Professional data needs numerical and description as well as graphical presentation.

1. 31 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
CHAPTER
3
[Graphical Presentation]
Subtopics:-
[3.1] [Organizing and Graphing Qualitative Data]
[3.2] [Organizing and Graphing Grouped Data]
[Learning Objectives]
 [Recognizing Charts For Quantitative Data]
 [Understanding The Principles Of Proper
Graphical Data Presentation]
 [Histogram]
 [Polygon]
 [Cumulative Polygon]

2. 32 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.1] [Organizing and Graphing Qualitative Data]
[A graphical representation is a visual display of data and statistical1 results. It is more
often and effective than presenting data in tabular form. There are different types of
graphical representation which is used depends on the nature of the data. Grade One
Company in the future may be probably to be recommended to provide measurement
analysis as shown in the X2 statistics ((F Lai, M Griffin, BJ Babin) (2009), Journal Of Business
Research, Elsiever, Vol 62, Issue 10, October 2009, Pages 980-986, Cited by 593)].
[3.1.1] [Understanding Of Graphic Integrated Statistical Packages Communication]
[The understanding of graphic integrated statistical packages communication using the
typography graphic communication is one of the conveyance of ideas information
culture2 which is associated with visual communication through two dimensional images
inclusive corporate context in relations with the company policy stress sensitivity was a
latest variables. The “Intercultural Sensitivity Development Model (IDSIM3)” employed
parametric statistics to generate the parametric assumption that could be significant
towards the change of attractive packaging of :-]
[Colour4 Images]
[Electronic56 resources]
[Illustration]
[Graphic Design]
[Drawing]
[Signboards]
[Attributes7]
[While graphic elements are a strong visual means of, overusing them adds visual clutter
and reduces the space available on a surface. They should be used sparingly. A design
trend in Microsoft Windows is a simpler, cleaner appearance by eliminating unnecessary
1 G Gay, Education and Urban Society Journal (1993)”Building Cultural Bridges: A Bold Proposal For Tender
Education”; RM Paige, Applied Cross Cultural Psychology (1990), Cited by 314 ; F Trompenaars, C Hampden
Turner (2011) “Riding The Waves Of Culture : Understanding Diversity In Global Business”; Cited By 10,345; J R
Betancourt (2003), Academic Medicine Journals “Cross Cultural Medical Education : Conceptual
Approaches and Frameworks For Evaluation, Cited by 481.
2 JJ Dahlggard, S M Dahlgaard Park – The TQM Imagine (2006) Emerald Sight.com Journal, “Lean Production,
Six Sigma Quality, TQM and Company Culture”.
3 MJ Bennett (1998) “Developmental Model Of Intercultural Sensitivity”, Wiley Online Library.
4 F Lai, M Griffin, BJ Babin, Journal Of Business Research (2009), Elsevier, Vol 62, Issue 10, October (2009),
Pages 980-986.
5 L Wilkinson (1992) “SYSTAT For Windows Statistics, Graphics, Data, Getting Started, Versions 5”, Cited By
9130; TC Ozawa, S J Kang, Journal Of Applied Crystallography (2004), “Balls & Sticks Easy To Use Structure
Visualization and Animation Program”.
6ST Kerr, Information Design Journal, (1984), “Learning To Use Electronic Test : An Agenda For Research Or
Typography, Graphics and Interpersonal Navigation”, Cited By 18.
7 Hue, White, Alex “The Elements of Graphic Design” New York NY Press” pp 81-105 ISBN01781-58115-762-8.

3. 33 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
graphics and lines. For example, according to ((R E Horn) (1999, )Information Design
Journal “Information Design Emergence Of A New Profession : Typography Graphic
Presentation”, Cited by 224, “When I was a CEO of an information design consulting company I
often asked documentation and training IT Information design consulting company often asked
documentation and training. There are business graphics and statistical packages advertising that
the charts words and images are tightly integrated in most business”) ideology8 as a new screen
design which may hypertext to others virtually became extinct handwriting styles for business
advocate.]
Figure 3.1 : Typography and Mathematics Relationships Towards New Trend Presentation
8 C Kostelnick (2004) Defining Visual Rhetorics Journal; “Melting Pot Ideology, Modernist Aesthetics And The
Emergence Of Graphical Conventions : The Statistical Atlases Of The United States (1874-1925).

