P2.1. Data Presentation Flashcards
1
Q
Types of Data Presentation:
A
- Textual presentation
- Tabular presentation
- Graphical presentation
2
Q
display clearly, effectively, and summarizes quantities of information.
A
DATA PRESENTATION
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
4
Q
- gives emphasis to significant data
- use for few data
A
Textual Presentation
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
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
7
Q
Consideration in table construction:
A
- simplicity
- clarity
- directness
8
Q
- data checking and editing
- summarizing and presenting data
- basis, aid in graph or chart construction
A
Tabular Presentation
9
Q
7 Components of Tabular Presentation:
A
Table number
Title
Row Headings/Stubs
Column Headings/Captions
Body of the Table
Source Note
Footnote
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
11
Q
2 types of tabular presentation:
A
- Master Table
- Dummy Table
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
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
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
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
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
- few data (< 3)
- small amount of data (= or > 3)
- small and large data (< or = or > 3)
A
- textual
- table
- 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
- simple bar graph
- multiple bar graph
25
- **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**
BAR GRAPH
26
1. used for **qualitative variables**
2. used for **discrete quantitative variables**
1. horizontal bar graph
2. vertical bar graph
27
- 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
Component bar graph
28
* **Plot of dots joined with lines** over some period of time in **sequential series**
* **TIME SERIES CHARTS**
* Horizontal axis: ?
* Vertical axis: ?
Line Graph
- hori = time series
- verti = variable values
## Footnote
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
- 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**
## Footnote
1. horizontal axis: ?
2. vertical axis: ?
HISTOGRAM
## Footnote
1. continuous quantitative
2. number of relative frequencies
30
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**
Frequency polygon
31
- 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
Stem-and-leaf plot
32
- 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**
Box plot
33
* shows the **relationship between two quantitative variables**
* gives rough estimate of the **type and degree of correlation between the variables**
Scatter plot
34
* 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**
Graphical presentation
35
* cannot show as many **sets of facts**
* can only show **approximate values**
* **require more time to construct**
* may be used to **misinterpret results**
Graphical presentation
