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Aed1222 lesson 4
1. Introduction to Statistics for Built
Environment
Course Code: AED 1222
Compiled by
DEPARTMENT OF ARCHITECTURE AND ENVIRONMENTAL DESIGN (AED)
CENTRE FOR FOUNDATION STUDIES (CFS)
INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA
2. What is/are Data Presentation?
●The data are summarised to enable researchers,
managers and decision-makers to observe
important features of the data, provide insight into
the type of model and analysis that should be
used.
Data Presentation
●Data presentation is an essential step before
further statistical analysis is carried out.
●and help them in making wise and effective
decision.
3. The need for summarizing data
●Summarizing data
Data must be summarized and presented in a
meaningful, readable and understandable ways so
they are useful for decision making and problem
solving.
Common model of presenting data includes :
andTabular SummaryTabular Summary Graphical SummaryGraphical Summary
4. DATA
Qualitative Quantitative
TabularTabular GraphicalGraphical TabularTabular GraphicalGraphical
Frequency
Distribution
Frequency
Distribution
Rel. Freq.
Distribution
Rel. Freq.
Distribution
Bar GraphBar Graph
Pie ChartPie Chart
Frequency
Distribution
Frequency
Distribution
Rel. Freq.
Distribution
Rel. Freq.
Distribution
Cumulative
Freq. Dist.
Cumulative
Freq. Dist.
Histograms &
Polygons
Histograms &
Polygons
Stem and
Leaf Plot
Stem and
Leaf Plot
An overview
OgivesOgives
An overview of common data presentation:
Contingency
Table
Contingency
Table
6. Frequency distribution >> a tabular models of data
summary by showing categories/classes (or variables)
together with the corresponding frequency (or
number) of items in each of several non-overlapping
classes.
Frequency Distribution
Objective >> to provide insights about the data that
cannot be quickly obtained by looking only at the
original data (raw data).
Tabular
Tabular
Examples of Frequency Distribution table:
14. Contingency Tables
What is a Contingency Tables / Cross Tabulation?
• A table showing the responses of subjects to one variable as
a function of another variable.
• A way of summarizing the relationship between variables.
• A table of frequencies classified according to the values of
two variables or more.
• In statistics, contingency tables are used to record and
analyze the relationship between two or more variables,
most usually categorical variables. It may be enhanced by
including the percentages that fall into each category.
Tabular
Tabular
15. ●When a population/sample is classified according to two
variables it is said to have been 'cross-classified' or subjected to
a two-way classification.
Suppose that we have two variables, Gender (male or female)
and handedness (right- or left-handed). We observe the values
of both variables in a random sample of 100 people. Then a
contingency table can be used to express the relationship
between these two variables, as follows:
Contingency tables cont.
Examples of Contingency Table:
16. ●The figures in the right-hand column and the bottom row are
called marginal totals and the figure in the bottom right-hand
corner is the grand total.
●If the proportions of individuals in the different columns
varies between rows (and, therefore, vice versa) we say that
the table shows contingency between the two variables. If
there is no contingency, we say that the two variables are
independent (i.e. there is no relationship between them).
Contingency tables cont.
17. ●The example in the previous slide is for the simplest kind of
contingency table, in which each variable has only two levels;
this is called a 2 x 2 contingency table.
●In principle, any number of rows and columns may be used.
Contingency tables cont.
18. Contingency tables cont.
What is the relationship between the factors gender and presence of tumor?
What effect does a kid's age have on the
color she/he likes?
29. Example of Pie Chart:
AED 1016 Graphic Communication 1
Ex 1 6%
Ex 2 6%
Ex 3 6%
Ex 4 10%
Ex 5 10%
Ex 6 10%
Ex 7 10%
Ex 8 10%
Sketch Task 16%
Sketchbook 4%
Portfolio 10% LEGEND
Pie Charts cont.
Graphical
Graphical
Breakdown of marks
31. Try this exercise!
Conduct a survey of the number of siblings for each
student in your group has.
1. What is the range of the data?
2. Identify the upper and lower halves of the data.
3. What percentage of the students have from 2 to 3 siblings?
4. What percentage of the students have fewer than 4 siblings?
5. How many students had up to 5 siblings?
Answer the following questions:
1. Arrange the obtained raw data in an ascending array.
2. Group the data and create a frequency table.
3. Add to it a cumulative frequency column, a relative frequency column
and a cumulative relative frequency column.
Notas del editor
Updated Version 02/11/2011
The table allows us to see at a glance that the proportion of men who are right-handed is about the same as the proportion of women who are right-handed although the proportions are not identical.
There may also be more than two variables, but higher order contingency tables are difficult to represent on paper. The relation between ordinal variables , or between ordinal and categorical variables, may also be represented in contingency tables, although such a practice is rare.
Males are more likely to develop a tumor than females… The majority of kids like RED at the age of 4, however, their color preference shifts gradually as they grow to BLUE, which is the least favorite color for kids 4 and 8 years of age. YELLOW is not a favorite among kids regardless of their age.
Raw data can be collected from students and written on the board. Then they can be arranged in an ascending array, and then grouped. A suggested grouping is: Less than 2, 2-3, 4-5, more than 5. The answers to questions 1 & 2 are derived from the array. The answer to questions 3, 4 & 5 are derived from the frequency table.