Inductive theory of research – involves a researcher starting from very specific data and then proceeding towards more general information about the research. For example, studying the culture of a person to understand the culture of the clan from which the person comes.
Deductive theory of research – works in reverse to the inductive theory. I. e. the research begins from a broad perspective and narrows down to individuals as it proceeds.
Epistemological considerations of research try to define the origin nature and scope of knowledge. It uses both positivist approach (scientific study of knowledge) and interpretive approach which deals with how a person interprets of understands a subject.
Ontological considerations of research consider knowledge from a social scientists’ perspective. It evaluates whether a social entity has a positive effect on external actors (objectivism) or if it crops from the social actors themselves or the social construction of the actors (constructionist). This shows that ontological considerations have two opposing positions as it is the case with epistemological considerations.
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Deals with quality of data obtained.
Great analysis to come up with quality information.
Produces in depth data.
Data is manipulated heavily using mathematical formula.
Main objective is high volume data collection.
Minimal data analysis.
Deals with quantity of data.
Employs very few data manipulation using statistical methods.
Characteristics of good research questions
Close relation to subject under research.
Easily framed with simple language.
Politics of social research
Revolving propagandas about the social research.
Is the research a political aspect of the social under research
The political influence of the group on which the study is intended.
Criteria of evaluating social research in terms of validity and reliability
Main objective of the study.
Target group of the study and the reliability of the information that can be drawn from the target group.
Types of research design (factors influencing)
The intended outcome of the research (data obtained).
Scope of the research.
Use of the obtained data.
Ethnic considerations in social research
The ethnic group under study.
Culture of the people under study.
Religion and other factors that might affect the way the people might react towards the study and questions.
Steps in designing a quantitative research
Defining the objective of the research.
Breaking down the research into the five essential steps.
Analyzing each step on its own to ensure it is adequately covered.
Writing down the actual plan of implementation and carrying out the financial budgeting for the whole research.
Implementing the research strategy.
Concepts and their measurements
Since the type of data collected requires statistical analysis for representation, concepts of data representation using graphs is necessary ranging from pie charts, bar graphs and line graphs.
Setting goals in a quantitative research
Goals are set depending on the main objective of the research. This step is carried out in the design stage of the research process. The goals set are mostly in forms of measurements of central tendency, measures of dispersion or distribution of data.
Critique of the research
This is does to determine whether the research is appropriate and the intended data obtained. It also dictates the effectiveness of the research in general.
Types of interviews
They largely depend on the target group and the type of data expected. The two common types are oral and written interviews. In both, close ended or open ended interviews modes may be used.
Characteristics of a good interview
Target group is reached and addressed accordingly.
Questions asked are relevant to the main objective of the research.
Questions are structured in the correct manner to avoid ambiguity.
Advantages and disadvantages of structured interviews
Related to the target group.
Advantages and disadvantages of open and close ended questions
Gives flexibility to the interviewee
Allows the interviewer to gather a lot of information
Prone to ambiguity
Lack precision and clarity.
Highly specific answers.
Information gathered is precise.
Makes the people fear due to lack of flexibility.
Rules of designing questions (factors considered).
Amount of data required.
Designing a questionnaire and pre-testing (factors considered).
Scope of the questionnaire.
The necessary questions which is dictated by the intended information to be gathered.
Types of questions to ask in the interview.
Target group of the research.
Helps analyze the validity of the questions and the possible data to be obtained.
Helps access the overall aftermath of the process. (Hudson, 2011)
Secondary data analysis
Other sources: journals, magazines, historical data and previously obtained results of a similar research.
Advantages and disadvantages of secondary data
Ease the research process.
Guides the researchers to obtaining the expected data.
Guides the whole process of research.
Makes the researcher reluctant since he/she already has the expected results thus is out just to confirm the earlier obtained information from the secondary sources. (Hudson, 2011)
Steps in qualitative research
General preparation for a research.
Setting the necessary goals and ways of obtaining the necessary data.
Data manipulation techniques and representation after the data has been processed.
Reliability and validity of this research
Depends on the data obtained and the sources of data. The validity of the data sources also dictates the validity of the research alongside the set goals of the research.
