Title: DATA ANALYSIS DATA AND ITS TYPES Submitted to: Dr. Muhammad Rasheed By: Fazal Hakim Reg # 1094-314064 Student of PhD (Education) Department of Education Preston University, Islamabad
Dec 12, 2015
Title: DATA ANALYSISDATA AND ITS TYPES
Submitted to: Dr. Muhammad Rasheed
By: Fazal HakimReg # 1094-314064Student of PhD (Education)
Department of EducationPreston University,
Islamabad
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A Big Help
.
Data Analysis is Qualitative or Quantitative
Analysis of Data is normally done via Statistics
Statistics: Deals with quantitative data. (or Numerical data.)
Definition: It is the scientific method of collection, classification, presentation ,
analysis and decision making of the quantitative data
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Data analysis and interpretation
True or False? Complex analysis impresses people.
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Analysis of Data and its Plannig
• To make sure the questions and your data collection instrument will get the information you want.
• To align your desired “report” with the results of analysis and interpretation.
• To improve reliability--consistent measures over time.
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Key components of a data analysis plan
• Purpose of the evaluation• Questions• What you hope to learn from the
question• Analysis technique • How data will be presented
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Analyzing and Interpreting Quantitative Data
• Quantitative Data isPresented in a numerical format
Collected in a standardized manner
e.g. surveys, closed-ended interviews, tests
Analyzed using statistical techniques
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Analyzing and Interpreting Qualitative Data
• Qualitative data is thick in detail and description.• Data often in a narrative format• Data often collected by observation, open-ended interviewing,
document review• Analysis often emphasizes understanding phenomena as they
exist, not following pre-determined hypotheses
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DATA AND ITS TYPES
Recognizing and understanding the different data types
is an important component of proper data use and
interpretation
Data are often discussed in terms of variables, where a variable is:
Any characteristic that varies from one member of a population to another.
A simple example is height in centimeters, which varies from person to person.
Data and Variables
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There are two basic types of variables: numerical and categorical variables.
Numerical Variables: variables to which a number is assigned as a quantitative value.
Categorical Variables: variables defined by the classes or categories into which an individual member falls.
Types of Variables
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Types of Numerical variables
• Discrete: Reflects a number obtained by counting—no decimal.
• Continuous: Reflects a measurement; the number of decimal places depends on the precision of the
measuring device. • Ratio scale: Order and distance implied. Differences can be compared; has a true zero. Ratios can be compared.
Examples: Height, weight, blood pressure • Interval scale: Order and distance implied. Differences can be compared; no true zero. Ratios cannot be compared. Example: Temperature in Celsius.
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Defined by the classes or categories into which an individual member falls.
Categorical Variables
• Nominal Scale: Name only--Gender, hair color, ethnicity
• Ordinal Scale: Nominal categories with an implied order--Low, medium, high.
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Data: Observations recorded during research
Types of data:
1. Nominal data synonymous with categorical
data, assigned names/ categories based on
characters with out ranking between categories.
ex. male/female, yes/no, death /survival
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2. Ordinal data ordered or graded data,
expressed as Scores or ranks
ex. pain graded as mild, moderate and severe
3. Interval data an equal and definite interval
between two measurements
it can be continuous or discrete
ex. weight expressed as 20, 21,22,23,24
interval between 20 & 21 is same as 23 &24