Tables and Graphs Flashcards

1
Q

Methods of Data Presentation: Textual

A
  1. Places important figures in the text of the study
  2. Allows us to highlight the significant figures in the study
  3. Confirms deductions and answers to the research problem
  4. Figures may be summary statistics like the minimum, maximum, mean median, mode, standard deviation, percentage, or total
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2
Q

Presenting Data with Text

A

data or highlights of the data are incorporated to a paragraph or in a textual presentation

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3
Q

Advantages of Textual Presentation

A

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.

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4
Q

Disadvantages of Textual Presentation

A

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.

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5
Q

Methods of Data Presentation: Tabular

A
  1. Arrangement of figures in rows and columns for easy
    reading and analysis
  2. Compares and look for relationships among the
    variables of interest
  3. It can have frequency counts, proportions,
    percentages, and other summary measures such as
    totals and averages
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6
Q

Formal Statistical Table

A

• 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

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7
Q

The Parts of a Formal Statistical Table

A
  1. Spanner head
  2. Column head
  3. Stub head
  4. Row captions
  5. Footnotes
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8
Q

Table Spanner

A

A table spanner is a heading that covers the entire table body.

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9
Q

Tabular Presentation

A
  • the systematic organization of data in rows and columns
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10
Q

Advantages of Tabular Presentation

A

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

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11
Q

Frequency Distribution

A

tabular arrangement of data by grouping the values into mutually exclusive classes and showing the number of observations falling in each class

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12
Q

Single-Value Grouping Frequency Distribution Table

A

form of frequency distribution where the distinct values are used as classes; commonly used for qualitative types of data

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13
Q

Grouping by Class Intervals

A

a form of frequency distribution where mutually exclusive classes are in the form of intervals; used for quantitative types of data.

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14
Q

Graphs

A

A device for showing numerical values or relationships in pictorial form.

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15
Q

Qualities of a Good Graph

A

• 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

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16
Q

Methods of Data Presentation: Frequency Histogram

A

• 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.

17
Q

Methods of Data Presentation: Frequency Polygon

A

• 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.

18
Q

Methods of Data Presentation: Graphical - Line Chart

A
• 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
19
Q

Guidelines for Line Chart

A
  • 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

20
Q

Column Charts

A

• 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

21
Q

Guidelines for Column Charts

A

• 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

22
Q

Horizontal Bar Charts

A

• 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

23
Q

Guidelines for Horizontal Bar Chart

A

• 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

24
Q

Pie Charts

A

• 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

25
Q

Guidelines for Pie Chart

A

• plot the biggest slice at 12 o clock
• arrange components of the pie chart according to
magnitude
• if there is an “Others” category, put it in the last
section
• use different colors, shadings, or patterns to
distinguish one section of the pie to the other
sections

26
Q

Pictograph

A

• appropriate for data sorted into categories for a
specific period of time
• gives only an approximation of the actual figures with
emphasis of getting the reader’s attention
• symbols selected should be self-explanatory and easy
to understand
• each symbol represents a number

27
Q

Statistical Maps

A

• also called cross-hatched maps or shaded maps
• shows data in geographical areas
• geographic areas may represent barangays, cities,
district, provinces, and countries
• figures in the map can be numbers, ratios, rates,
percentages, and indices

28
Q

Stem-and-leaf Display (Tukey, 1977) Steps

A

Steps:

  1. Divide each measurement into two parts: the stem and the leaf.
  2. List the stems in a column, with a vertical line to their right.
  3. For each of the measurement, record the leaf portion in the same row as its corresponding stem.
  4. Order the leaves from lowest to highest in each stem.
  5. Provide the key to your stem and leaf coding so that the reader can recreate the actual measurements if necessary.