ppt - data analysis and interpretation

8/10/2019 PPT - Data Analysis and Interpretation

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Analyzing and

Interpreting the DataAll meaningsdepend on the key of

interpretation.

-George Eliot


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Analysis and Interpretation

ANALYSIS clos e exam inat ion: the examination of something

in detail in order to understand it better or draw

conclusions from it

assessment: description or explanation of data,which should be based on careful consideration or

investigation

INTERPRETATION

establ ishm ent o f meaning: an explanation of the

significance of research data gathered


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Effective Data AnalysisData ANALYSIS and INTERPRETATION is theprocess of: assigning meaning to the collected

information, as well as determining the conclusions, significance,

and implications of the findings.

REMEMBER:

The steps involved in data analysis are a

function of the type of information collected. However, returning to the purpose of the

assessment and the assessment questionswill provide a structure for the organization of

the data and a focus for the analysis.


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The Body of your Paper

should be composed of the

following:

1. verbal meaning of the numerical or

raw data,

2. analysis, and

3. interpretation


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Effective Data Analysis

Effective data analysis involves:

keeping your eye on the main

research goal,

managing the data you gathered,

engaging in the actual process of

quantitative &/or qualitative analysis,

presenting your data, and

drawing meaningful & logical

conclusions .


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Always refer back to the Big

PictureAnalysis should be approached as a

critical,

reflective, and

iterative process

that cycles between data and an

overarching research framework that

keeps the big picture in mind.


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The analysis of NUMERICAL

(QUANTITATIVE) DATAis represented in mathematical terms. Themost common statistical terms include: the mean, which represents a numerical

average for a set of responses.

standard deviation, which represents thedistribution of the responses around themean. It indicates the degree of consistencyamong the responses.

frequency distribution, which indicates thefrequency of each response. For example, ifrespondents answer a question using anagree/disagree scale, the percentage ofrespondents who selected each response on

the scale would be indicated.


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The analysis of NARRATIVE

(QUALITATIVE) DATA

is conducted by organizing the data into

common themes or categories.

It is often more difficult to interpret

narrative data since it lacks the built-instructure found in numerical data.

Initially, the narrative data appears to be a

collection of random, unconnectedstatements.

The assessment purpose and questions

can help direct the focus of the dataor anization.


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Strategies in

analyzing NARRATIVE

(QUALITATIVE) DATAFocus groups and Interviews: Read and organize the data from each

question separately. This approach permits

focusing on one question at a time (e.g.,experiences with tour guides, characteristics

of tourists, tourism board responsibilities).

Group the comments by themes, topics, or

categories. This approach allows for focusingon one area at a time (e.g., characteristics of

tour guideslevel of preparation, knowledge

of the destination, availability).


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Strategies in

analyzing NARRATIVE

(QUALITATIVE) DATADocuments Code content and characteristics of

documents into various categories (e.g.,training manual policies and procedures,communication, responsibilities).

Observations

Code patterns from the focus of theobservation (e.g., behavioral patterns amount of time engaged/not engaged inactivity, type of engagement, communication,

interpersonal skills).


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Managing Data

Regardless of data type, managingyour data involves

familiarizing yourself with appropriate

software developing a data management system

systematically organizing and screening

your data

entering the data into a program

and finally weeding out the unnecessary

from the necessary data


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Data Types

Different data types demand discretetreatment, so itsimportant to be able to

distinguish variables by

cause and effect (dependent orindependent)

measurement scales (nominal, ordinal,

interval, and ratio)


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Presenting Quantitative Data

Presenting quantitative data ofteninvolves the production of graphs andtables

These need to be1. selectively generated so that they make

relevant arguments

2. informative yet simple, so that they aidreadersunderstanding


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Uncovering and Discovering

ThemesThe methods and logic of qualitative dataanalysis involve:

uncovering and discovering themes

that run through raw data, and interpreting the implication of those

themes for research questions