How to Write Chapter 4

Chapter 4 – ANALYSIS, PRESENTATION, AND INERPRETATION OF DATA32
Chapter 4 – ANALYSIS, PRESENTATION, AND INERPRETATION OF DATA

Pamantasan ng Lungsod ng Maynila
Intramuros, Manila
College of Engineering and Technology
Chemical Engineering Department


Pamantasan ng Lungsod ng Maynila
Intramuros, Manila
College of Engineering and Technology
Chemical Engineering Department







HOW TO WRITE CHAPTER 4
Chapter 4 – ANALYSIS, PRESENTATION, AND
INTERPRETATION OF DATA



Submitted by:
Sablan, Anna Angelica M.
Sarsoza, Andriane C.
Supremo, Journel Ann T.
Venturina, Richard Harvey G.


Submitted to:
Engr. Milagros R. Cabangon


01 September 2014


Table of Contents

Analysis 2
Classification of data 3
Quantitative Analysis in Evaluation 5
Arrangement of data or classes of data. 6
Group-derived generalizations 6

PREPARING DATA FOR PRESENTATION 8
How to construct a talligram 8

PRESENTATION OF DATA 11
TEXTUAL PRESENTATION OF DATA 11
TABULAR PRESENTATION OF DATA 12
GRAPHICAL PRESENTATION OF DATA 19

REFERENCES 31








Analysis

Analysis is the process of breaking up the whole study into its constituent parts of categories according to the specific questions under the statement of the problem. This is to bring out into focus the essential features of the study. Analysis usually precedes presentation.
In most social research the data analysis involves three major steps, done in roughly this order:
Cleaning and organizing the data for analysis (Data Preparation)
Describing the data (Descriptive Statistics)
Testing Hypotheses and Models (Inferential Statistics)
Data Preparation
 involves checking or logging the data in; checking the data for accuracy; entering the data into the computer; transforming the data; and developing and documenting a database structure that integrates the various measures.
Descriptive Statistics
used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data. With descriptive statistics you are simply describing what is, what the data shows.
Inferential Statistics
investigate questions, models and hypotheses. In many cases, the conclusions from inferential statistics extend beyond the immediate data alone. We use inferential statistics to make inferences from our data to more general conditions.


Hence with the use of Data Analysis Procedure, you can
convert data into information and knowledge, and
explore the relationship between variables.

Understanding of the data analysis procedures will help you to
appreciate the meaning of the scientific method, hypotheses testing and statistical significance in relation to research questions
realise the importance of good research design when investigating research questions
have knowledge of a range of inferential statistics and their applicability and limitations in the context of your research
be able to devise, implement and report accurately a small quantitative research project
be capable of identifying the data analysis procedures relevant to your research project
show an understanding of the strengths and limitations of the selected quantitative and/or qualitative research project
demonstrate the ability to use word processing, project planning and statistical computer packages in the context of a quantitative research project and report
be adept of working effectively alone or with others to solve a research question/ problem quantitatively.

Classification of data

Classification is grouping together data with similar characteristics. Classification is a part of analysis. The bases of classification are the following:
Qualitative
Qualitative data can be arranged into categories that are not numerical. These categories can be physical traits, gender, colors or anything that does not have a number associated to it.
Qualitative data is sometimes referred to as categorical data.
The most common analysis of qualitative data is observer impression. That is, expert or bystander observers examine the data, interpret it via forming an impression and report their impression in a structured and sometimes quantitative form.
Qualitative data is extremely varied in nature. It includes virtually any information that can be captured that is not numerical in nature. Here are some of the major categories or types:
In-Depth Interviews
In-Depth Interviews include both individual interviews as well as "group" interviews. The data can be recorded in a wide variety of ways including stenography, audio recording, video recording or written notes
Direct Observation
It differs from interviewing in that the observer does not actively query the respondent. It can include everything from field research where one lives in another context or culture for a period of time to photographs that illustrate some aspect of the phenomenon. The data can be recorded in many of the same ways as interviews and through pictures, photos or drawings.
Written Documents
Usually this refers to existing documents (as opposed transcripts of interviews conducted for the research). It can include newspapers, magazines, books, websites, memos, transcripts of conversations, annual reports, and so on. Usually written documents are analyzed with some form of content analysis

Quantitative
Quantitative data are anything that can be expressed as a number, or quantified. Examples of quantitative data are scores on achievement tests, number of hours of study, or weight of a subject. These data may be represented by ordinal, interval or ratio scales and lends themselves to most statistical manipulation.
refers to the systematic empirical investigation of social phenomena via statistical, mathematical or numerical data or computational techniques
The objective of quantitative research is to develop and employ mathematical models, theories and/or hypotheses pertaining to phenomena.

