as mean ± error, which is usually either
the standard deviation or the standard
deviation of the mean (e.g., 9.8 ± 0.02 m/s
2).
9
Random Error
Random error, known also as experimental
error, contributes uncertainty to any
experiment or observation that involves
measurements.
One must take such error into account when
making critical decisions.
When you present data that are based on
uncertain quantities, people who see your
results should have the opportunity to take
random error into account when deciding
whether or not to agree with your conclusions.
10
5

6. Random Error (cont…)
Without an estimate of error, the
implication is that the data are perfect.
Random error plays such an important role
in decision making, it is necessary to
represent such error appropriately in text,
tables, and in figures.
11
Random Error (cont…)
To represent random error, we
commonly use what we call an error
bar, consisting of a vertical line that
extends from the mean value in
proportion to the magnitude of the error.
The most common type of error bar that
you will encounter includes a "cap" that
clearly indicates the end of the bar in each
direction.
12
6

7. References
Introductory Laboratory Courses in
Biochemistry & Cell Biology,
syllabushttp://www.ruf.rice.edu/~bioslabs/b
ios211/index.htm
Abdisalam Issa-Salwe lecture notes,
Taibah University.
13
7