Elements of Research
He argued the case for limiting the use of the concept of racism to ideology on the spurious relationships, and a loose — even contradictory — logical structure. 3 Correlation and Causation; 4 Quantitative and Qualitative; 5 Objective vs. . The operational definition of a thing often relies on comparisons with standards: . in the ways people occupying different racial, classed, gendered, sexual, religious, . between variables are found but the relationship turns out to be spurious. A positive relation means that as values of one variable increase, For example, gender and race precede political socialization and other political phenomena. A spurious relationship results when the impact of a third variable explains the.
As a reminder, the direction of a relationship refers to positive or negative relations between variables. A positive relation means that as values of one variable increase, or decrease, values of the other variable also increase, or decrease.
A negative relationship means that as values of one variable increase, or decrease, values of the other variable change in the opposite direction. The magnitude of a relationship between variables is also important when considering causality.
The magnitude of a relationship is the extent to which variables change together in one direction or the other. The highest magnitude of relationship is a perfect relationship, in which knowledge of the value of the independent variable determines the exact value of the dependent variable. On the other hand, the lowest magnitude of relationship, the zero relationship, occurs when systematic change between the values of an independent variable and a dependent variable is not discernable.
There are four formal criteria that are necessary to establish that a relationship is causative: The assumption here is that longer the hair, higher the scores.
Introduction to Sociology/Sociological Methods
However, the lurking factor here may be that female students got better, may be because they worked harder and more sincerely than the guys. Or perhaps, they were seniors who already had some experience due to which they fared better.
People assume that the more they read, they outgrow their shoes, or their shoes don't fit them as they read better. How wrong, how wrong. The very obvious factor here is age. As they grow bigger, they tend to develop their reading ability. Along with mental skills, their bodies undergo a change as well, and their feet grow bigger, which is why they outgrow their shoes. Truth be told, it is the fact that eating excessively causes them to be lethargic and lazy, which is why they are not into sports and other activities, which makes them clumsy and obese.
The safety factor here is the security measures for public and private grounds and parks. The connection assumed here is that the more safety measures in place, the fatter the kids get.
Predictions refer to experimental designs with a currently unknown outcome. A prediction of an unknown differs from a consequence which can already be known.
Testing[ edit ] Once a prediction is made, a method is designed to test or critique it. The investigator may seek either confirmation or falsification of the hypothesis, and refinement or understanding of the data.
Though a variety of methods are used by both natural and social scientists, laboratory experiments remain one of the most respected methods by which to test hypotheses. Scientists assume an attitude of openness and accountability on the part of those conducting an experiment. Detailed record keeping is essential, to aid in recording and reporting on the experimental results, and providing evidence of the effectiveness and integrity of the procedure.
They will also assist in reproducing the experimental results. This is a diagram of the famous Milgram Experiment which explored obedience and authority in light of the crimes committed by the Nazis in World War II.
The experiment's integrity should be ascertained by the introduction of a control or by observation of existing controls in natural settings. In experiments where controls are observed rather than introduced, researchers take into account potential variables e. On the other hand, in experiments where a control is introduced, two virtually identical experiments are run, in only one of which the factor being tested is varied.
This serves to further isolate any causal phenomena. For example in testing a drug it is important to carefully test that the supposed effect of the drug is produced only by the drug.
Doctors may do this with a double-blind study: Neither the patients nor the doctor know who is getting the real drug, isolating its effects. This type of experiment is often referred to as a true experiment because of its design.
Spurious Correlation Explained With Examples
It is contrasted with alternative forms below. Once an experiment is complete, a researcher determines whether the results or data gathered are what was predicted or assumed in the literature beforehand. If the experiment appears successful - i. An experiment is not an absolute requirement. In observation based fields of science actual experiments must be designed differently than for the classical laboratory based sciences.
Sociologists are more likely to employ quasi-experimental designs where data are collected from people by surveys or interviews, but statistical means are used to create groups that can be compared. For instance, in examining the effects of gender on promotions, sociologists may control for the effects of social class as this variable will likely influence the relationship.
Unlike a true experiment where these variables are held constant in a laboratory setting, quantitative sociologists use statistical methods to hold constant social class or, better stated, partial out the variance accounted for by social class so they can see the relationship between gender and promotions without the interference of social class. The four components of research described above are integrated into the following steps of the research process. Identify your topic of interest and develop a research question in the form of a cause-and-effect relationship.
Conduct a review of the literature: Access studies that have already been performed by other researchers and published in peer-reviewed journals. You'll find out what is already known about the topic and where more research is needed. Refine your research question in a way that will add new information to the existing research literature, expressing it in the form of a testable research hypothesis.
This includes identifying two or more variables and articulating how one variable is thought to influence the other. Decide on a way to approach data collection that will provide a meaningful test of the research hypothesis. Some designs include data collection at only one point in time, but more complex questions require data gathering over time and with different groups of people.
