Protected populations of people - Essay Example

Protected populations of people 1. Protected populations are considered to be populations of people who are vulnerable and who need to be extra protected while carrying out any form of research (Creswell, W. J 2003). Groups like women, children and prisoners are termed as protected populations. They are protected since they are vulnerable and may be subjected to some form of coercion so as to produce information against their will. These people need to be allowed the freedom to participate in any research activity at will. They should be allowed free consent. 2. The human being his important than any scientific findings. Thus the human being needs to be protected all the times during research. This protection should originate from the ability to participate in the study at will. A free consent form should be signed by the participants and they should be allowed to terminate their participation at any time whenever they feel that their rights are infringed. 3. Research is done so that the information originating from the research may be used to make tangible decisions (Creswell, W. J 2003). Further, research is done so as to gauge the effectiveness of some control measure e.g. medicine, policy etc. It is also used to gauge people’s perceptions of an activity or performance. Policies and actions should be based on reliable information which originates from research works. 4. Qualitative research is a study aimed at gauging the effectiveness of something while quantitative research aims at getting the exact number of the elements affected or the number of those that are in need of a certain action. Qualitative research will be carried out to see whether a policy has negative or positive effects while a quantitative will confirm the number of those who are affected negatively of positively. A hypothesis is a statement which is to be proved often called the null hypothesis (Creswell, W. J 2003). If the null is rejected, there is the alternative which is called the alternative hypothesis and it takes the part of the null if it is not true. An example of a null hypothesis is: There is no difference in score between males and females in mathematics. The research question will be: Is there any difference between the scores of females and males in mathematics? 5. Sampling is inferential statistics where a sample is collected to explain the traits of a certain population. There are many type of sampling; random sampling where each element has an equal chance of being selected, stratified sampling where the population is put in statas each containing members with the same kind of traits (homogeneous), cluster sampling where members are clustered and then there is systematic sampling where members are selected according to a certain criteria say the kth element. In data collection, several ways exist. A questionnaire is one the ways of collecting data. Questionnaires are the mostly used in data collection due to the fact that; the participant gives more information than he/she would have given in any other method. Also, the designer will have the freedom to control some responses making it easy to analyze the data. The open-ended questions give the researcher an advantage since more information will be delved using them. Further, the participant can answer them at his/her own pace; there is no strict deadline on when to deliver the filled questionnaires (Creswell, W. J 2003). Lastly, a questionnaire has the potential of getting information from a large group of people from all representations. Some participants most likely need to be pushed so as to be able to fill completely all the questions. Also, all questionnaires administered to participants by mailing may fail to reach the researcher at the end thus losing information. In addition, the participant may at times fail to understand the questions properly thus giving the wrong information. Further, since they are mostly filled when the event has already taken place, then the participant may have forgotten very important aspects. The open-ended questions, though important, may produce large amounts of data which may prove difficulty to handle during analysis and evaluation. Lastly, many participants may not understand the seriousness of the study and may fill it jokingly. However, the disadvantages can be dealt with finality if the correct steps are followed by the one evaluating them. Another method is interviews which are conducted either face to face or via the phone. To collect data using interviews is advantageous since, the researcher gets up to date information from the participant. In addition, he/she chooses the right information to record and to use during analysis. Also, during the interviews, the interviewer can set the mood, which may encourage the participant to give more information. In other cases, when the participant gives the wrong information, the interviewer can determine the correctness of the information by watching at the signals of the participant (Creswell, W. J 2003). The interviewer can ask concrete questions since there is the allowance for clarification as well as requesting the participant to clarify on the answers he/she gives. At times, the participants feel probed and may end up not giving the right information but may give what he/she deems fit for the interviewer. Further, if the interviewer is leading, the participant may end up giving non-tangible answers. If it takes long, the participant may not feel good and may end up giving answer anyhow so that the process can end. Also, interviews are expensive to conduct and mostly the phone interviews if they take long which translates to fewer people being interviewed. The third method observations where data is collected based on the participant’s actions by watching what he/she is doing or reacting to a certain scenario. In this case, the researcher can get what he/she deems fit while observing; first hand information which many times is unbiased. Observation leads to better understanding of the situation while collecting information that can be used in making decisions. According to Creswell, W. J (2003), the researcher gets to know what to expect while doing and also experiences what the participant is doing and gets to gauge the participant’s actions and responses. Further, the process of observing provides a think-aloud so that the observer and the participant can go in the same direction. Observations can lead to biased data since the participant might feel overlooked and may tend to perform to the best so as to impress the observer. Other method in use is documentary evidence. 