Contents
Proposals and Research Methodology
Rationale
Research is a human activity based on intellectual investigation and aimed at discovering, interpreting, and revising human knowledge on different aspects of the world. It can be scientific or not scientific.
Scientific research relies on the application of scientific methods based on scientific paradigm. This research provides scientific information and theories for the explanation of the nature and properties of humans and the whole Universe. It makes practical applications possible.
Scientific research is funded by public authorities, by charitable organisations and by private groups, including many companies.
The term research is also used to describe an entire collection of information about a particular subject.
Scientific research is the subject of different classifications.
- Academic conference
- Advertising Research
- Demonstrative evidence
- Empirical research
- European Charter for Researchers
- Internet research
- Innovation
- Lab notebook
- Marketing research
- Open research
- Operations research
- Original research
- Participatory action research
- Psychological research methods
- Research and development
- Social research
Research Process. Generally, research is understood to follow a certain structural process. Though step order may vary depending on the subject matter and researcher, the following steps are usually part of most formal research, both basic and applied:
- Formation of the topic
- Hypothesis
- Conceptual definitions
- Operational definitions
- Gathering of data
- Analysis of data
- Conclusion, revising of hypothesis
A common misunderstanding is that by this method a hypothesis can be proven. Generally a hypothesis is used to make predictions that can be tested by an observing the outcome of an experiment. If the outcome is inconsistent with the hypothesis, then the hypothesis is rejected. However, if the outcome is consistent with the hypothesis, the experiment is said to support the hypothesis. This careful language is used because researchers recognize that alternative hypotheses may also be consistent with the observations. In this sense, a hypothesis can never be proven, but rather only supported by surviving rounds of scientific testing and, eventually, becoming widely thought of as true (or better, predictive), but this is not the same as it having been proven.
A useful hypothesis allows prediction and within the accuracy of observation of the time, the prediction will be verified. As the accuracy of observation improves with time, the hypothesis may no longer provide an accurate prediction. In this case a new hypothesis will arise to challenge the old, and to the extent that the new hypothesis makes more accurate predictions than the old, the new will supplant it.
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Teaching and Learning Resources
Introduction. Reseach Process. Research Methods
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Concept Mapping is a technique for visualizing the relationships between different concepts. A concept map is a diagram showing the relationships between concepts. Concepts are connected with labelled arrows, in a downward-branching hierarchical structure. The relationship between concepts is articulated in linking phrases, e.g., "gives rise to", "results in", "is required by," or "contributes to".
- Concept
Mapping Website
- Free Concept Mapping Resources to help teachers introduce young children to the ideas of Concept Mapping.
- Wiki dedicated to conceptmapping
- Concept Mapping Homepage by Jan Lanzing
- "The Theory Underlying Concept Maps and How To Construct Them", Joseph D. Novak, Cornell University
- Italian Site on the Concept Mapping use in the school, by Marco Guastavigna
- Concept Mapping at the Graphic Organizer
- Concept Mapping: A Graphical System for Understanding the Relationship between Concepts
- Concept mapping software
The goal of the research process is to produce new knowledge, which takes three main forms:
- Exploratory research, which structures and identifies new problems
- Constructive research, which develops solutions to a problem
- Empirical research, which tests the feasibility of a solution using empirical evidence
As discussed in the previous section, these forms are not clear-cut.
Research can also fall into two distinct types:
Research Methods used by scholars:
- Action research
- Cartography
- Case study
- Classification
- Experience and intuition
- Experiments
- Interviews
- Mathematical models
- Participant observation
- Simulation
- Statistical analysis
- Statistical surveys
- Content or Textual Analysis
- Ethnography
Research is often conducted using the hourglass model.[1] The hourglass model starts with a broad spectrum for research, focusing in on the required information through the methodology of the project (like the neck of the hourglass), then expands the research in the form of discussion and results.
Research
Proposal. Research Problem. Secondary Data.
