Tables and Graphs Flashcards
Methods of Data Presentation: Textual
- Places important figures in the text of the study
- Allows us to highlight the significant figures in the study
- Confirms deductions and answers to the research problem
- Figures may be summary statistics like the minimum, maximum, mean median, mode, standard deviation, percentage, or total
Presenting Data with Text
data or highlights of the data are incorporated to a paragraph or in a textual presentation
Advantages of Textual Presentation
a) This presentation gives emphasis to significant figures and comparisons, usually highlighted in the text.
• b) It is simplest and most appropriate approach when there are only a few numbers to be presented such as numerical measures that summarize the data.
Disadvantages of Textual Presentation
a) When a large mass of quantitative data is included in a
text or paragraph, the presentation becomes almost
incomprehensible.
• b) Paragraphs can be tiresome to read especially if the same words are repeated so many times.
Methods of Data Presentation: Tabular
- Arrangement of figures in rows and columns for easy
reading and analysis - Compares and look for relationships among the
variables of interest - It can have frequency counts, proportions,
percentages, and other summary measures such as
totals and averages
Formal Statistical Table
• Contains all the important parts of a table like a table number, table title, head note, stub head, box head, column headings, footnotes, source
notes, etc.
• Can stand alone even without an introductory statement
The Parts of a Formal Statistical Table
- Spanner head
- Column head
- Stub head
- Row captions
- Footnotes
Table Spanner
A table spanner is a heading that covers the entire table body.
Tabular Presentation
- the systematic organization of data in rows and columns
Advantages of Tabular Presentation
Advantages:
• a) more concise than textual presentation
• b) easier to understand
• c) facilitates comparison and analysis of relationship among
different categories
• d) presents data in greater detail than a graph
Frequency Distribution
tabular arrangement of data by grouping the values into mutually exclusive classes and showing the number of observations falling in each class
Single-Value Grouping Frequency Distribution Table
form of frequency distribution where the distinct values are used as classes; commonly used for qualitative types of data
Grouping by Class Intervals
a form of frequency distribution where mutually exclusive classes are in the form of intervals; used for quantitative types of data.
Graphs
A device for showing numerical values or relationships in pictorial form.
Qualities of a Good Graph
• Accurate – should not be deceptive, distorted, or misleading
• Simple – should be straightforward, not loaded with
irrelevant or trivial symbols and ornamentation
• Clear – should be easily read and understood
• Attractive – to attract and hold attention
Methods of Data Presentation: Frequency Histogram
• Shows the overall picture or shape of the
distribution of the observed values in the data set.
• Each class frequency is represented by a vertical
bar, whose height is equal to the frequency of the
class interval and whose width represents the class
size.
• No gaps in between the bars.
• Area under the frequency histogram corresponds
to the total number of observations.
• Tallest vertical bar shows the frequency of the
modal class, the class interval with the largest
class frequency.
Methods of Data Presentation: Frequency Polygon
• Plots the class frequencies at the midpoint of the classes and connects the plotted points by means of straight lines.
• It can be superimposed on the frequency
histogram by connecting the midpoints of the
adjoining bars and then putting two additional
classes at both ends to close it.
• The area under the frequency polygon will be the same as the area under the frequency histogram.
• Both areas represent the total number of observations.
Methods of Data Presentation: Graphical - Line Chart
• appropriate for time series data • emphasis is on the movement • shows trends, patterns, forecasts • applicable for one or more time series data for comparison purposes
Guidelines for Line Chart
- ratio of height to width should be 2:3 or 3:4
* put the variable of interest on the vertical axis and the time on the horizontal axis
Column Charts
• Compares the magnitudes of variable in the x-
axis for the different categories of variable in
the y-axis
• for time series data, emphasis is on the
magnitude and not the movement or trend
Guidelines for Column Charts
• height of the column represents the amount of a
specific time
• columns must not be too long or too short, not too
wide or too narrow
• space between the bars must not be too wide or
narrow
• usual space between bars is around one-fourth of the width of the column
• vertical scale of the column chart should start
with zero
• do not put a break on the vertical scale
• use scale figures that are multiples of 5, 10,…,50
• if the observed values are small, use multiples of
2
• put a axis title label to identify the variable of
interest
• for one series of data, use only one color or
pattern
• for two or more series of data, use different
colors, shadings or patterns
• avoid wavy or unconventional patterns
Horizontal Bar Charts
• For qualitative types of data given a specific period
of time
• Compares the magnitudes of the different categories
of a qualitative variable
• Place the categories of the qualitative variable on
the y-axis and the amount or number is on the
horizontal axis
Guidelines for Horizontal Bar Chart
• the length of the bar represents the value for
the category
• the bars should not be too wide or narrow nor
too long or too short
• the spaces in between the bars may be one-fifth
to one-half the width of the bar
• sometimes arranging the bars according to
length facilitates comparisons
• use appropriate colors for the bars
Pie Charts
• circle divided into several sections
• useful for data sorted into categories for a specific
period of time
• emphasis is to show the component parts with
respect to the total in terms of the percentage
distribution
• use the pie chart if there are less than 6 categories in the data set