4. 34 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
3.2 [Organizing and Graphing Grouped Data]
Figure 3.2 : Integrative Statistical Communication Data9
[In order to organize the graphical illustration, there is a need to establish a cross cultural
perspective from universities, antecedents and the statistical quality may control the
consequences of positive (+) or negative (-) relationship.]
[Moreover, without undertaking a cross cultural study analysing the surrounding society
relating to (PEST) political, environment, social and technology impacts with quality10
values business relationship may interrelate the organizational business performance
relationships.]
[Although multiracial ethnic background, with the availability of the graphical integrative
statistical with e-commerce technology settings, it is shown another alternative defensive
strategies. While, the educational institutions are very susceptible to the opinions of
business and industry.]
[The academic medicine journal refers to (J R Betancourt, (2003) “Cross Cultural Medical
Education: Conceptual Approaches and Frameworks For Evaluation”, The Hispanic
education using statistical portrait11.]
[Apart of more profitable, it is true that this integrative statistical packages creates prompt
services can be achievable through the maximization of cross cultural12 method analysis
9 www.google.integrativestatisticalcommunicationdata.com
10 S R Segarra Moliner, MA Moliner Tena, (2013) Marketing Emerald Insight Research Gate net Journal,
“Relationship Quality In Business To Business: A Cross Cultural Perspective From Universities”.
11 G Gay (1993) Education and Urban Society Journal, “Building Cultural Bridges : A Bold Proposal For
Teacher Education”.

5. 35 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
effects especially perceived from the service quality dimensions on internal stakeholders
(students, employees, lecturer, Top Management) or (customers, disabled, public, VIP)
external stakeholders’ satisfaction that may establish the cross cultural psychological
educational improvement13 achievement strategies.]
3.2.1 [ Bar, Histogram, Line, Pie Graphical Chart]
[A graph made of bars whose heights represent the frequencies of respective categories
is called a bar graph. The bar graphs and histograms have been used formulation for
graphical presentation for numerous hundreds of years.]
Table 3.4: The Pie Is Divided Into Different Portions That Represent the Percentages of the
Population or Sample Belonging To Different Categories
[As we know, a circle contains 360 degrees. To construct a pie chart, we multiply 360 by
the relative frequency for each category to obtain the degree measure or size of the
angle for the corresponding category.]
12 N Kassim, N Asiah Abdullah, (2010), Asia Pacific Journal Of Marketing, “The Effect Of Perceived Service
Quality Dimensions On Customer Satisfaction, Trust and Loyalty In e-Commerce Settings : A Cross Cultural
Analysis”, Cited By 418.
13 N Kassim, N Asiah Abdullah, (2010), Asia Pacific Journal Of Marketing emerald sight com, “The Effect Of
Perceived Service Quality Dimensions On Customer Satisfaction, Trust and Loyalty In e-Commerce Settings :
A Cross Cultural Analysis; F Lai, M Griffin, B J Babin, (2009), Journal Of Business Research, Elsiever, Vol 62,
Issue 10, October 2009, Pages 980-986; G Gay (1993), Education and Urban Society Journal sagepub.com,
“Building Cultural Bridges: A Bold Proposal For Teacher Education, Cited by 314; RM Paige (1990) Applied
Cross Cultural Psychology, “Cross Cultural Psychological Perspectives”; D Valentine, RS Cheney,(2001)
Business Communication Journal sagepub.com, “Intercultural Business Communication, International
Students and Experiential Learning; F Trompenaars, C Hampden Turner (2011), ”Riding The Waves Of Culture :
Understanding Diversity In Global Business.”
Formula to find degree of each
category:
Percentage = (Frequency / Total
Frequency) x 100
Degree =

