Deck 13: Managing Data and Introducing Data Analysis
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Deck 13: Managing Data and Introducing Data Analysis
1
Quantitative data analysis is the analysis of numerical data using statistical methods.
True
2
Qualitative data analysis is the analysis of numerical data using statistical methods.
False
3
Some research projects generate quantitative data, some generate qualitative data and some generate a mixture of both, this is known as mixed methods research.
True
4
There are two different approaches to the analysis of data, quantitative data analysis and qualitative data analysis.
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5
If there is a lot of quantitative data, it may be necessary, even advisable, to use a dedicated software package for the analysis.
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6
Data is 'cleaned' to ensure that it is accurate.
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7
Soap and water is essential to the process of cleaning data.
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8
CAQDAS stands for computer assisted qualitative data analysis software.
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9
Simple and small quantitative data sets can be analysed by simply counting the numbers and calculating simple statistics in relation to them.
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10
The first stage of data analysis is description, where the researcher describes the data, and describes what s/he sees in the data.
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11
When using a dedicated software package for data analysis, the researcher must code the data before inputting it into the computer.
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12
Data management is the correct, safe and secure management of data.
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13
It is the responsibility of the researcher to gather data properly, to manage data properly, to keep data safe and secure, and to adequately and expertly analyse that data for the research project.
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14
There are two different orders of data, quantitative data and qualitative data.
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15
SPSS (Statistical Package for the Social Sciences) is a computer software package designed for the analysis of quantitative data.
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16
In checking accuracy in data, and accuracy in the way in which data was loaded into the computer software package, the researcher is engaged in cleaning the data.
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17
A coding key is a guide, created by the researcher, to the codes used in coding the data before inputting the data into the computer.
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18
Mixed methods research is superior to research that generates only quantitative data or only qualitative data.
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19
CADA stands for computer assisted data analysis.
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20
Qualitative data analysis does not draw on statistics or statistical methods; this is because qualitative data is non-numerical data.
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21
Atlas ti is a:
A)Means of analysing quantitative data.
B)Means of analysing statistical data.
C)Computer software package designed to support qualitative data analysis.
D)Computer software package designed to support quantitative data analysis.
A)Means of analysing quantitative data.
B)Means of analysing statistical data.
C)Computer software package designed to support qualitative data analysis.
D)Computer software package designed to support quantitative data analysis.
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22
NUDIST is a:
A)Means of analysing quantitative data.
B)Means of analysing statistical data.
C)Computer software package designed to support qualitative data analysis.
D)Computer software package designed to support quantitative data analysis.
A)Means of analysing quantitative data.
B)Means of analysing statistical data.
C)Computer software package designed to support qualitative data analysis.
D)Computer software package designed to support quantitative data analysis.
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23
The focus of any plan for data management is:
A)The cost of the plan.
B)The security and safety of the data.
C)The complexity of the plan.
D)The secrecy of the plan.
A)The cost of the plan.
B)The security and safety of the data.
C)The complexity of the plan.
D)The secrecy of the plan.
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24
NVivio is a:
A)Means of analysing quantitative data.
B)Means of analysing statistical data.
C)Computer software package designed to support qualitative data analysis.
D)Computer software package designed to support quantitative data analysis.
A)Means of analysing quantitative data.
B)Means of analysing statistical data.
C)Computer software package designed to support qualitative data analysis.
D)Computer software package designed to support quantitative data analysis.
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25
CADA stands for:
A)Complex and Assisted Data Analysis.
B)Careful Analysis of Data Advised.
C)Computer Assisted Data Analysis.
D)Complete Analysis of Data Advised.
A)Complex and Assisted Data Analysis.
B)Careful Analysis of Data Advised.
C)Computer Assisted Data Analysis.
D)Complete Analysis of Data Advised.
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26
The four stages of data analysis are description, interpretation, conclusions, and theorisation.
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27
The third stage of data analysis is the conclusions stage; the researcher draws a major or a minor conclusion from the data. In drawing conclusions, the researcher moves the interpretation along, from stating what it is that they see in the data, and what they think that means, to drawing some kind of conclusion about it.
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28
CAQDAS stands for:
A)Can Analyse Quantitative Data And Statistics.
B)Can Analyse Qualitative Data And Statistics.
C)Can Analyse Qualitative Data Sets
D)Computer Assisted Qualitative Data Analysis.
A)Can Analyse Quantitative Data And Statistics.
B)Can Analyse Qualitative Data And Statistics.
C)Can Analyse Qualitative Data Sets
D)Computer Assisted Qualitative Data Analysis.
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29
Data management is:
A)The correct, safe and secure management of data.
B)The responsibility of the thesis supervisor.
C)The responsibility of research participants.
D)The responsibility of research assistants.
A)The correct, safe and secure management of data.
B)The responsibility of the thesis supervisor.
C)The responsibility of research participants.
D)The responsibility of research assistants.
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30
If your data is electronically or digitally stored you should:
A)Keep it on a memory stick.
B)Keep it on a DVD.
C)Make copies of the file.
D)Keep it locked away.
A)Keep it on a memory stick.
B)Keep it on a DVD.
C)Make copies of the file.
D)Keep it locked away.