Statistics is the most widely used branch of mathematics in quantitative research outside of the physical sciences, and also finds applications within the physical sciences, such as in statistical mechanics. Statistical methods are used extensively within fields such as economics, social sciences and biology.
. Using quantitative methods, it is possible to give precise and testable expression to qualitative ideas. This combination of quantitative and qualitative data gathering is often referred to as mixed-methods research.

Quantitative Analysis in Evaluation

Before you begin your analysis, you must identify the level of measurement associated with the quantitative data. The level of measurement can influence the type of analysis you can use. There are four levels of measurement:
Nominal data – data has no logical; data is basic classification data
Ordinal data – data has a logical order, but the differences between values are not constant
Interval data – data is continuous and has a logical order, data has standardized differences between values, but no natural zero
Ratio data – data is continuous, ordered, has standardized differences between values, and a natural zero

Geographical
Data may be classified according to their location. For instance, the schools in the secondary level in Province A may be grouped by district.
It uses techniques from spatial analysis, but also encompasses geographical activities such as the defining and naming of geographical regions for statistical purposes.

Chronological
In this, data are classified according to the order of their occurrence
Cross-classification- this is further classifying a group of data into subclasses. This is breaking up or dividing a big class into smaller classes.

Arrangement of data or classes of data.
The bases of arrangement of data or groups of data are the same as those of classification.
Qualitative
Data may be arranged alphabetically, or from the biggest class as from phylum to specie in classifying animals or vice versa, or listing the biggest country to the smallest one or vice versa, or from most important to least important, or vice versa, etc. Ranking of students according to brightness is qualitative arrangement.
Quantitative
This is arranging data according to their numerical magnitudes, from the greatest to the smallest number or vice versa. Schools may be arranged according to their population, from most populated to the least populated, and so with countries, provinces, cities and towns.
Geographical
Data may be arranged according to their geographical location or according to direction. Data from the Ilocos Region may be listed from north to south by province as Ilocos Norte, ABra, Ilocos Sur, and La union
Chronological
This is listing down data that occurred first and last those occurred last according to the purpose of presentation. This is especially true in historical research. For instance, data during the Spanish period should be treated first before the data during the America period.

Group-derived generalizations

One of the main purposes of analyzing research data is to from inferences, interpretations, conclusions, and/or generalizations from the collection data. In so doing the researcher should be guided by the following discussions about group-derived generalizations.
Group-generalizations are applicable to all kinds of research, be they social, science or natural science research. There are several types of these but are discussed under four categories by Good and Scates.

Generally, only proportional predictions can be made. One of type of generalization is that which is expressed in terms of proportion of the cases in a group, often in the form of probability. When this type is used, we do not have enough information about individual cases to make predictions for them, but we can nevertheless predict for a group of future observations
The average can be made to represent the whole group. A second type of ground-derived generalization results from using the average as a representation of the group of cases and offering it as a typical result. This is ignoring the individuals comprising the group or the variation existing in the group or the variation existing in the group but the average represents the whole group.
Full-frequency distribution reveals characteristics of a group. As a third type of knowledge growing out of the study of groups, we have the full-frequency distribution- the most characteristic device, perhaps of all statistical work. Perhaps too, the most inferential characteristics of frequency distribution are shape and spread. Frequency distributions carry the implication of probability.
A group itself generates new qualities, characteristics, properties, or aspects not present in individual cases.
Other group properties that exist only in groups are cooperation, opposition, organization, specialization, leadership, teaching, morale, reciprocal sharing of emotions, etc. which vanish in individual cases.
Two more categories of generalization may be added at this point.
Generalization can also be made about an individual case. For instance, a high school graduating student is declared valedictorian of his class. We can generalize that, that student is the brightest in his class. This is group-derived generalization because it cannot be made if there is only one student.
In certain cases, predictions on individual cases can be made. It has been mentioned earlier that, generally, only proportional predictions.



