GROUP NO.5 MBA (3.5) 3rd sem (A.N) 1.Shakir Nawaz Khan .Roll No.62 2.Farhat ullah Roll No . 3. Zubaida dawood Roll No. 4. Usman khurshid Roll No.83 5. Nauman ayaz Roll No.61

Data analysis : Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science

USMAN KHURSHID .

SHAKIR NAWAZ

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ZUBAIDA DAWOOD

Qualitative Data Analysis The outputs of qualitative data analyses are usually words, the inputs are also usually words – typically in the form of extended texts Data is almost always derived from what the researcher has observed, heard in interviews, or found in documents

Qualitative Data Analysis Social anthropological versus interpretivist approaches Social anthropologists (and others, like grounded theorists and life historians) believe that there exist behavioral regularities (for example, rules, rituals, relationships, and so on) that affect everyday life and that it should be the goal of researchers to uncover and explain those regularities.

Qualitative Data Analysis Social anthropological versus interpretivist approaches Interpretivists (including phenomenologists and symbolic interactionists) believe that actors, including researchers themselves, are forever interpreting situations, and that these, often quite unpredictable, interpretations largely affect what goes on.

Qualitative Data Analysis Does qualitative data analysis emerge from or generate the data collected? The question of which comes first Data or ideas about data

Qualitative Data Analysis The strengths and weaknesses of qualitative data analysis revisited Strengths Can produce theories More likely to be grounded in the immediate experiences of those participants than in the speculations of researchers.

Qualitative Data Analysis The strengths and weaknesses of qualitative data analysis revisited Weaknesses Generalizability

Qualitative Data Analysis Are there predictable steps in qualitative data analysis? First researchers code their own data or acquire computer-ready data Other steps are much more fluid Typical flow includes data collection –data reduction—data displaying—conclusion drawing and verification

Qualitative Data Analysis Data Collection and Transcription Several software packages exist to facilitate the processing of qualitative data Qualitative data software packages have many pros an cons and should be considered carefully before adopting.

Nauman ayaz .

Qualitative Data Analysis Data Reduction The various ways in which a researcher orders collected and transcribed data Coding and memoing are common data reduction techniques

Qualitative Data Analysis Coding The process of assigning observations, or data, to categories In qualitative analysis, coding is more open-ended because both the relevant variables and their significant categories are apt to remain in question longer

Qualitative Data Analysis Coding The goal of coding is to create categories that can be used to organize information about different cases Assigning a code to a piece of data is the first step in coding The second step is putting the coded data together with other data coded the same way

Qualitative Data Analysis Coding Types of Coding One purpose of coding is to keep facts straight – called descriptive coding Coding to advance your analysis is analytical coding The preliminary phase of analytical coding is called initial coding Initial coding eventually becomes focused coding, which is concentrating or elaborating on codes specific to analysis

Qualitative Data Analysis Coding Memos Extended notes that the researcher writes to help herself or himself understand the meaning of codes

Qualitative Data Analysis Data displays Visual images that summarize information

Summary Quantitative data analyses Qualitative data analyses