City or Town
|
Point
A
|
Point
B
|
Point
C
|
Point
D
|
Point
E
|
Point A
|
—
|
||||
Point B
|
87
|
—
|
|||
Point C
|
64
|
56
|
—
|
||
Point D
|
37
|
32
|
91
|
—
|
|
Point E
|
93
|
35
|
54
|
43
|
—
|
The going can get really tough when you have to deal with a pile of data. It can be easier of the data is properly organized and tabulated. Whether you are doing a quantitative analysis, or preparing charts and graphs, preparing a table will form the basis for a number of calculations. A pile of data will be simpler to understand when it is arranged and classified in a systematic manner. There can be a number of approaches for arranging data in tables.
When just a list is needed, then a one dimensional table will be suitable. In this style, each individual observation is equivalent, meaning that they all point to the same answer. The only way they can be arranged is according to the numeric value in ascending or descending order.
There are two dimensional tables, which are used widely in Thesis Data Analysis. This table shows two aspects of each variable, like the height and weight of students in a class. So a result of observation or data collected will be expressed as 4 feet, 40 kg. Both the values need to be arranged in the table and the organization can be done according to the numeric value of the first characteristic.
Whatever be the form of table you are preparing, each value must be a legitimate result of the data collection process and must contribute to the experiment. Each entry is termed as an experiment variable. While there is no theoretical limit to the number of variables that an experiment can include, you have to be rational when doing Dissertation Data Analysis and consider only so many variables that can be logically measured. The variables must also be scientifically fit to be measured. Too many factors at a time will make the table cumbersome and the calculation complicated.
The
first step in dissertation creation is research, followed writing and editing.
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