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31
The fourth and final stage of data analysis is the theorisation stage. The researcher theorises their data by linking it with the theory, laid out the in the literature review carried out for the research.
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32
There are essentially:
A)Two kinds of data, quantitative and qualitative.
B)Three different kinds of data, quantitative, qualitative and mixed.
C)Four different kinds of data, quantitative, qualitative, mixed and scientific.
D)Five different kinds of data, quantitative, qualitative, mixed, scientific and sound.
A)Two kinds of data, quantitative and qualitative.
B)Three different kinds of data, quantitative, qualitative and mixed.
C)Four different kinds of data, quantitative, qualitative, mixed and scientific.
D)Five different kinds of data, quantitative, qualitative, mixed, scientific and sound.
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33
Qualitative data is data in the form of:
A)Numbers.
B)Statistics.
C)Mathamatical equations.
D)Feelings, beliefs, perspectives, opinions.
A)Numbers.
B)Statistics.
C)Mathamatical equations.
D)Feelings, beliefs, perspectives, opinions.
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34
It is of the utmost importance that the analysis and the findings from the analysis are grounded in the data.
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35
The second stage of data analysis is interpretation, where the researcher interprets the data. The researcher attempts to detail and explain what the data mean, the meaning of the data.
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36
The fourth framework in the four frameworks approach to research is:
A)The conceptual framework.
B)The theoretical framework.
C)The methodological framework.
D)The analytical framework.
A)The conceptual framework.
B)The theoretical framework.
C)The methodological framework.
D)The analytical framework.
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37
Quantitative data is data in the form of:
A)Numbers.
B)Narratives and stories.
C)Drawings, cartoons, paintings, photographs.
D)Feelings, beliefs, perspectives, opinions.
A)Numbers.
B)Narratives and stories.
C)Drawings, cartoons, paintings, photographs.
D)Feelings, beliefs, perspectives, opinions.
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38
The computer software package SPSS is useful:
A)For the analysis of qualitative data.
B)For the analysis of quantitative data.
C)For the analysis of mixed data.
D)For the analysis of scientific data.
A)For the analysis of qualitative data.
B)For the analysis of quantitative data.
C)For the analysis of mixed data.
D)For the analysis of scientific data.
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39
Summarising statistics are:
A)Difficult to calculate.
B)Easy to calculate.
C)Highly sophisticated mathamatical manipulations.
D)Statistics that provide summaries of data.
A)Difficult to calculate.
B)Easy to calculate.
C)Highly sophisticated mathamatical manipulations.
D)Statistics that provide summaries of data.
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40
Sometimes researchers gather both quantitative and qualitative data for their research project; this is known as:
A)A mixed methods research project.
B)A large research project.
C)A large data set.
D)A cross concepts research project.
A)A mixed methods research project.
B)A large research project.
C)A large data set.
D)A cross concepts research project.
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41
For the most efficient management of a large qualitative data set:
A)A thematic approach to analysis is most effective.
B)A computerised qualitative data analysis software package, CAQDAS, is invaluable.
C)The use of a calculator is essential.
D)The use of SPSS is essential.
A)A thematic approach to analysis is most effective.
B)A computerised qualitative data analysis software package, CAQDAS, is invaluable.
C)The use of a calculator is essential.
D)The use of SPSS is essential.
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42
There are:
A)Seven stages in data analysis.
B)Six stages in data analysis.
C)Five stages in data analysis.
D)Four stages in data analysis.
A)Seven stages in data analysis.
B)Six stages in data analysis.
C)Five stages in data analysis.
D)Four stages in data analysis.
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43
Signs in society are signs because they signify something and anything that has signifying power can be studied:
A)Semiotically.
B)Using surveys.
C)Using case studies.
D)Using experiments.
A)Semiotically.
B)Using surveys.
C)Using case studies.
D)Using experiments.
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44
The first stage in data analysis is:
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
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45
Why is data management important?
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46
Semiotics is:
A)The study of surveys and survey research.
B)The study of case studies and case study research.
C)The study of experiments and experimental research.
D)The study of signs, their form, content and expression, in society.
A)The study of surveys and survey research.
B)The study of case studies and case study research.
C)The study of experiments and experimental research.
D)The study of signs, their form, content and expression, in society.
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47
The second stage in data analysis is:
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
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48
The fourth and final stage in data analysis is:
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
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49
Explain the role of research in the generation of theory.
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50
The argument or point that you make in your data analysis chapter must be:
A)Short and to the point.
B)Clearly debatable.
C)Dictated by the thesis supervisor.
D)A clear response to the overall aim of the research project.
A)Short and to the point.
B)Clearly debatable.
C)Dictated by the thesis supervisor.
D)A clear response to the overall aim of the research project.
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51
Computerised data analysis software packages are particularly helpful with:
A)Decisions around methodology.
B)Decisions around data gathering methods.
C)Managing data and data analysis.
D)Managing fieldwork.
A)Decisions around methodology.
B)Decisions around data gathering methods.
C)Managing data and data analysis.
D)Managing fieldwork.
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52
The third stage in data analysis is:
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
A)Description.
B)Interpretation.
C)Drawing conclusions.
D)Theorisation.
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53
Outline some of the key ways in which qualitative data can be analysed.
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