uses analytical and logical reasoning to gain information from the data

to find meaning in data so that the derived knowledge can be used to make informed decisions

What are the methods of data analysis?

Science involves in the collection, organization, analysis, and interpretation of numerical data

the methods of data analysis are: research objectives, number of population sample, types of variables measured in the study, and scale of measurement

2 types of statistics

It is an initial step in the analysis of data in analytic research

Descriptive statistics are used in descriptive studies as a means of describing the nature and characteristics of the event under investigation

What are under the Descriptive Statistics?

What are under the Inferential Statistics?

A table of rank ordered scores that shows the number of times each value occured

Percentages of Frequency Distribution

constructed by grouping the scores into classes, or intervals, each class represents a unique range of scores within the distribution

classes are mutually exclusive (no overlap) and exhaustive within the range of scores obtained

identify

identify

layman’s concept of average

it is sensitive to extreme values

it is used especially when other statistical techniques like testing of hypothesis are to be applied to the data.

identify what kind of central tendency

the middlemost observation in a set of data arranged in numerical order

it is not sensitive to extreme values

it is used when distribution is markedly skewed

the most frequently occurring value among the observations

unaffected by extreme values

not used in higher statistical analysis

used for continuous and symmetric data. such as when your data is normally distributed

used for ordinal data or for a numerical data whose distribution is skewed. dealing with ordinal data

used primarily for bimodal distributions. the least used of the measures of central tendency. can only be used when dealing with nominal data

It describes the degree of scatter of the different values of the variable

What are the different degree of scatters of the different values of the variable

highest – lowest value / Maximum- minimum

the average of squared differences from the mean

the squared value of the standard deviation

looks at how spread out a group of numbers is from the mean

square root of the variance

Measures variability in relation to the mean. It is useful in comparing two series for sets of data, especially when such sets or series are expressed in different units of measurements

determine which is more variable

Summary indices describing the “central point” or the most characteristic value of a set of measurement

values of random variable X that divides the observations into 100 equal parts

values of random variable X that divides the observations into 10 equal parts

values of random variable X that divides the observation into 4 equal parts

It can be observed and recorded. This data type is non-numerical in nature and is collected through methods of observations, one-on-one interviews, focused group discussions, and similar methods. in statistics, it is also known as categorical data – data that can be arranged categorically based on the attributes and properties of a thing or a phenomenon.

Because qualitative data are so dense and rich, not all information from the interviews can be used in the data analysis.

Qualitative researchers need to winnow the data, a process of focusing on some of the data and disregarding other parts of it.

In qualitative research, data are combined into a small number of themes.

2 kinds of qualitative research

it is a time-consuming process, even if you are analyzing data from a few individuals.

these have become quite popular, and they help researchers organize, sort, and search for information in text or image databases. The basic idea behind these is that using a computer is an efficient means for storing and locating qualitative data. Although the researcher still needs to go through each line of the text just like hand coding, by going through transcriptions, and assigning codes, this process may be faster and more efficient. they require time and skill to learn and employ effectively, although books for learning the programs are widely available.

3 popular qualitative data analysis software programs

These programs: MAXqda, Atlas.ti, and QSR NVivo are available to work on a PC or MAC.

These first 2 programs were developed in Germany

This program was developed in Australia

It specifically uses Colaizzi’s strategy.

Qualitative data analysis will proceed on two levels: (a) the first is the more general procedure in analyzing the data, and (b) the second would be the steps for analysis embedded within specific qualitative designs.

Despite these analytic differences specific to each qualitative design, researchers often use a general procedure for qualitative data analysis.

Has systematic steps such as open coding, axial coding, and selective coding.

involve the use of a detailed description of the setting or individuals, followed by analysis of the data for themes.

Researchers should view qualitative data analysis as following steps from specific to general and as involving multiple levels.