PREPARING DATA FOR PRESENTATION

Before presenting data in accepted forms, especially in presenting them in the form of statistical tables, they have to be tallied first in a tabulation diagram which may be called talligram, a contraction of tally and diagram. The individual responses to a questionnaire or interview schedule have to be tallied one by one.
How to construct a talligram
A talligram may be constructed as follows:
Determine the classes and their respective subclasses along with their respective numbers. For instance, in the study about the relationship between the perceived stress levels of 4th-year standing Engineering students of Pamantasan ng Lungsod ng Maynila and their academic performances, suppose there are eleven stress factors (stressors) contributing to the level of stress perceived by the student during the previous semester such as Broken Family, Bullying, Course Load, Environment, Examination, Health Problems, Heavy Workload, Long Travel Time, Relationship and Traffic. The subclass used is the number of students that perceived stress under the said stressors. The classes and their subclasses are arranged alphabetically.

Make rows for the classes by drawing horizontal lines with appropriate spaces between the lines and the number of the rows should be two more than the number of classes. In the previous example, there should be, supposedly, thirteen rows, since there are eleven classes (the eleven stressors mentioned in the previous step). The uppermost row is for the subclass (number of students that perceived stress under the said stressors). The next eleven rows are for the classes. The bottom row is for the totals, but for the tallying of the data gathered, there is no need for additional bottom row since the data to be tallied is from a multiple response questionnaire and the grand total of these data is meaningless. Therefore, only twelve rows are necessary for the talligram construction.

Make columns for the subclasses by drawing vertical lines with appropriate spaces between the lines and the number of columns should be two more than the number of subclasses. For the given example, since there is a single subclass, there should be three columns. The leftmost column is for the labels of the of the class rows, the rightmost column is for the totals, and the middle column is for the subclass.

Stressors
Number of Students that Perceived stress under the stressor
Total
Broken Family


Bullying


Course Load


Environment


Examination


Financial Difficulties


Health Problems


Heavy workload


Long Travel Time


Relationship


Traffic




How to tally data (responses) gathered through a questionnaire.

Tallying responses to a questionnaire in a talligram follows. Suppose a multiple-response questionnaire gives the following data.

Student A put a checkmark on the following items (stressors) in the questionnaire that he thought contributes to the stress level he perceived during the previous semester: Course load, Examination, Environment, Financial difficulties and Health Problems. Enter a tally in the cells which are the intersections of the 2nd column and the Course Load row, 2nd column and the Examination row, 2nd column and the Environment row, 2nd column and the Financial Difficulties row and 2nd column and the Health Problems row.

Student B put a checkmark only on the item Broken Family in the questionnaire. Enter a tally in the cell which is the intersection of the 2nd column and the Broken Family row.

Continue the process until all the data gathered are entered.

Stressors
Number of Students that Perceived stress under the stressor
Total
Broken Family
11
2
Bullying
11
2
Course Load
11111 – 11111 – 11
12
Environment
11111 – 11111
10
Examination
11111 – 11111- 111
13
Financial Difficulties
11111 – 1
6
Health Problems
111
3
Heavy workload
11111 – 11111
10
Long Travel Time
11111 – 1
6
Relationship
11
2
Traffic
11111 - 1111
9

Stress Factors Perceived by 4th-Year Standing Engineering Students of PLM During the Previous Semester, A.Y. 2013-2014

The tables presented above can now be converted into a statistical table for data presentation. Generally, all quantified data are tallied first in talligram which are then converted into statistical tables for data presentation using Hindu-Arabic numerals in the cells in place of tallies.





Presentation of Data

Presentation is the process of organizing data into logical, sequential, and meaningful categories and classifications to make them amenable to study and interpretation. Analysis and presentation put data into proper order and in categories reducing them into forms that are intelligible and interpretable so that the relationships between the research specific questions and their intended answers can be established. There are three ways of presenting data: textual, tabular and graphical.

TEXTUAL PRESENTATION OF DATA

Textual presentation uses statements with numerals or numbers to describe data. The main aims of textual presentation are to focus attention to some important data and to supplement tabular presentation.
The disadvantage, especially if it is too long, is that it is boring to read and the reader may not even be able to grasp the quantitative relationships of the data presented. The reader may even skip some statements.
Example: The following refers to the stress factors that contributed to the perceived stress of the students during the previous semester during the previous semester.
Stressors
Number of Students that Perceived stress under the stressor, f
Percentage Distribution
Broken Family
2
12.5%
Bullying
2
12.5%
Course Load
12
75%
Environment
10
62.5%
Examination
13
81.25%
Financial Difficulties
6
37.5%
Health Problems
3
18.75%
Heavy workload
10
62.5%
Long Travel Time
6
37.5%
Relationship
2
12.5%
Traffic
9
56.25%
n = 16; *Percentage distribution = (f/n) x 100%
Percentage Distribution of the Number of Students Experiencing Stress Due to Different Stressors

