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

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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