Main goal and critique
Mainly determined by the set goals in the research objectives. If the set in-depth analysis is done and it proves the hypotheses earlier set, then the research is a success.
The critique mostly supports the validity of the research since it is not any easy task to carry out a qualitative research which is mostly involved in proving certain hypotheses.
Qualitative vs. quantitative research springs back to chapter 1 where the differences in structure and data manipulation in the two research structures are done. (Hudson, 2011)
Ethnography – form of qualitative research design which is aimed at studying the cultural phenomena of a certain group of people.
Role of ethnographers – main role is to gather enough knowledge about the culture and social organization as well as the behavior of a certain group of people.
Access to settings – deals with the actual work of finding the correct cultural background on which to set the whole research thus if a certain cultural setting is accessible, it is possible to study it.
Field notes – help in collection of first hand information from the field and compilation of a research report in the findings section of the report.
Difference between qualitative and quantitative interviewing lies in the depth and spectrum of the focus group. Qualitative interviews digs more about a social phenomenon and mostly employs use of experts in a certain field in social sciences or subject under discussion while quantitative deals with obtaining volumes of data about the subject under research and then analyzing the data so as to draw conclusions.
Focus groups are also called target groups and they are the intended people while preparing an interview to be the interviewees. All the questions are set with them in mind. (Hudson, 2011)
Advantages and disadvantages of focus groups
Simplifies the work of setting and testing of questions.
Ease the access and analysis of the obtained data.
Narrows the study to only a certain group.
Limits data collection.
Ease of collecting wrong data through collusion. (Hudson, 2011)
Types of probability and non-probability samples
Probability of a sample is dictated by the ease of variation. Continuous distribution normally calls for probability samples while discrete distributions call for non-probability manipulation.
Sampling error and reducing non-response
Sampling error is half the sampling interval and defines the deviation from the range in which the sampling is done.
Reducing non-response is a rather tricky aspect which calls for mobilization of more techniques of acquiring information from the target group or data manipulation so as to fit in the required standards.
Measurement of variables deals with how a dependent variable as obtained after data analysis varies with a change in the independent variable. Dependent variable is normally represented in the imaginary axis and the independent on the real axis.
Measures of central tendency deals with the distribution of data around the mean, mode and median. In most cases, the most considered measure of central tendency is around the mean where the data can be evenly distributed, positively skewed or negatively skewed.
Measures of dispersion deals with how any individual element in a data collection is related to the mean of the data. The most common measures of dispersion are variance and standard deviation.
Another measure of dispersion commonly used is regression. This is mostly applied if the dependent variable is affected by more than one independent variable. If the dependent varies with one independent variable, it is called a univariate. If it varies according to two independent variables, it is bivairate and if it varies according to three or more, it is commonly referred to as multivariate (Hudson, 2011).
Strategies in qualitative data analysis. The main theories used are the discourse theory which deals with specific data to evaluate its viability without considering much of the earlier obtained and thematic theory which pairs related data to reduce the bulk and ease analysis.
Grounded theory is a theory evolved from analysis of data which has been collected from research in the field of social sciences.
Narrative analysis is a part of qualitative analysis that deals with how people conceptualize their lives and tell about their lives. (Hudson, 2011)
Content analysis deals with determination of what an aspect of human communications entails and tries to inform about. It includes analysis of books, speeches or even conversations in either qualitative manner or quantitative manner.
Conversational analysis is part of content analysis which deals exclusively with conversations.
Discourse analysis is a content analysis which deals with analyzing both the literal and deep meaning of a sentence or words in a conversation. (Gee, 2005)
Advantages and disadvantages of content analysis
Easy to obtain the required information.
Requires less time to gather enough information in a research.
Helps analyze the validity of data or information which is being passed across.
Depends on intellectual sharpness of the source. (Gee, 2005)
Factors to consider while writing a research
Objectives of the research
Practicability of the research
Data collection and analysis tools.
Type of data to collect.
Affordability of the research.
Structure of a research
Objectives of the research
Data analysis and representation
Gee, J. 2005. An Introduction to Discourse Analysis: Theory and Method. London: Rutledge.
Hudson, M. 2011. Quantitative and qualitative research. Retrieved from http://www. experiment-resources. com