6. 36 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.2] [Frequency Polygon]
[A polygon is another device that can be used to present quantitative data in graphic
form. This is the same as marking the midpoint at the top of each bar in a histogram. The
resulting line graph is called a frequency polygon or simply a polygon. In a frequency
polygon, the class midpoints are connected with a line segment.]
Table 3.5: The Resulting Line Graph Representing the Frequency Polygon

7. 37 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
Rental Rates Number Of Apartments Midpoints
350-379 3 364.5
380-409 8 394.5
410-439 10 424.5
440-469 13 454.5
470-499 33 484.5
500-529 40 5144.5
530-559 35 544.5
560-589 30 574.5
590-619 16 604.5
620-649 12 634.5
Total ∑f=200
0
5
10
15
364.5 394.5 424.5 454.5
Frequency
Midpoint
Table 3.6 : The Resulting Line Point Graph Chart Representing The Frequency
Polygon
Number of
apartment
MONTHLY APARTMENT RENTAL RATES
0
5
10
15
20
25
30
35
40
45
MIDPOINT
FREQUENCY

8. 38 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[While according to William Playfair and Karl Pearson are commonly cited of the bar
graph (Spence (2005), Spence, I (2005), “No Humble Pie: The Origins and Usage Of A
Statistical Chart, “Journal of Educational and Behavioral Statistics, 30, 353-368, SAGE”.
According to Naomi Robbins January 4, 2012, Forbes Contributions explains that a
histogram is not a bar chart. Histograms are used to show distribution of variables. Bar
chart is used to compare variables. According to Naomi Robbins January 4, 2012, Forbes
Contributions explains that a histogram is not a bar chart. Histograms are used to show
distribution of variables. Bar chart is used to compare variables.]
Figure 3.1 : A Histogram Having The Distribution Of
Times Visitors
Figure 3.2 : A Bar Chart Comparing The
Median Times Visitors

9. 39 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[A chart, also called a graph, is a graphical
representation of data, in which "the data is
represented by symbols, such as bars in a bar
chart, lines in a line chart, or slices in a pie
chart". A circle divided into portions that
represent the relative frequencies or
percentages of a population or a sample
belonging to different categories is called a
pie chart.
Table 3.3: Different Categories of Pie Charts
Organizing and
graphing
qualitative
data
Bar charts
Organizing and
graphing
qualitative data
Pie chart
Organizing and
graphing qualitative
data
Histogram charts.
Portray a frequency
distribution in a
histogram, frequency
polygon and
cumulative frequency
polygon
Develop
Charts
For
qualitative
quantitative
data
Figure 3.5 : Examples Of Graphical Presentation For Information, Education, Business
Documentation In Association Of Statistical Packages Advertising The Words and Images Are
Tightly Integrated In Most Business, Graphic Sounds Elements and Education14 As A Cross Selling.
14S Yurtkuran (2013) “Use Of The Semantics Of Typography In Architectural Design Education”.

10. 40 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.3] [Organizing Graphical Illustration Applying Basic Terms Methodology Variables]
[3.2.3.1] [Basic Terms]
[On completion of this course, students should be able to differentiate quantitative and
qualitative data as well as the bigger picture of statistics which related to the below
mentioned examples:-]
[3.2.3.2] [Quantitative Variables Research Methodology Terms]
[Quantitative research is the systematic empirical investigation of observable phenomena
via inferential statistical techniques application. This is a systematic empirical investigation
that uses mathematical formula or computational techniques. The main objective of
quantitative research is to develop graphical presentation by employing some
phenomena having a significant probability related values of :-]
1. Research Problems Logical Reasoning Selection On The Research
Topic or Title
2. Research Objectives Logical Reasoning Selection On The Research
Topic or Title
3. Research Hypothesis Introducing The Research Subjects or Title

