Data, Type and Methods of representation Dr Hidayathulla Shaikh

Objectives At the end of lecture student should be able to Define data Classify data Explain various methods of data representation

3 Data Definition: Ordinal DichotomousNominal A collective recording of observations either numerical or other-wise Two broad categories:

Qualitative Data When the data is collected on the basis of attributes or qualities like sex, malocclusion, cavity etc., Nominal data Naming or categorical variables that have no measurement scales Examples Recording blood groups a) O b) A c) B d) AB Reasons for extraction of teeth a) Caries b) periodontitis c) therapeutic d) others

Ordinal (ranked) data – Characterized in terms of more than two variables and have a clearly implied direction but the data are not measured on a measurement scale – Examples Severity of patient perceived pain a) No pain b) mild pain c) moderate pain d) severe Esthetic concerns of children a) Satisfied b) neutral c) not satisfied

Dichotomous data (Binary variables) – The variable can have only two values – May or may not be directional – Examples Sex of the respondents Presence or absence of dental disease in a village population Nominal, ordinal and dichotomous data can be called categorical data

Quantitative Data When the data is collected through measurements using calipers, like arch length, arch width, fluoride concentration in water supply etc., Discrete: When the variable under observation takes only fixed values like whole numbers. Continuous: If the variable can take any value in a given range, decimal or fractional

Data : A set of values recorded on one or more observational units. Quantitative data : Data with magnitude. E.g. Height & weight, Blood pressure etc Qualitative data : Data with frequency only but no magnitude. E.g. Attacked, died, cured, relieved, treated, not treated etc.

Sources Primary: 1.Direct Personal Interview. 2.Oral Health Examination. 3.Questionnaire Method. Secondary: Hospital Records. Government Records.

Presentation of data Data collected & compiled from experimental work, surveys, records –raw data Needs to be sorted & classified To make it simple, concise, meaningful, interesting & helpful 10

11 Objective of classification of data : make the data simple, concise, meaningful, interesting and helpful in further analysis. Presentation of Data 2 methods  A) Tabulation  B) Diagrams / drawings The two elements of classification are The variable and The frequency.

Variable: a name denoting a condition, occurrence or effect that can assume different values Divided: subgroups,classes. have lowest and highest values Class interval : difference between the upper and lower limit of a class Eg: in the class 5 -14, 5 - lower limit and 14 - upper limit. class interval = =9. Frequency: is the number of units belonging to each group of the variable. Frequency distribution table: way of presenting data in the tables

A) Tabulation Types of tables 1) Master table – table which contain all the data obtained from survey 2) Simple table – they are one way table which supply answers to questions about one characteristics.

3) Frequency distribution table This is simplest two column frequency table. The first column lists the classes into which the data are grouped. The second column lists the frequencies for each classification. 14 Table1 students in a primary school Classes (standard) No. of students 1 st 68 2 nd 65 3 rd 63 4 th 62 5 th 60

Diagrams Extremely useful attractive to the eyes, give a bird's eye view of the entire data, have a lasting impression facilitate comparison of data relating to different time periods and regions. 15

TYPES OF DIAGRAMS Bar Diagram : qualitative data. Multiple Bar: qualitative data Component Bar Diagram: qualitative data Proportional Bar Diagram: qualitative data. Pie Diagram: qualitative data Line diagram: qualitative data Frequency Polygon: quantitative data Cartograms or Spot Map: geographical distribution of frequencies Histogram: quantitative data of continuous type. 16

Basic rules in constructing diagrams Every diagram must be self explanatory, simple and consistent with the data. The values of the variables are presented on horizontal or X-axis and the frequency on vertical line or Y-axis. There should not be too many lines on the graph. The scale of presentation for X axis and Y axis should be mentioned. The scale of division of the two axes should be proportional & the details of the variables and frequencies be presented on the axes. 17

Bar Diagram 18 represent qualitative data. only one variable. width of the bar remains the same the length varies according to the frequency in each category. bars : vertical or horizontal. Limitation : represent only one classification cannot be used for comparison

Multiple Bar Compare qualitative data with respect to a single variable. Eg: sex ­wise or with respect to time or region. each category of the variable have a set of bars of the same width corresponding to the different sections without any gap in between the width and the length corresponds to the frequency. 19

Component Bar Diagram represent qualitative data, presents both the number of cases in major groups as well as the subgroups simultaneously Used to compare sub groups between major groups of observations. 20

Proportional Bar Diagram: Represent qualitative data. Compare only the proportion of sub-groups between different major groups of observations, then bars are drawn for each group with the same length, either as 1 or 100%. These are then divided according to the sub-group proportion in each major group. 21

PIE DIAGRAM The frequency of the group is shown in a circle. Degree of angle denotes the frequency. Instead of comparing the length of bar, the areas of segments are compared. 22

Line diagram useful to study changes of values in the variable over time It is simplest type of diagram X-axis, - hours, days, weeks, months or years Y-axis- value of any quantity pertaining to X-axis, 23

Histogram Quantitative data of continuous type. Bar diagram without gap between the bars. Represents a frequency distribution. The class interval is given on X axis Frequencies are given along Y axis. 24

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Frequency Polygon frequency distribution of quantitative data compare two or more frequency distributions. a point is marked over the mid-point of the class interval, corresponding to the frequency. points are connected by straight lines. The first point and last point are joined to the midpoint of previous and next class respectively. To compare two or more frequency distributions, lines of different types are drawn on the same graph. 26

Cartograms or spot maps Used to show geographical distribution of frequency 27

PICTOGRAM The pictures representing the value of items are called pictograms. It is most useful way of representing data to those people who cannot understand. 28