P2.1. Data Presentation Flashcards

1
Q

Types of Data Presentation:

A
  1. Textual presentation
  2. Tabular presentation
  3. Graphical presentation
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2
Q

display clearly, effectively, and summarizes quantities of information.

A

DATA PRESENTATION

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3
Q
  • describing data by the use of statements with few numbers
  • presented in paragraphs or sentences
  • explain results and trends, and provide contextual information

stress or emphasize significant information

A

Textual Presentation

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4
Q
  • gives emphasis to significant data
  • use for few data
A

Textual Presentation

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5
Q
  • data becomes incomprehensive when large quantitative data are included in paragraph
  • paragraph involving many figures can be tiresome to most readers when same words are repeated many times
A

Textual Presentation

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6
Q
  • data are converted into words or numbers in rows and columns
  • data should never be put in a table if it can be described in 1-2 sentences
A

Tabular Presentation

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7
Q

Consideration in table construction:

A
  • simplicity
  • clarity
  • directness
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8
Q
  • data checking and editing
  • summarizing and presenting data
  • basis, aid in graph or chart construction
A

Tabular Presentation

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9
Q

7 Components of Tabular Presentation:

A

Table number
Title
Row Headings/Stubs
Column Headings/Captions
Body of the Table
Source Note
Footnote

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10
Q
  • self-explanatory
  • all sources are specified
  • headings are specific and understandable
  • row & columns are checked for accuracy
  • cells are not left blank; enter “0” or “-“
  • exclusive & exhaustive categories
A

Tabular Presentation

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11
Q

2 types of tabular presentation:

A
  1. Master Table
  2. Dummy Table
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12
Q
  • single table which allows the distribution of observations across many variables of interest in a given study
  • each observation is cross classified across the variables which may be quantitative or qualitative data
  • allow the smaller generation of smaller tables

  • store information with an aim of presenting detailed statistical data
  • facilitate generation and tabulation of smaller table
A

Master Table

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13
Q
  • complete except for body
  • give preview of what table outputs may be expected from the study

  • help researcher clarify instrument
  • help protocol reviewer & computer programmer
A

Dummy Table

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14
Q

3 types of tables by number of variables presented:
- tables with only one variable
- tables with two variables
- tables with three or more variables

A
  • One-way table
  • Two-way table
  • Multi-way table
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15
Q
  • easy to understand
    * compact and concise than textual form
  • presents greater detail of data than graph
  • readily points out trends, comparisons and interrelations
  • facilitates analysis of categories of given variable
A

Tabular Presentation

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16
Q
  • too many rows and columns could make it difficult for the reader to understand the data
  • requires more time to construct
A

Tabular Presentation

17
Q
  • Pictorial representations of certain quantities(frequency) plotted with reference to a set of axes(x – horizontal; y – vertical)
  • graphs simplify complex information by using images and emphasizing data patterns or trends
  • useful for summarizing, explaining, or exploring quantitative data
  • present both large and small amounts of data
A

Graphical presentation

18
Q
  1. few data (< 3)
  2. small amount of data (= or > 3)
  3. small and large data (< or = or > 3)
A
  1. textual
  2. table
  3. graphical
19
Q
  • visually summarize the variables (data set is large)
  • emphasize particular statement about data set
  • enhance readability
  • appeal the visual memory
A

Graphical presentation

20
Q
  • include, below the figure, a title providing all relevant information
  • be referred to as figures in the text
  • identify figure axes by the variables under analysis
  • quote the source which provided the data, if required
  • demonstrate the scale being used
  • be self-explanatory
A

Graphical presentation

21
Q

Types of Graphical presentation:

pbc lhf sbs

A
  • pie chart
  • bar graph
  • component bar graph
  • line graph
  • histogram
  • frequency polygon
  • stem-and-leaf plot
  • box plot
  • scatter plot
22
Q
  • circles subdivided into a number of slices
  • area of each slice represents the relative proportion data points falling into given category
  • use to show how a whole is divided into its component parts which could be breakdowns of groups or totals
A

Pie chart

23
Q
  • bars of the same sizes
  • height & length = quantities of variables
  • Horizontal or vertical with gaps between to emphasize discontinuities
  • Also known as ONE DIMENSIONAL DIAGRAM
  • height of bars/rectangles: quantity of variables
A

BAR GRAPH

24
Q

2 types of Bar Graph:
1. w/ only one variable
2. w/ two or more variable

A
  1. simple bar graph
  2. multiple bar graph
25
Q
  • Height of bars should be proportional to the frequencies or rates of categories
  • Width of bars should be equal
  • Percentages & rates must be used when total number of observations for the groups are not uniform
  • When percentages are used, the sum of the heights of all the bars must be equal to 100%
  • To make them more appealing, bars are either colored or shaded in different ways
A

BAR GRAPH

26
Q
  1. used for qualitative variables
  2. used for discrete quantitative variables
A
  1. horizontal bar graph
  2. vertical bar graph
27
Q
  • bar is divided into smaller rectangles
  • smaller rectangle is proportional to the relative contribution of the component of the whole
  • used for NOMINAL DATA
  • different shades or colors emphasize differences between parts of the whole
  • Preferable over the pie in situations where the compositions of two or more groups are to be compared
A

Component bar graph

28
Q
  • Plot of dots joined with lines over some period of time in sequential series
  • TIME SERIES CHARTS
  • Horizontal axis: ?
  • Vertical axis: ?
A

Line Graph
- hori = time series
- verti = variable values

Scale:
frequency and percentage are used if the measure is distribution.

rate is also a measure, you can also use other like proportion, mean, median, etc. but frequency and distribution are mostly used.

29
Q
  • depict number or relative frequencies of data points falling into the given class
  • bars are drawn over the true limits of the classes, no gaps exist in between
  • preferred for grouped interval data

  1. horizontal axis: ?
  2. vertical axis: ?
A

HISTOGRAM

  1. continuous quantitative
  2. number of relative frequencies
30
Q

similar to histogram except that:
* frequencies are plotted against the corresponding midpoints of the classes
* adjacent points are joined with lines and the plot is tied down to the horizontal axis resulting in multi-sided polygon

A

Frequency polygon

31
Q
  • for small set of data
  • rank ordered lists
  • easier to restore the original value of the observation
  • lines gives more information than bars in histogram
  • show the actual data value instead of using bars to represent the height of an interval
A

Stem-and-leaf plot

32
Q
  • shows description of a large quantitative data
  • can be presented horizontal or vertical
  • height of rectangle is arbitrary and has no specific meaning
  • comparing the distributions of several variables or the distribution of a single variable in several groups on the same scale
A

Box plot

33
Q
  • shows the relationship between two quantitative variables
  • gives rough estimate of the type and degree of correlation between the variables
A

Scatter plot

34
Q
  • main feature & implications of the body of data can be grasped at a glance
  • more attractive & appealing to a wider range of readers
  • simplifies concepts that would otherwise have been expressed in so many words
  • shows trends & patterns of a large set of data
    * comparisons could be made more striking
  • can be readily clarify data
A

Graphical presentation

35
Q
  • cannot show as many sets of facts
  • can only show approximate values
  • require more time to construct
  • may be used to misinterpret results
A

Graphical presentation