Of the sixteen 4th-year standing Engineering students of PLM surveyed, two or 12.5 percent have perceived stress due to Broken Family, Bullying and Relationship, three or 18.75 percent due to Health Problems, six or 37.5 percent due to Financial Difficulties and Long Travel Time, nine or 56.25 percent due to Traffic, ten or 62.5 percent due to the Environment and Heavy Workload, twelve or 75 percent due to Course Load and thirteen or 81.25 percent have said that they were stressed due to the Examinations.

TABULAR PRESENTATION OF DATA

When presenting ideas that include references to data, it can be helpful to make the point using a table or graph. Text alone should not be used to convey more than three or four numbers. Sets of numerical results should usually be presented as tables or pictures rather than included in the text. Well presented tables and graphs can concisely summarize information which would be difficult to describe in words alone.
On the other hand, poorly presented tables and graphs can be confusing or irrelevant. While they can be powerful methods, they also have the potential to ruin a presentation if they convey the wrong message or they confuse the audience. Appropriate use of tables and graphs is one way to enhance the message you are delivering. It is crucial to remember that when using a table or graph the associated text should describe what the data reveal about the topic; you should not need to describe the information again in words.
Tables and graphs should, ideally, be self-explanatory. The reader should be able to understand them without detailed reference to the text, on the grounds that users may well pick things up from the tables or graphs without reading the whole text. The title should be informative, and rows and columns of tables or axes of graphs should be clearly labeled.
Once data and information are recorded and available at school, descriptive statistics can be produced to summarize the data, to describe the situation, and to identify issues and factors. We can produce descriptive statistics by:
Sorting and re-grouping data;
Transforming raw data into indicators such as percentages, rates, and ratios; and
Presenting the data and indicators in tables, charts, and texts which enable easy analysis, interpretation, and use.
Descriptive statistics also include summary statistics such as averages, range, median, mode, and standard deviation. These summary statistics can help people to understand the nature and characteristics of the data set and the phenomenon, which is important when they are analyzing and interpreting data and indicators in order to understand the situation and to make decisions. More and more, charts and other graphical presentations are produced to present education data and indicators, using statistical and data presentation tools.
Statistical table defined. A statistical table or simply table is defined as a systematic arrangement of related data in which classes of numerical facts or data are given each a row and their subclasses are given each a column in order to present the relationships of the sets or numerical facts or data in a definite, compact, and understandable form or forms. (Calderon, et al, p.210)
The basic structure of a table is a set of columns and rows that contain the data and usually contain either a row or column (or both) of headings that organize the data. When deciding on the size of the table, it is a good idea to keep the six by six guideline in mind. Used in the context of tables, this guideline suggests that a table should try to have no more than six columns and no more than six rows in order to keep the amount of information to a reasonable level. In selecting the size of the table, make sure that the font size of the text in each cell of the table is big enough to be read clearly when displayed.

Advantages of tabular over textual presentation of data. (Calderon, et al, p.210) The advantages of the tabular over the textual presentation of data are:
Statistical tables are concise, and because data are systematically grouped and arranged, explanatory matter is minimal.

Data are more easily read, understood, and compared because of their systematic and logical arrangement into rows and columns. The reader can understand and interpret a great bulk of data rapidly because he can see significant relationships of data at once.

Tables give the whole information even without combining numerals with textual matter. This is so because tables are so constructed that the ideas they convey can be understood even without reading their textual presentation.

The major functional parts of a statistical table. (Bacani, et al, p. 55)
Table Number. Each table should have a number, preferably in Arabic, for reference purposes. This is because only the table numbers are cited. The number is written above the title of the table. Tables are numbered consecutively throughout the thesis report. If there is only one table the number is unnecessary.

Title. The title should tell about the following:
The subject matter that said table deals with;
Where such subject matter is situated, or to what entity or persons it belongs, or from whom the data about such matter were gathered;
When data about such subject matter were gathered or the time period when such data were existent; and
Sometimes how the data about such subject matter are classified.
Usually, however, only the first two elements are mentioned in the title, and occasionally, only the subject matter. Only the beginning letters of the important words in the title are capitalized. If the title contains more than one line, it should be written like an inverted pyramid.
Headnote or Prefatory Note. This is written below the title and it is usually enclosed in parentheses. It explains some things in the table that are not clear.

