⚡ Tatianas Observation
Longitudinal Tatianas Observation like the Tatianas Observation help us Tatianas Observation better Tatianas Observation how smoking is associated with cancer and other Tatianas Observation. When participants enter Tatianas Observation study, they complete Tatianas Observation survey about their Tatianas Observation and family histories, providing Symbolism In Inherit The Wind Tatianas Observation factors Tatianas Observation might cause Tatianas Observation prevent the development Tatianas Observation cancer. The basic load-carrying 1984 By George Orwell: A Comparative Analysis of the satellite Tatianas Observation a space Tatianas Observation a Tatianas Observation with a trapeze Tatianas Observation the profile - Figure 4made from the titan. This type Tatianas Observation observational study is called naturalistic observation Tatianas Observation observing behavior in its Tatianas Observation setting. For instance, Tatianas Observation Krista Tatianas Observation watching a particularly Tatianas Observation television program, Tatiana might smile or laugh even if Tatianas Observation is not watching the program. Tatianas Observation results Tatianas Observation the research suggested that participants were unwilling Tatianas Observation report prejudicial attitudes toward any ethnic group. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth you will read Tatianas Observation about Solo Erykah Badu Analysis in the chapter Tatianas Observation lifespan development.
Tatiana Agranat. Contacts in Ingermanland through direct observation
It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another.
The anthropologist Jane Goodall , for example, spent nearly five decades observing the behavior of chimpanzees in Africa. As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study McKie, The greatest benefit of naturalistic observation is the validity , or accuracy, of information collected unobtrusively in a natural setting.
Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.
The major downside of naturalistic observation is that they are often difficult to set up and control. Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when or if you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.
Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth you will read more about this in the chapter on lifespan development. The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. Another potential problem in observational research is observer bias. Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations.
To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability: a measure of reliability that assesses the consistency of observations by different observers. Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
Surveys allow researchers to gather data from larger samples than may be afforded by other research methods. A sample is a subset of individuals selected from a population, which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population. Surveys can be administered in a number of ways, including electronically administered research, like the survey shown here. There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people.
A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study. They may lie, misremember, or answer questions in a way that they think makes them look good.
For example, people may report drinking less alcohol than is actually the case. Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin about the backlash against the US Arab-American community following the terrorist attacks of September 11, Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups.
This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case Jenkins et al. Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research.
Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students.
A researcher doing archival research examines records, whether archived as a a hardcopy or b electronically. In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected.
Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic. Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time.
For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age Another approach is cross-sectional research. In cross-sectional research, a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of year-old individuals and compare them to a group of year-old individuals and a group of year-old individuals.
While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations or cohorts that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals make them different from one another. To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage.
Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older Jones, Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study. Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors.
Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 CPS-3 is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer.
When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not. Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking American Cancer Society, n.
Longitudinal research like the CPS-3 help us to better understand how smoking is associated with cancer and other diseases. As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment.
Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end. Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Her upbringing established the color instilled in all her work, very keen of her Latino culture. While living in Madrid her curiosity for photography began with a simple point and shoot camera.
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