11. 41 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
4. Research Literature Collection Of Journal Theories Application On
Validating The Statistical Concept Data
5. Research Methodology Application On Mathematical Models
[Quantitative data can be classified into categories or classes. They can best be
presented in the form of Frequency distribution, bar chart, pie chart and contingency
table. ]
[3.3.3.1b] [Qualitative Variable Research Methodology Terms]
[According to Wikipedia, explained that qualitative research is applying some descriptive
statistics. Technique to obtain more valuable information that can be explained uses
various academic disciplines Including psychological sense, emotional intelligence,
observational consumers’ experiences. Examination in the fields of sociology, social
sciences and pure statistical science method example of:-]
A. [Research Question Inquiry that may employ a different academic discipline]
B. [In depth Knowledge, interview, and understanding technological graphic
presentation skills and Public Speaking Skills Through Mini Research
Conference
C. Assessment by Top Management]
D. [Knowledge of business research and statistics mathematical tools]
[Provide a working knowledge of the mathematical tools, language,
and thought processes used by statisticians.]
[Provide a lasting security of their ability to discuss comfortably any
simple statistical task in the normal course of their work.]
[Recognize the relevance and importance of statistical methods that
may be applied to (PEST) Political, Environment, Social and
Technological as well as for economics, mathematical, psychology,
business and health science.]
[Choose and apply appropriate graphical and numerical tools for
organizing, describing, and exploring data.]
[Adopting new body knowledge and confidence accuracy to make
an effective and efficient decision analysis presentation especially
under such condition of imperfect information analysis and uncertainty
business performance.]

12. 42 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.3.3] [Research Methodology Measurement Based On Categorical Data Level
Application on Graphical Illustration Integrative Statistical Excel Microsoft 2007
Communication Data]
[There are two types of categorical data which illustrates the business research statistics
methodology as follows: -]
[3.4.1] [Nominal Categorical Data]
[3.4.2] [Ordinal Categorical Data]
[3.2.3.3a] [Nominal Data Level]
[The nominal level data can be categorical data that lack an ordering scheme.]
[3.2.3.3b] [Ordinal Data Level]
[The ordinal level data are categorical data that lack an ordering scheme; ordinal level
data are which having an ordering scheme whether one value is better or higher than
another value.]

13. 43 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4] [Business Research Statistical Measurement Based On Population Sampling]
[The Chapter One complete report is requiring the researchers or statistics students to
explain the necessary details as in the Table 1, what is their title or subject, objectives,
problem statement that attract their attention to explore further on their case study
business research statistics to determine their quality analytical work which carries almost
5% - 20% for their carry marks grading assessment.]
[3.2.4.1] [Population Data Sampling]
Table 3.7: Example of Business Research Statistics Variables: Population Data Sampling
[Population is needed to be recognized by the researcher which can be unbiased and
can be generalized result in a larger population. On the other hand, statistics can be
reliable information if inquires deeply into specific experiences with the intention of
describing and exploring meaning of the research area describing about the whole
population through descriptive statistics text, narrative visual aid data or by developing
awareness theme to that particular set of participants or population. Another hand, if it
uses the research questionnaires design application on the quantitative data variables
which must be displayed in the form of :
Dependent Variables Data
Independent Variables Data
Numerical Values Data
Inferential Statistics Techniques
Graphical Data Percentages Figures Data

14. 44 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[Table 2 refers to page 26 explains the example of business research statistics variables in
association of investigating and selecting WHO, WHAT, WHERE, WHEN and HOW the
population can be a complete collection of people which can analyze their
demographic profile and others usage statistical techniques measurement:-
Age
Elements
Job
Characteristics
Objects
Measurements
[3.2.4.2] [Sample Population Act As Data Sampling]
[In statistics and quantitative research methodology, a data sample is a part of the data
collection that explains WHO, WHAT, WHERE, WHEN all about your population that we are
interested in to investigate which defined its statistical procedure. The elements of a
sample are known as sample points or sampling units or observations. The sample usually
represents a subset of manageable size. Samples are collected and statistics are
calculated from the samples which coming either from descriptive data or inferential
data interrelated with the sample to the whole populations.]
[There are two basic ways to gather data: either through experiment or observational
studies. In an experiment, we apply s treatment and measure its effect. In an
observational study, we simply observe and record data. We select our samples using
probability sampling. There are different types of sampling inclusive:-]
a. [Random Sampling]
b. [Systematic Sampling]
c. [Stratified Sampling]
d. [Cluster Sampling]
e. [Convenience Sampling]