Stub. The stub contains the stub head and the row labels. The stub head tells what the stub contains, the row labels. Each row label describes the data contained in that row.

Box Head. The box head contains the master caption, the column captions, and the column subcaptions. The master caption describes the column captions and the column captions in turn describe the subcolumn captions.

Main body, field, or text. The main body, field, or text of the table contains all the quantitative and/or proportional information presented in the table in rows and in columns.

Footnote. The footnote which appears immediately below the bottom line of the table explains, qualifies, or clarifies some items in the table which are not readily understandable or are missing. Proper symbols are used to indicate the items that are clarified or explained. The footnote is not necessary if everything in the table is clear and there is nothing to clarify or explain.

Source note. The source note which is generally written below the footnote indicates the origin or source of the data presented in the table. The source note is not necessary if the sources of the data are the respondents to a questionnaire or interview schedule.

Rulings and spacing in tables. (Calderon, et al, p.210) Ruling is done in a table to emphasize or make clear relationships. There are no fixed standard rules to follow in ruling and spacing tables. Emphasis and clarity are the determining factors. However, the following guidelines are generally followed in the construction of tables for a thesis report:
The table number is not separated by line from the title. It is written two spaces above the title.

The title is separated from the rest of the table by a double line placed two spaces below the lowest line of the title.

The stub, master caption, captions, subcaptions, and totals are separated from one another by vertical and horizontal lines.

The rows and columns are not separated by lines. Major groups, however, are separated by single lines. For purposes of clarity, rows are separated by a double space and the columns are separated by as wide a space as possible.

Both ends of the table are unruled
.
There is always a line, either single or double, at the bottom of the table.

Textual Presentation of Tabular Data
Tables and charts are often accompanied by descriptive text that highlights the findings, patterns, issues and implications of the data. Textual descriptions and discussions play a crucial role in almost every kind of data presentation, especially for people who are not familiar with data tables and charts. Many people even prefer plain textual descriptions to tables and charts, or at least need some clear and simple explanations to help them understand the data and important points presented in the tables and charts.


Basic rules

One of the important functions of text is to provide a verbal description of the data in tables and charts. We should remember five basic rules when drafting a text to describe a table or chart:

1. Try to capture the readers' interest – While staying within the confines of scientific rigor, the writer should strive to enliven the text by highlighting key findings and meanings.

2. Take time to write clearly and succinctly – draft and re-draft to clearly and unambiguously describe the data.

3. Ensure consistency of language and style throughout the report or presentation – Often sections of a single piece are written separately for each table or chart, so a final check to ensure consistency is advisable.

4. Avoid unnecessary repetition – if parts of the report or presentation are written separately, contents get repeated. Review the written text to eliminate unnecessary repetitions and to harmonize the texts.

5. Focus on the main points and minimize unnecessary details – Present the most important information first, and add details only if absolutely necessary.

A verbal summary should simply accompany the table or chart to explain what the data reveal. It should not dwell on issues that are too specific or too detailed. Nor should it repeat what is obvious in a table or chart unless there is a need to emphasize the importance of a certain aspect or limitations of the data. Sometimes, a verbal summary is all that is included in a presentation, particularly when the findings are so simple that any other summarized display like tables and charts are not justified. Or, when numerical or graphical presentations are too complex, it is better to include them separately in the appendices. The following are some additional basic rules:

Keep the summary short – never allow the verbal summary to expand into an itemized account of each entry in the table or chart. Position the summary in the text close to the table or chart to which it refers. Quoting directly the key reference numbers is the best way.

Use 'emotional' descriptions and wording sparingly – Sensational messages can be effective with a non-technical audience, but they can communicate biases or lead to biased interpretations. For example: "Education expenditure per student in China rose by 10 per cent" may be better than: "Education expenditure per student in China shot up by 10 per cent!"

Unless writing specifically for expert readers, avoid using unnecessary technical terms.

Be cautious when attributing causality to a factor – for example, some erratic movements in a data series may be due to changes in definitions or measurement unit, rather than actual changes in the underlying event. Do not jump to conclusions that 'this caused that', unless there is ample evidences to justify it.