Tutorials
| Problem Definition |  |
| Problem Definition and Research Proposal | |
| Secondary Data | |
Readings
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Survey
Research, Questionnaires. Sampling.
Tutorials
| Survey Research | |
| Observation & Experimentation | |
| Measurement & Questionnaire Design | |
| Sampling & Fieldwork | |
Readings
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A questionnaire is a research instrument consisting of a series of questions and other prompts for the purpose of gathering information from respondents. Although they are often designed for statistical analysis of the responses, this is not always the case. The questionnaire was invented by Sir Francis Galton.
Questionnaires have advantages over some other types of surveys in that they are cheap, do not require as much effort from the questioner as verbal or telephone surveys, and often have standardized answers that make it simple to compile data. However, such standardized answers may frustrate users. Questionnaires are also sharply limited by the fact that respondents must be able to read the questions and respond to them. Thus, for some demographic groups conducting a survey by questionnaire may not be practical.
As a type of survey, questionnaires also have many of the same problems relating to question construction and wording that exist in other types of opinion polls.
Sampling is that part of statistical practice concerned with the selection of an unbiased or random subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for the purposes of making predictions based on statistical inference. Sampling is an important aspect of data collection.
Researchers rarely survey the entire population for two reasons (Adèr, Mellenbergh, & Hand, 2008): the cost is too high, and the population is dynamic in that the individuals making up the population may change over time. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data.
Each observation measures one or more properties (such as weight, location, color) of observable bodies distinguished as independent objects or individuals. In survey sampling, survey weights can be applied to the data to adjust for the sample design. Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population.[1]
- Process
- Population definition
- Sampling frame
- Probability and nonprobability sampling
- Sampling methods
- Replacement of selected units
- Sample size
- Sampling and data collection
- Errors in sample surveys
- Survey weights
- History
- Acceptance sampling
- Data collection
- Official statistics
- Replication (statistics)
- Sample (statistics)
- Sample size rule of thumb for estimate of population mean
- Sampling (case studies)
- Sampling error
- Gy's sampling theory
- Horvitz–Thompson estimator
- Notes
- References
Analysis.
Statistics.
Tutorials
| Coding & Descriptive Statistics | |
| Univariate Statistics | |
| Bivariate Statistics | |
| Multivariate Statistics | |
Readings
Descriptive Statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data. Various techniques that are commonly used are classified as:
- Graphical description in which we use graphs to summarize data.
- Tabular description in which we use tables to summarize data.
- Summary statistics in which we calculate certain values to summarize data.
In general, statistical data can be described as a list of subjects or units and the data associated with each of them. Although most research uses many data types for each unit, we will limit ourselves to just one data item each for this simple introduction.
We have two objectives for our summary:
We want to choose a statistic that shows how different units seem similar. Statistical textbooks call the solution to this objective, a measure of central tendency.
We want to choose another statistic that shows how they differ. This kind of statistic is often called a measure of statistical variability.
When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the arithmetic mean, the medianor the mode. Sometimes, we choose specific values from the cumulative distribution function called quantiles.
The most common measures of variability for quantitative data are the variance; its square root, the standard deviation; the range; interquartile range; and the average absolute deviation (average deviation).
See also
- statistical regularity
- planning statistical research
- statistical inference
- inferential statistics
- summary statistics
- data mining
External links
- Descriptive Statistics Lecture: University of Pittsburgh Supercourse: http://www.pitt.edu/~super1/lecture/lec0421/index.htm
- http://www.socialresearchmethods.net/kb/statdesc.php
Write-Up
Tutorials
Readings
Recommended Texts
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The Business of Reseach - Issues of Policy and Practice Jones Finer C., Lewando Hundt G. (2001) The Business of Research: Issues of Policy & Practice, Oxford: Blackwell Publishers. (ISBN: 0-631-22824-1) pp. 160 Check the availability and buy your books from our Bookshop. |
