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Observational studies observe natural phenomena without intervention, while experimental studies manipulate variables to determine cause and effect. Observational studies are useful for understanding associations, while experimental studies can establish causal relationships between variables. Experimental studies involve random assignment of participants to groups, while observational studies rely on natural groupings.
Some common methods of study in psychology include experimental research, surveys, case studies, and observational studies. Experimental research involves manipulating variables and measuring their effects on behavior. Surveys collect data from a large sample of participants through questionnaires. Case studies involve in-depth analysis of a single individual or group. Observational studies involve observing and recording behaviors in natural settings.
Observational studies can provide valuable insights, but they have limitations. They can suggest associations between factors, but cannot prove causation. Factors like confounding variables and biases can impact the reliability of observational studies. It is important to interpret their results cautiously and consider other types of studies for more robust evidence.
Observational studies allow researchers to directly observe children's behaviors and interactions in natural settings. This method can provide valuable insights into real-life behavior, reactions, and development without the constraints of a lab setting. Observational studies can help researchers understand how children learn, interact, and develop in everyday contexts.
Psychoanalytic observational studies involve closely observing individuals' behaviors, thoughts, and emotions within a psychoanalytic framework to gain insights into the unconscious motivations underlying their behaviors. These studies aim to understand the development of personality, relationships, and mental health through the lens of psychoanalytic theory pioneered by Freud. Observational methods such as free association, dream analysis, and transference play key roles in these studies.
In a controlled experiment, researchers manipulate variables to observe their effect on outcomes, while in an observational study, researchers observe natural variations in variables without manipulating them. Controlled experiments allow for stronger causal inferences compared to observational studies because they can establish cause-and-effect relationships.
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observational studies
Data will be either qualitative (non numerical description) or quantative (numerical values assigned to a property). To give you an example, a meterologist may describe the sky on a particular day as cloudy (qualitative) with a 5 mile per hour wind (quantative). Studies can be classified as experimental studies or observational studies. The experimental study means that the scientist is able to treat or alter in some way the population. Medical studies of drugs frequently conduct experimental studies and collect experimental data. Observational studies, we collect data without altering the population. A good example is astronomical studies, where it is impossible to alter the population. Scientific studies need to be thorough investigations relying on good data and sufficient quantity of data in order to reach conclusions.
Surveys or studies that involve collection of data can be categorized as either observational or experimental. The experimental study occurs in a very controlled environment where some treatment is applied to the subjects. Data collection measures the change in some attributes of subjects after treatment. Wikipedia terms observational studies as "uncontrolled experimental studies." See related link. Observational studies can be more difficult as follows: 1. The controlled environment may be missing. Suppose I am asking people if they like a particular product. Some may have used this product, others may have heard bad things about it from friends. The influences can be numerous. 2. The means of obtaining a representative sample may be complicated. Suppose I am interested in determining if a particular pollutant is causing any harm. I would go to an area where the pollutant was the highest and examine people complaining of problems. Perhaps other pollutants are higher in this particular area. I have confounding problems. 3. The observational study often suffers from an inability to do "identical, repeated trials" as it does not initiate a particular treatment. This inability can result in erroneous conclusions, particularly when data is scarce and develops over time. This is particularly true in epidemiology studies, where the area to be studied and the time required to reach a conclusion depend on the phenomena being studied. If the disease is changing with time, it may be impossible to reach a conclusion even after many incidences have occurred. Does this mean we should just rely on experimental data? No, because in many areas which involve spatial analysis (astronomy, mining of minerals, epidemiology), experiments are not possible. Many disease studies depend on both experimental data and observational surveys.
A person who studies reasons for rising and falling populations is a Demographer
The main possible advantage is that in an experiment, it is possible to control some of the variables so that it is easier to measure the effect of key variables. In observational studies, no such control is possible.
Observational techniques, typically, place the user in the eventual context in which a system will be operated. In contrast, lab-based techniques rely upon careful control of variables that might otherwise confound experimental results. Lab based studies can be used to make direct and fair comparisons between different systems using statistical measures of significance . In contrast, observational studies provide rich insights into the application of an interactive system but it can be difficult to make such direct comparisons when the experience of interactive with the system can be influenced by a host of factors that are difficult to replicate for each system within the eventual context of use.
Observational studies
If the observer and the observing equipment are unbiased then there is no reason for the study to be biased.
In an experiment investigators apply treatments to experimental units (people, animals, plots of land, etc.) and then proceed to observe the effect of the treatments on the experimental units. n an observational study investigators observe subjects and measure variables of interest without assigning treatments to the subjects. The treatment that each subject receives is determined beyond the control of the investigator. For example, suppose we want to study the effect of smoking on lung capacity in women. Summary: 1.The main difference between observational study and experiments is in the way the observation is done. 2.In an experiment, the researcher will undertake some experiment and not just make observations. In observational study, the researcher simply makes an observation and arrives at a conclusion. 3.In observational study, no experiment is conducted. In this type of study the researcher relies more on data collected. 4.In an experiment, the researcher observes things through various studies. 5.There is human intervention in experiments whereas there is no human intervention in observational study. 6.Hawthorne studies are a good example for experiments. 7.The study to determine the relation between smoking and lung cancer is a typical example for observational study.
The study of information related to people and populations is "social studies".
Cause and effect conclusions can be drawn from experimental studies, where researchers manipulate an independent variable to observe its effect on a dependent variable. Correlational studies, on the other hand, can only show associations between variables but not causation.