Steps in Data Analysis in Qualitative Research

Organize and prepare the data for analysis. This involves transcribing the interviews, optically scanning interview transcripts, typing up the field notes, sorting and arranging the data into different types depending on the sources of information

Read all the data. This provides a general sense of the information and an opportunity to reflect on its overall meaning. What general ideas are the participants saying? What is the tone of the ideas? What is the impression of the overall depth, credibility, and use of the information? Sometimes qualitative researchers write notes in the margins of transcripts and start listing general thoughts about the data at this stage. For visual data, a sketchbook of ideas can begin to take shape

Start coding all the data.

Use the coding process to generate (1) a description of the setting or people and (2) categories or themes for analysis. Description involves a detailed rendering of information about people, places, or events in a setting. This analysis is useful in designing detailed descriptions for case studies, ethnographies, and narrative research projects. Codes are also used for generating themes or categories. These themes are the ones that appear as major findings in qualitative studies and are often used as headings in the findings section of studies.

Advance how the description and themes will be represented in the qualitative narrative. The most popular approach is to use a narrative passage to convey the findings of the analysis. This might be a discussion that mentions a chronology of events, the detailed discussion of several themes and subthemes, or a discussion with interconnecting themes.

it involves making an interpretation of the findings or results. Asking, “What were the lessons learned?” captures the essence of this idea. These lessons could be derived from a comparison of the findings with information gathered from the literature or theories. In this way, authors suggest that the findings confirm past information or diverge from it.

It is the process of organizing the transcript data by bracketing chunks of text and writing a word representing the text. It involves segmenting sentences or paragraphs into categories, and labeling those categories with a term, often a term based on the actual language of the participant, called an in vivo term.

Part of the coding process is deciding whether the researcher should: (a) develop codes only on the basis of the emerging information collected from participants, (b) use predetermined codes and then fit the data to them, or (c) use some combination of emerging and predetermined codes.

It is the process of organizing the transcript data by bracketing chunks of text and writing a word representing the text. It involves segmenting sentences or paragraphs into categories, and labeling those categories with a term, often a term based on the actual language of the participant, called an in vivo term.

Guest and colleagues (2012) discussed and illustrated the use of codebooks in qualitative research. The intent of a codebook is to provide definitions for codes and to maximize coherence among codes—especially when multiple coders are involved. This codebook would provide a list of codes, a code label for each code, a brief definition of it, a full definition of it, information about when to use the code and when not to use it, and an example of a quote illustrating the code.

It is the process of organizing the transcript data by bracketing chunks of text and writing a word representing the text. It involves segmenting sentences or paragraphs into categories, and labeling those categories with a term, often a term based on the actual language of the participant, called an in vivo term.

The basic premise of this book is that qualitative researches are not the same, and, over time, variations in procedures of conducting qualitative inquiry has evolved. This book discusses five approaches to qualitative research: (a) narrative research, (b) phenomenology, (c) grounded theory, (d) ethnography, and (e) case studies. A process approach is taken throughout the book in which the reader proceeds from broad philosophical assumptions and on through the steps of conducting a qualitative study (e.g., developing research questions, collecting and analyzing data, and so forth). The book also presents comparisons among the different qualitative approaches so that the researcher can make an informed choice about what strategy is best for a particular study.

This is an eight-volume kit that is authored by different world-class qualitative researchers and was created to collectively address the core issues that arise when writing a qualitative research. It addresses how to plan and design a qualitative study, the collection and production of qualitative data, the analysis of data (e.g., visual data, discourse analysis), and the issues of quality. Overall, it presents a recent, up-to-date window into the field of qualitative research.

This book provides a practical and detailed study of themes and data analysis in qualitative research. It contains detailed passages about the development of codes, codebooks, and themes, as well as approaches to enhancing the validity and reliability in qualitative research. It explores data reduction techniques and a comparison of themes. It presents useful information about qualitative data analysis software tools as well as procedures for integrating quantitative and qualitative data

They introduced the procedures for designing a qualitative study and a qualitative proposal. The topics covered are comprehensive. These include building a conceptual framework around a study; the logic and assumptions of the overall design and methods; methods of data collection and procedures for managing, recording, and analyzing qualitative data; and the resources needed for a study, such as time, personnel, and funding. This is a comprehensive and insightful text from which both beginners and more experienced qualitative researchers can learn.