Percentage Distribution of the Number of Students Experiencing Stress Due to Different Stressors

Stressors
Number of Students that Perceived stress under the stressor, f
Percentage Distribution
Examination
13
81.25%
Course Load
12
75%
Environment
10
62.5%
Heavy workload
10
62.5%
Traffic
9
56.25%
Financial Difficulties
6
37.5%
Long Travel Time
6
37.5%
Health Problems
3
18.75%
Broken Family
2
12.5%
Bullying
2
12.5%
Relationship
2
12.5%
n = 16; *Percentage distribution = (f/n) x 100%
Of the sixteen 4th-year standing Engineering students of PLM surveyed, two or 12.5 percent have perceived stress due to Broken Family, Bullying and Relationship, three or 18.75 percent due to Health Problems, six or 37.5 percent due to Financial Difficulties and Long Travel Time, nine or 56.25 percent due to Traffic, ten or 62.5 percent due to the Environment and Heavy Workload, twelve or 75 percent due to Course Load and thirteen or 81.25 percent have said that they were stressed due to the Examinations.

GRAPHICAL PRESENTATION OF DATA

Graph
A graph is a chart representing the quantitative changes of a variable itself or in comparison with another variable in a pictorial or diagrammatic form.
The quantitative variations or changes in the data may refer to their qualitative, geographical, or chronological attributes.

Purpose of Graphing. To present the variations, changes, and relationships of data in a way that is appealing, effective, and convincing.

Advantages of the Graphic Method (Bacani, et al., pp. 54-55)
According to Bacani, et al. the following advantages of the graphical method:
It attracts attention more effectively than do tables, and, therefore, is less likely to be overlooked. Readers may skip tables but pause to look at charts.
The use of colors and pictorial diagrams makes a list of figures in business reports more meaningful (also in thesis report).
It gives a comprehensive view of quantitative data. The wandering of a line exerts a more powerful effect in the reader's mind than tabulated data. It shows what is happening and what is likely to take place.
Graphs enable the busy executive of a business concern to grasp the essential facts quickly and without much trouble. Any relation not seen from the figures themselves is easily discovered from the graph. Illustrations, including attractive charts and graphs, are now considered by most businessmen as indispensable accompaniment to good business reports.
Their general usefulness lies in the simplicity they add to the presentation of numerical data.

Limitations of Graphs (Bacani, et al., p.55)
If there are advantages, there are also disadvantages of the graph. Some of these are:
Graphs do not show as much information at a time as do tables.
Graphs do not show data as accurately as the tables do.
Charts require more skill, more time, and more expense to prepare than tables.
Graphs cannot be quoted in the same way as tabulated data.
Graphs can be made only after the data have been tabulated.

Types of Graphs or Charts
Graphs may be classified into the following types:
Bar Graphs
Single Vertical bar graph
Single Horizontal bar graph
Grouped or multiple or composite bar graph
Duo-directional or bilateral bar graph
Histogram
Linear Graphs
Time series or chronological line chart
Composite line chart
Frequency Polygon
Ogive
Band Chart
Hundred percent graphs or charts
Subdivided bar or rectangular bar graph
Circle or Pie graph
Pictograms
Statistical Maps
Ratio charts
Construction of Individual Graphs
Stated herein are the principles to be followed in the construction of individual graphs.
Bar Graph
A bar chart or bar graph is a chart with rectangular bars with lengths proportional to the values that they represent. Each bar is drawn to a height or length equal to the magnitude it represents as indicated in the scale (y-axis). The bars are separated from each other by a space equal to one-half inch the width of a bar. However, there are no fixed rules that govern the construction of graphs and the maker may only be guided aesthetic, proportional, and symmetrical consideration and for convenience.
Comparison in bar graph is linear. It is the length of each bar that determines the magnitude it represents.
Essentials of a Bar Graph
The essential parts of a graph are the following:
Number. Charts or graphs are also numbered for reference purposes. The general practice is to write the number as Figure 1, Figure 2, Figure 3, etc. at the bottom of the graph.
Title. The same principles hold in graphs as in tables. The title is usually written above the graph.
Scale. The scale indicates the length or height unit that represents a certain amount of the variable which is the subject of the graph. The scale enables the reader to interpret the significance of a number of length or height units. Thus, if a length or height units. Thus, if a length or height units. Thus, if a length or height unit is equal to 2, two length or height units equal 4,3 length or height units equal 6, etc. The y-axis represents the scale.
Classification and arrangement. The principles of classification and arrangement are the same in graphs as in tables.
Classes, categories, or time series indicated at the x-axis and the scale units are indicated at the y-axis.
Symmetry of the graph. The whole chart or graph should be about square; otherwise the length should be a little greater than the height. The chart should be placed on the page in such a way that the margins at the left and at the right should be about the same, or or the margin at the left is a little wider.
Footnote. The footnote, if there is any, should be placed immediately below the graph aligned with the left side of the graph.
Source. The source of the data, if there is a any, should be written just below the chart at the lower left immediately below the footnote if there is any, but it should be above the graph number.