15. 45 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4.3] [Research Objectives]
[The Chapter One is requiring researcher to illustrate their understanding on what appears
on their brain cognitive systems that probably create the following examples of research
objectives:-]
[To study the average weight of newborn baby measurement inclusive statistical
founder responses in New Zealand for year 2012]
[To identify the members and record data after asking their opinions]
[In case study on business research statistical packages will be useful especially
integrating it with an experiment for applied educational knowledge research. This may
cater a sound academic and quality leadership among the researchers and BDM111
statistics for the entire Diploma until Professional level students. It caters a treatment and
measures for testifying their knowledge and cognitive skills of effective and efficient
communication effects performance. Any observational study or experiment in which the
sample is not representative of the population may produce poor data and unreliable
results. The selection of a sample is very important step in a statistical project. This case
study also to visualize the students’ understanding on how to employ the probability
sampling in choosing their sample by applying it with the technology as well as Microsoft
Excel and T1-83 to randomly generate numbers in the computer software packages. The
other sampling is a systematic sampling. This may have a list of numbers of sample such as
customers at a restaurant every day for an entire year and selected every 21st entry; the
data need to be selected on the same day of the week.]

16. 46 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4.4] [Research Methodology Measurement Based On Variables]
[This Chapter Three display the need of Research Methodology for data findings report
which are requiring the researchers or Business Research Statistic BDM111 to be more
capable to understand theoretically and producing the statistic data by adopting the
recognition of research variables as an important valuable product opportunities
motivation element trend for Cosmopoint College achievement for educational
knowledge application.]
[3.2.4] [Research Question 1]
[Which of the following statements are descriptive and which statements make an
inference?]
[3.2.4.1] [Research Findings Answering the Research Question 1 tally with the
research objectives 1(one)]
[In the last four semesters that the instructor taught intermediate algebra, an average
of 15 people passed the class. Answer 1: This statement is descriptive, because we
can verify that the average for these four semesters is 15.]
[3.2.4.2] [Research Question 2:]
[What is descriptive and which statements make an inference statistics data?]
[3.2.4.2a] [Research Findings Answering the Research Questions 2 tally with the
research objectives 2 (two)]
[The instructor will never pass more than 20 people in an intermediate algebra class.
Answer 2: This statement is an inference; it makes a prediction based on the fact that the
instructor did not pass the course in these four semesters.]
[3.2.4.3] [Research Question 3]
[How do you analyze the following statements are descriptive and which statements
make an inference?]

17. 47 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4.3a] [Research Findings Answering the Research Questions 3 tally with the
research objectives]
[Only four people passed one semester because the instructor was in a bad Mood the
entire semester. Answer 3: This statement makes an inference because we are not told
that the instructor was in a bad mood that semester.] [Elements or Members or
Populations]
[3.2.5] [How To Construct A Bar Graph?]
Step 1: We mark the various categories on the horizontal axis
Categories on the horizontal X-axis:
Categorize on the EDUCATION level-
 Diploma
 Degree/bachelor
 Master
Step 2: We mark the frequencies on the vertical axis
a. Categories on the horizontal X-axis:
b. Mark the frequencies on the vertical y- axis
c. Earnings
 RM18000
 RM 36000
 RM 72000
Step 3: Notes that all categories are represented by intervals of the same
width
Step 4: Then we draw one bar for each category such that the height of
the bar represents the frequency of the corresponding category

18. 48 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
Table 3.2: Typical Annual Earnings Based On Education Level