Select a research method: Once a design has been established, one or more actual data gathering strategies will need to be identified. Each method comes with its own strengths and weaknesses, so sociologists are increasingly incorporating mixed-methods approaches in their research designs to enrich their knowledge of the topic. Some of the more popular research methods used by sociologists are: Operationalizing means deciding exactly how each variable of interest will be measured.
In survey research, this means deciding on the exact wording of the question or questions used to measure each variable, a listing of all possible responses to closed-ended questions, and a decision as to how to compute variables using multiple indicators. Identify the population and draw a sample: A population is the group a researcher is interested in learning about.
Is it all students at one particular University? All residents of the United States? All nonprofit organizations in a particular city? Because it is frequently too expensive to try to collect data from all units in a population, a sample of those units is often selected.
Samples that use principles of random selection, where every unit in the population has an equal chance of being included in the sample, have the best chance of reflecting the views and behaviors of the entire population of focus. Data collection must be systematic and rigorous so that procedural mistakes do not create artificial results. Powerful statistical packages today make data analysis easier than it has ever been.
Still, great care needs to be taken to accurately code the data i. Research results are shared with the larger community through presentations, reports, and publications in peer-reviewed journals. This allows others to consider the findings, the methods used, and any limitations of the study.
Qualitative sociologists generally employ observational and analytic techniques that allow them to contextualize observed patterns in relation to existing hierarchies or assumptions within natural settings.
Thus, while the true experiment is ideally suited for the performance of quantitative science, especially because it is the best quantitative method for deriving causal relationships, other methods of hypothesis testing are commonly employed in the social sciences, and qualitative methods of critique and analysis are utilized to fact check the assumptions and theories created upon the basis of "controlled" rather than natural circumstances.
Evaluation and Iteration[ edit ] The scientific process is iterative. At any stage it is possible that some consideration will lead the scientist to repeat an earlier part of the process. For instance, failure of a hypothesis to produce interesting and testable predictions may lead to reconsideration of the hypothesis or of the definition of the subject. It is also important to note that science is a social enterprise, and scientific work will become accepted by the community only if it can be verified and it "makes sense" within existing scientific beliefs and assumptions about the world when new findings complicate these assumptions and beliefs, we generally witness paradigm shifts in science .
Spurious Correlation Explained With Examples
All scientific knowledge is in a state of flux, for at any time new evidence could be presented that contradicts a long-held hypothesis, and new perspectives e. For this reason, scientific journals use a process of peer reviewin which scientists' manuscripts are submitted by editors of scientific journals to usually one to three fellow usually anonymous scientists familiar with the field for evaluation.
The referees may or may not recommend publication, publication with suggested modifications, or, sometimes, publication in another journal. Sometimes peer review inhibits the circulation of unorthodox work, and at other times may be too permissive. The peer review process is not always successful, but has been very widely adopted by the scientific community.
The reproducibility or replication of quantitative scientific observations, while usually described as being very important in a scientific method, is actually seldom reported, and is in reality often not done. Referees and editors often reject papers purporting only to reproduce some observations as being unoriginal and not containing anything new. Occasionally reports of a failure to reproduce results are published - mostly in cases where controversy exists or a suspicion of fraud develops.
The threat of failure to replicate by others as well as the ongoing qualitative enterprise designed to explore the veracity of quantitative findings in non-controlled settingshowever, serves as a very effective deterrent for most quantitative scientists, who will usually replicate their own data several times before attempting to publish.
Sometimes useful observations or phenomena themselves cannot be reproduced in fact, this is almost always the case in qualitative science spanning physical and social science disciplines.
They may be rare, or even unique events. Reproducibility of quantitative observations and replication of experiments is not a guarantee that they are correct or properly understood. Errors can all too often creep into more than one laboratory or pattern of interpretation mathematical or qualitative utilized by scientists. Correlation and Causation[ edit ] This diagram illustrates the difference between correlation and causation, as ice cream consumption is correlated with crime, but both are dependent on temperature.
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Thus, the correlation between ice cream consumption and crime is spurious. In the scientific pursuit of quantitative prediction and explanation, two relationships between variables are often confused: While these terms are rarely used in qualitative science, they lie at the heart of quantitative methods, and thus constitute a cornerstone of scientific practice.
Correlation refers to a relationship between two or more variables in which they change together. A positive correlation means that as one variable increases e. A negative correlation is just the opposite; as one variable increases e.
Causation refers to a relationship between two or more variables where one variable causes the other. In order for a variable to cause another, it must meet the following three criteria: Ice cream consumption is positively correlated with incidents of crime. Employing the quantitative method outlined above, the reader should immediately question this relationship and attempt to discover an explanation. It is at this point that a simple yet noteworthy phrase should be introduced: If you look back at the three criteria of causation above, you will notice that the relationship between ice cream consumption and crime meets only one of the three criteria they change together.
The real explanation of this relationship is the introduction of a third variable: Ice cream consumption and crime increase during the summer months.
Thus, while these two variables are correlated, ice cream consumption does not cause crime or vice versa.