Types of Bar Graphs

Single Vertical Graph. The bars are constructed vertically and show magnitude of data, used to depict time series data.



Single Horizontal Graph. The bars are constructed horizontally and are used to compare magnitudes of different categories.


Grouped (Multiple or Composite) Bar Graph. Grouped bar graph is used in comparing two or more categories of a variable; when the groups have common attributes.



Duo-directional or Bilateral Bar Graph. It is used to show data in the form of assets, profits, and positive numbers, liabilities, losses and negative numbers.



Subdivided (Composite) Bar Graph. It is used to show variations or changes of the component parts of a whole and the whole itself.



Histogram. It is composed of bars placed side by side whose heights indicate the magnitudes of classes/categories.




Linear Graphs
Linear graphs are good devices to show variations of values over successive periods of time. Changes in the data are indicated by the linear curves.

Advantages of Linear Graphs or Charts
The advantages of the linear graph or chart are the following:
The curve shows data as a continuous line; hence, it is continuous in its effect.
The wandering line of the curve tells the story. At a glance one can see just what the situation is and what is likely to happen.
Its preparation requires less time and skill.
Construction of Line Graphs
Linear graphs are constructed in much the same way as many of other graphs are. A slight difference lies in the process of locating the intersections of the abscissa representing a class or category of a variable and the ordinate representing the magnitudes of the classes or categories of the variable. The intersections of the abscissa and the ordinate are marked by bold dots and then joined successively by either straight lines or curved lines to show the variations of a variable or the variable to that of another.
Types of Linear Graphs
Time Series Linear Charts (Single Line). Line charts depict the variations of a variable over a period of time. The (x) – Periods of time; (y) – values of the variable.




Time Series Composite or Multilinear Charts. These charts are used when comparisons are made between or among categories of the same variables vs. periods of time.



Frequency Polygon. It is used to graph class or grouped frequency distributions. (x-axis) – Classes; (y-axis) – frequencies of the classes.


The Ogive. The ogive is used to graph cumulative frequencies, either cumulative freq. upward or cumulative freq. downward.



Band Chart. Band Chart is a form of line graph that shows the proportional variations of the parts of a whole vs. period of time.
















One Hundred Per cent Graphs or Charts
One hundred percent graphs or charts show the comparison of the proportional sizes of the component parts that make up the whole, the whole being made equivalent to 100%. It is the percent equivalent of the component parts that are portrayed in the graph. The percent equivalent of each component part is found by dividing it by the total of the component parts and multiplying the result by 100%. There are two types or kinds of 100% charts: a.) the 100% bar or rectangular chart and b.) Pie chart or circle graph. These are to graph budgets, enrolments, sales, etc.

Types of 100% Graphs or Charts

One Hundred Percent Bar Graph/ Rectangular Chart. The bar is erected vertically and the whole height is equivalent to 100%.




Pie Chart. A pie chart is a circular chart divided into sectors, illustrating numerical proportion.


Pictograms
The Pictogram or pictograph is used to portray data by means of pictures or symbols with equivalent values.


Statistical Maps
Statistical Maps are special type of map in which the variation in quantity of a factor such as population, or crops in a geographic area is indicated.


Ratio Charts
A Ratio Chart in which the points are determined by measuring time (independent variable) and the logarithms of the values (dependent variables).












References

(March 2001). Approaches to the Analysis of Survey Data. U. K.: The University of Reading and Statistical Services Centre.
Calderon, J. F. (1993). Methods of Research and Thesis Writing. Mandaluyong City: National Book Store, Inc.
(March 2000). Informative Presentation of Tables, Graphs, and Statistics. U.K.: The University of Reading Statistical Services Centre.
Presenting Numerical Data. (2012). Learning Development, University of Leicester .




Composition of food commercials on Black prime time and general prime time

Percentage of Population