19. 49 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.6 ] [How To Construct A Combo Graph?]
Example On How To Construct Combo Graph Through Microsoft Excel Window
Step 1 : Start Windows
Step 2 : Select Program Excel Spreadsheet Application
Step 3 : Add on the particular variables information to be described
Step 4 : Fill in the lines backgrounds for each variables to illustrate your data relationship
Step 5 : Split off the variables to different page with different type of chart
Step 6 : Transpose the variables with graphical design accordingly
Step 7 : Sort out all the variables with population sampling differences by decoding them
either numerical 1 or using identity card accordingly
Step 8 : Filter out all the errors and select the best graphical design with percentages
values
Table 3.3 : Assessment on Data Information Findings Source Obtained by Contract Lecturer
Namely Lizinis Cassendra Frederick Dony Integrating Graphical Statistic Students’ Grading
Subject of BDM111 For September, 2017, Cosmopoint College, Kota
Kinabalu, Sabah, Malaysia
Year Born Demographic Final Exam Carry Marks Assessments
1997-0611 34% 41%
1997-1215 39% 54%
1998-0920 28% 42%
1998-0215 27% 51%
1998-1219 20% 40%

20. 50 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
Solution For Graphical Integrated Microsoft Office Excel 2007 Windows Applying Linear Statistical
Regression Presentation
Figure 3.6 : The Linear Regression Analysis Relationship Comparison Assessment On
Cosmopoint, Kota Kinabalu, Sabah, Malaysia Among The Population Sampling Variables
Characteristics Of Students’ Grade Comparison Between Carry Marks 60% and 40% For
September, 2017

21. 51 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[Based on page 43, the Figure 3.6 is to confirm that this chapter 4 is to visualize the Table
3.2 information is quantifying the strength of the linear relationship between a pair of
variables. Whereas the regression also having a positive (0.416) and negative15 (-0.04x)
close to 1.]
[This indicates that there is a strong linear statistical relationship for final exam grade
assessment in blue line chart coding narrowing down shown that most of the students
unable to adopt and memorize the statistical knowledge.]
[However, both findings indicates that Cosmopoint College education policy is providing
new opportunity for students to obtain better carry marks 60% (sixty percentage) to
entitled them having an excellent grade for Statistic BDM111.]
[Hence, this chapter 4 is to confirm that the mini research conference, international
research publication skills and knowledge among the students or lecturers on the business
health research statistical concept should be prioritized by the Cosmopoint College
management to produce a significant attention for quality leadership development.]
[Therefore, by obtaining more research grant integration this can increase quality lean
productivity for Cosmopoint College which can be explained by the movement of the
graphical line chart (red color) decoding with statistical excel Microsoft Office Version
Year 2007 Presentation displaying the variable as follows:-]
[Table 3.4 : The Carry Marks and Final Exam Assessment Outcome For Linear Regression
Variables Table Of Graphical BDM 111 Statistical Trend Characteristics Of Cosmopoint
Students’ Grade Comparison For Year September, 2017 Analysis]
[Carry Marks Assessments] [Final Exam Assessments]
[y = - 0.0647 + 0.4707] [y = -0.04x + 0.416]
[R2 = 0.0131] [R2 = 0.7648]
15 V Bewick (2003)(5 November 2003 “Statistics Review 7: Correlation and Regression – NCBI”.

22. 52 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[References]
1. Fundamentals of Business Statistics, 6th Edition, Dennis J. Sweeney, Thomas A.
William, David R. Anderson, Thomson South Western, 2013.
2. Statistics, 3rd Edition, Lau Too Kya, Phang Yook Ngor & Zainudin Awang, Oxford
Fajar, 2015, CICT Library 10KK000001220 HA 35.L3882015.
3. Research Methods For Business : A Skill Building Approach, Fourth Edition, Uma
Sekaran, Southern Illinois University at Carbondale, Copyright 2003, John Wiley &
Sons, Inc, CICT Library, 03KLG000000070 HD30.4.S4352003.
Supplementary References Materials:
1. Basic Statistics for Business & Economics, 8th Edition, Douglas A. Lind, Coastal
Carolina University and The University of Toledo, William G. Marchal, The University of
Toledo, Samuel A. Wathen, Coastal Carolina University, Mc Graw Hill, 2012.
2. Introductory Statistics, Neil A. Weiss, 8th Edition, Pearson, 2011.
3. Basic Statistics For Business & Economics, Eighth Edition, Lind / Marchal / Wathen,
CICT Library 14KK2000000806 HA29.L5632013.