6. Reliability is a measure of how variables are important in the study. It is measured using reliability analysis. It the reliability coefficient of a certain variable is greater than .5, then the variable is reliable. It not, the variable is not reliable and can be dropped from the analysis without effects to the final results. 7. Data validity is the correctness and the responsibleness of data. For example, if one is dealing with dates and names; the dates should follow the right formats without mistakes. Also, the names should be correctly spelled. This is referred to as internal validity. External validity is how the data appears from outside. How the people will view that data is what is termed as external validity. 8. Nomothetic causal relationship states that there is correlation between the dependent and the independent variable. It shows that, the dependent changes as the independent does. Idiographic causal relationship attempts to explain a result from a series of circumstances that are related to one another. Idiographic relationship is more qualitative as it tries to explain an outcome based on related circumstances. 9. A causal relationship is the relationship that exists between tow variables when one variable causes real change to the other variable. Casual relationships are determined by experimental research in order to determine the assertion that, changes in one variable causes changes in another variable for sure and the change is significant. The most important part is whether the change is due to the change in the other variable. 10. Correlation is a measure of how two variables relate, positively or negatively. If the correlation coefficient is less than 0, then the two variables are negatively related. If greater than 0, then positively related with each other. Correlation does not imply that, the relationship is not significant, two variables for example may have a negative correlation between them and be significantly related. 11. Spurious relationship is a kind of relationship where two variables are not correlated in their original manner but the kind of relationship which does exist is due to another third variable. For example, if students in a mathematics class who have long hair have higher scores in end term exam than those who have short hair; may be there would be a correlation between the hair length and the test scores. However, there may be no causal link in that, students who wish to get good grades should let their hair grow. This is an example of a spurious relationship. 12. Grounded theory is a theory that deals with using of empirical data without any form of set data. I can equate this with non-parametric tests where the test is done without regard of whether the data conforms to a certain distribution or not. 13. Literature review add some rigor to any scientific work in that, it shows the reader other works related to yours and what the authors did and established from their findings. Literature review shows some basis of your work. Further, it acts as reference in case one wants to read further or when wants to do related study. 14. Ethical is important if a research work is to have the required scientific rigor or if it is to get the required rating. First of all it is important to respect the participants in the research and understand vulnerable groups and what is expected of you; the researcher. Also, the research tools have to meet the required standards and should be test-retested. After data collection, the data should be safeguarded according to the data protection act of 1998. Ethical issues if well followed to the latter leads to high quality research. 15. Operational definition is a process of identifying an object by distinguishing it from its background of empirical experience. In regard to data collection, it is the getting of data there and then and not depending on the experience of past to determine how a certain population is expected to behave in the future. In mathematics, it is the determination of the operation to use; addition, multiplication, subtraction and division. To operationalize a term is either to add, or to subtract, or to divide or to multiply it with another term; thus operationalize. 16. A variable is a symbolic representation of which is used to denote a certain unknown quantity or expression. Variables allow us to represent things which we are not aware of and things which have no definite representation. Variables are of four types. Discrete variables (countable), continuous variables (measurable), independent variables and the dependent variable. The independent allows us to forecast the dependent if the model is there. 17. A dependent variable is a variable whose outcome depends on another variable called the independent variable. An example of a model is; Y = 4 + 3 X, Here, Y is the dependent variables and depends on X, the independent variable. Reference Creswell, W. J (2003).Research Design: Qualitative, Quantitative, and Mixed Method Approaches. Sage Publications, Inc   Read More