Presentation of Data
By
Dr. Lamya Al-Aazzawi
Data is pieces of information, such as numbers collected from measurement and counts obtained during research study known as data to give a full picture of classification data can be divided into two types
Two types of data as follows:
1.Discrete data have only one of a limited set of values and are counted only in whole numbers. Discrete variables may include things like hair color, gender, and number. These data are qualitative in nature
2.Continuous data are measurements made from a value within a defined range. Variables a long continuum such as temperature, scores on test, and time. These data are quantitative in nature.
Different scales of measurement are used for discreet and continuous data
Discreet data can use nominal or ordinal.
• Nominal scales of measurement consist of named categories with no order. For example, females may be placed in category A and males in category B.
• Ordinal scales of measurement consist of categories of variables in which the categories are in order, but there is no equal or defined distance between them.
Continuous data use interval and ration scales
• Interval scales of measurement have equal distance between variables, but there is no true zero point (i.e., temperature on Fahrenheit thermometer)
• Ratio scales of measurement have equal intervals between the variables, but there is a meaningful zero point (i.e., height and weight)
Types of Data.
Types of data Characteristics Examples Related Scales of Measurement Appropriate data display
Discrete Limited set of values, representative as whole numbers, qualitative Hair color, number of times a person brushes Nominal (named categories, e.g. male or female
Ordinal (same as nominal but categories in order; stages of cancer Bar graph
Continuous Particular value within a range variable a long a continuum, quantitative Temperature, test scores, time Interval (same as ordinal plus equal distance between variables but no zero; e.g., Fahrenheit
Ratio (same as interval plus equal distance between variable with zero; e.g., height, weight
Histogram
Tabulation
• General principles
• Use a clear and concise title that describes person, place, and time — what, where, and when — of the data in the table. Precede the title with a table number
• The table should be numerical e.g. table 1,2
• A Title should be given to each table which should be brief and explanatory
• The heading of columns or rows should be clear or concise
• The table should not be too large
• Foot notes may be given, where necessary providing explanatory notes or additional information
Simple table
When characteristics with values are presented in the form of table it is known as simple table
Frequency distribution table
• In the frequency distribution table, the data is first split up into convenient groups (class interval) and the number of items (frequency) which occur in each group is shown in adjacent columns
• Hence it is a table showing the frequency with which the values are distributed in different groups or classes with some defined characteristics
Charts and Diagrams
• Charts and diagrams are useful methods of presenting simple data.
• They have powerful impact on imagination of people.
• Gives information at a look
• Diagrams are better retained in memory than statistical table.
Common diagrams
• Simple bar graph. It is often used to display nominal or ordinal data that are discrete in nature.
• Multiple diagram
• Histogram. Although a type of bar graph is used most often to represent interval or ratio scaled variables that are continuous in nature
• Frequency polygon. It is used to present data that are continuous in nature
• Scatter diagram.
Line diagram
Bar charts
• The data presented is categorical
• Data is presented in the form of rectangular bar of equal breath
• Each bar represents one variant/attribute
• Suitable scale should be indicated and scale started from zero
• The bar may be vertical or horizontal
Histogram
This diagram is used to represent qualitative data of continuous type A histogram is a bar diagram without gap between the bars. It represents a frequency distribution
Pie Diagram
These are popularly used to show percentage breakdowns for qualitative data.
المادة المعروضة اعلاه هي مدخل الى المحاضرة المرفوعة بواسطة استاذ(ة) المادة . وقد تبدو لك غير متكاملة . حيث يضع استاذ المادة في بعض الاحيان فقط الجزء الاول من المحاضرة من اجل الاطلاع على ما ستقوم بتحميله لاحقا . في نظام التعليم الالكتروني نوفر هذه الخدمة لكي نبقيك على اطلاع حول محتوى الملف الذي ستقوم بتحميله .
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