Quantitative and qualitative data analysis lecture 1 introduction
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Quantitative and Qualitative Data Analysis Lecture 1: Introduction. Statistics (3rd Ed.) by David Freedman, Robert Pisani and Roger Purves . Norton Doing Data Analysis with SPSS Version 12 by Carver and Nesh .

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Quantitative and qualitative data analysis lecture 1 introduction

Quantitative and Qualitative Data AnalysisLecture 1: Introduction


Reference books

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 2

Statistics (3rd Ed.) by David Freedman, Robert Pisani and Roger Purves. Norton

Doing Data Analysis with SPSS Version 12 by Carver and Nesh.

Qualitative Data Analysis: An Expanded Sourcebook, by Matthew B. Miles and A. Michael Huberman. 2nd Edition. Sage Publications: Thousand Oaks, CA

A Practical Guide to Scientific Data Analysis by David Livingstone ChemQuest, Sandown, Isle of Wight, UK

Reference books


Outline

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 3

Motivation

What is Data?

What is Data Analysis

Quantitative Data and Qualitative Data

Quantitative and Qualitative Data Analysis

Outline


Things aren t always what we think

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 4

Things aren’t always what we think!

Blind men and an elephant


Quantitative and qualitative data analysis lecture 1 introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 5

Data

Data: Values of qualitative or quantitative variables.

What information do we get from this data??


Data analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 6

Data Analysis

Sorted data


Data presentation

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 7

Data Presentation

Marks

Hours studied


What is data analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 8

Data analysis is the process of turning data into information

An attempt by the researcher to summarize collected data

Data Interpretation is an attempt to find meaning

Good analysis communicates something meaningful about the world

What is data analysis?


Types of data

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 9

Types of Data

Quantitative Data:

Data that is numerical, counted, or compared on a scale

Qualitative Data:

Textual data

Interview transcripts

Case notes/ clinical notes

Photographs

Video recordings


Types of data analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 10

Types of Data Analysis

Quantitative Data Analysis:

Converting quantitative data into information

Qualitative Data Analysis:

Converting qualitative data into information


Quantitative and qualitative data analysis lecture 1 introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 11

Quantitative Analysis


Quantification of data

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 12

Quantification Analysis :

The numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect.

Quantification of Data


Quantitative analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 13

Quantitative Analysis

Can be used to answer questions like

  • What is the percent distribution?

  • How much variability is there in the data?

  • Are the results statistically significant?


Simple quantitative analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 14

Simple Quantitative Analysis

  • Averages

    • Mean: add up values and divide by number of data points

    • Median: middle value of data when ranked

    • Mode: figure that appears most often in the data

  • Percentages


Central tendency

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 15

Central Tendency

Central tendency: The way in which quantitative data tend to cluster around some value. A measure of central tendency is any of a number of ways of specifying this "central value"

Central Tendency

Average (Mean)

Median

Mode


Quantitative and qualitative data analysis lecture 1 introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 16

Mean

  • Mean (arithmetic mean) of data values


Quantitative and qualitative data analysis lecture 1 introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 17

Mean

  • The most common measure of central tendency

  • Affected by extreme values (outliers)

0 1 2 3 4 5 6 7 8 9 10

0 1 2 3 4 5 6 7 8 9 10 12 14

Mean = 5

Mean = 6


Median

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 18

Median

Median: The “middle” number

Not affected by extreme values

0 1 2 3 4 5 6 7 8 9 10

0 1 2 3 4 5 6 7 8 9 10 12 14

Median = 5

Median = 5


Quantitative and qualitative data analysis lecture 1 introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 19

Mode

Mode: Value that occurs most often

  • Not affected by extreme values

  • There may be no mode

  • There may be several modes

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

0 1 2 3 4 5 6

No Mode

Mode = 9


Simple quantitative analysis1

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 20

Simple quantitative analysis

  • Graphical representations give overview of data


Simple quantitative analysis2

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 21

Simple quantitative analysis

  • Graphical representations give overview of data


Strengths of quantitative research

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 22

Strengths of Quantitative Research

  • Precise, quantitative, numerical data

  • Testing hypothesis/confirming theories

  • Generalizing finding, random samples with sufficient size

  • Comparatively quick data collection

  • Less time consuming analysis

  • May minimize personal bias

    .


Weaknesses of quantitative research

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 23

Weaknesses of QuantitativeResearch

  • Only applicable for measurable (quantifiable) phenomena

  • Simplifies and ”compresses” the complex reality, lack of detailed narrative

  • Theories or categories might not reflect local constituencies’ understandings


Quantitative and qualitative data analysis lecture 1 introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 24

Qualitative Analysis


Qualitative data

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 25

Qualitative Data

  • Narratives, logs, experience

  • Interviews

  • Diaries and journals

  • Notes from observations

  • Photographs

  • Video recordings


What is qualitative research

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 26

What is Qualitative Research?

  • Research studies that investigate the quality of

    • Relationships

    • Activities

    • Situations

    • Materials


Qualitative data analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 27

Qualitative Data Analysis

Used for any non-numerical data collected as part of the evaluation

  • Unstructured observations

  • Analysis of written documents

  • Diaries, observations


Qualitative data analysis1

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 28

Qualitative Data Analysis

Answers questions like:

  • Is the project being implemented according to plan?

  • What are some of the difficulties faced by staff?

  • Why did some participants drop out early?

  • What is the experience like for participants?


Steps in qualitative research

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 29

Steps in Qualitative Research

The steps are as follows (in some cases):

  • Identification of the phenomenon and hypothesis generation

  • Identification of the participants in the study

  • Data collection (continual observance)

  • Data analysis

  • Interpretation/Conclusions


Generalization in qualitative research

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 30

Generalization in Qualitative Research

  • A generalization is usually thought of as a statement or claim that applies to more than one individual, group, or situation.

  • The value of a generalization is that it allows us to have expectations about the future.

  • A limitation of Qualitative Research is that there is seldom justification for generalizing the findings of a particular study.


Trustworthiness in qualitative research

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 31

Trustworthiness in Qualitative Research

Check on the trustworthiness of the researchers:

Compare one informant’s description with another informant’s description of the same thing.

  • Triangulation: Comparing different information on the same topic.

    • Data triangulation

      • Use of multiple data sources

        • Students, teachers, administrators, etc.

    • Methods triangulation

      • Interviews, observations, etc.

    • Researcher triangulation

      • Use a team of researchers.


Criteria for judging research

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 32

Criteria for judging research

Quantitative

  • Internal validity

    • Did A cause B?

  • External Validity

    • Are these findings generalizable?

  • Reliability

    • Are the measures repeatable?

  • Objectivity

    • Are the findings free of researcher bias/values?

Qualitative

  • Credibility

    • Believable from participant’s view

  • Transferability

    • Can this finding be transferred to other contexts?

  • Dependability

    • Would another researcher come to similar conclusions?


Quantitative and qualitative data analysis lecture 1 introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 33

Thanks for your attention


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