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essays on experimental designs
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Experimental designs
Experimental designs are viewed as the most accurate, and most demanding of research designs, requiring strict attention to rules and procedures. Researchers use these research designs to manipulate and control testing procedures as a way to understand a cause and effect relationship. Commonly, independent variables are manipulated to judge or decide their effect on a dependent variable (Trochim & Donnelly, 2008).
In order for an experiment to be considered a true experimental design, the design must fit specific criteria. The researcher must have a hypothesis for a cause and effect relationship between variables, the treatment group, the control group, random selection for the treatment group, and random assignment for the control group. In a simple experiment, the researcher forms two groups that are similar or equivalent, through probability, to each other in every way possible appropriate to the concept of experiment. The treatment group receives the procedure for the experiment and the control group does not. Therefore, the only difference between the groups will be that one group receives the treatment for the experiment and one group does note. After the experiment is conducted the researcher analysis the results in both groups.
An important part of an experiment is random assignment. If the participants for the study are randomly assigned to create two groups, and the researcher has enough participants in the study to have the desired “probabilistic equivalence” (Trochim & Donnelly, 2008, p. 187) then the researcher will feel a sense of confidence that the study will have internal validity in order to assess whether or not the treatment caused the outcome hypothesized. Well-c...
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...not possible to construct (Experiment-Resources.com, 2010).
Experiments and research
The measure of the dependent variable is a significant element in experimental and quasi-experimental designs and allows for comparison of groups. Both designs can show probability of cause and effect relationships, which is important in research (Writing @ CSU, 2010).
Experiment-Resources.com. (2010, July). Types of research design. Retrieved July 17, 2010, from
Experiment- Resources.com: http://www.experiment-resources.com/true-experimental-design.html#ixzz0u5wQkp6b
Trochim, W. M., & Donnelly, J. P. (2008). The research methods knowledge base. Mason, OH: Cengage.
Writing @ CSU. (2010). Differences between experimental and qausi-experiment research. Retrieved July
19, 2010, from Writing @ CSU: http://writing.colostate.edu/guides/research/experiment/pop3e.cfm
Experimental research is the one type of research that allows psychologists to make causal statements. It is where the researcher changes one or more variables that may have an effect on some other variables (King, 2016). The hypothesis is a specific expectation about what is going to happen in the experiment (King, 2016). In the research, the hypothesis was that women would perceive fat talk to be more socially acceptable than men (Katrevich et al., 2014). The other elements of experimental method are dependent and independent variables. The independent variable (IV) is the cause of the results, and it is changed by the experimenter to find the effects, but the dependent vari...
To develop problem solving and experimental skills, for example, information is accurately processed and presented, experimental procedures are planned, designed and evaluated properly, producing valid results, recording results, and valid conclusion is drawn.
Several factors can affect the actual results of an experiment. Among them are experimental and subject bias. Experimental bias concerns anything that misconstrues the experimenter's comprehension of the relationship between the dependent and independent variable (Feldman, 1999). Subject bias is the tendency of the subject to behave atypically. The double-blind procedure evades experimental and subject bias as the experimenter evaluates results unbiased as the experimenter is uninformed about whether the subject has received the actual treatment or the placebo and the subject will behave normally as they do not know if they have received the actual treatment or the pseudotreatment, the placebo. Therefore, the results and any distinctions among the control and experimental groups are clearly based on the independent variable and has to be the effect of the treatment. For example, in an experiment to evaluate a drug that encourages engagement in conversations, after administering the drugs to the experimental group and the placebo to the control group, the experimenters talk with participants and evaluate the conversation's degree of excellence which are not easy to assess. Thus, the experimenter might be biased and unintentionally give the participants in the experimental group better evaluations because they know that this group has been administered the real drug (Carlson & Buskit, 1997).
In order to have a successful, reliable experiment you need sufficient data and evidence, reliable research, variables to test and a follow – up experiment. There are several types of variables you need to do an experiment. An independent variable is the manipulated experimental factor that is changed to see what the effects are. A dependent variable is the outcome. This factor can change in an experiment in reaction to the changes in the independent variable. An experimental group is the group of participants that are exposed to the change that the independent variable represents. The control group is participants who are treated in the same way as the experimental group except for the manipulated factor which is the independent variable (King 24). Proper data, evidence and research is also needed so the experiment turns out correctly and you know what you are testing. A follow – up experiment is not required, however it helps the validity of the conclusion of the experiment. Validity is “the soundness of the conclusions that a researcher draws from an experiment” (King 25). Conducting a follow – up experiment will help researchers and people alike see if the experiment worked properly, continues to help people and see how participants are doing after the experiment is over.
The research design used was between-subjects design. As this was not a true-experiment and instead a quasi-experimental design, meaning that instead of manipulating an independent variable pre-existing differences, such as in the case of this study gender, determine which group the participants are placed in. The dependent variable however was the results collected from the questionnaire. Due to the nature of the design there was no control group.
Going into details of the article, I realized that the necessary information needed to evaluate the experimental procedures were not included. However, when conducting an experiment, the independent and dependent variable are to be studied before giving a final conclusion.
The experimental design of the research involves the organization of an experiment to effectively test the study’s hypothesis. In addition, it involves setting up proper manipulations and measurements of an experiment. To test this specific hypothesis, the researcher will need significant resources, such as direct scanners, to test and analyze the variables. The variables in the study will include the plasticity of the human brain during different life stages and the age differences between individuals. The experimental design includes independent and dependent variables, which the researcher will thoroughly test and
However, a hypothesis cannot function without its independent and dependent variables. They are both parts of an experiment that are in place to be measured and experimented with. Many variables exist, fo...
Randomized Controlled Trials can be used to in several types of evaluations, including new therapies (i.e. Cognitive behavioral therapy versus emotionally focused therapy when treating couples), community interventions, and diagnostic techniques (O'Brien, 2013). The RCT study design randomly assigns participants into an experimental group or a control group. As the study is conducted, the only expected difference between the control and experimental groups is the outcome variable being studied (O'Brien, 2013).
Advantages associated with quantitative descriptive design prompted choosing the design. One advantages of the quantitative descriptive design is accommodation of large amounts of data. For this study, feedback from the students is needed in order to guide decision making and
Quasi-experimental studies have several issues that lead to lack of internal validity of the study. These occur as a result of the experimental conditions not being highly controlled or randomized. This leads to intervention and control groups being nonequivalent leading to issues with study design. This is what is evidenced in the study conducted by Yuan et al. (2009) where five units assigned a number of 8 to 10 voluntary participants to either the experimental or control groups. There is thought to be a risk of bias in assigning participants to the two groups as a result of this. This comes from the random error that occurs on measurements across the two different groups. This random error also affects the statistical conclusion validity
However, since the two differ in their overall goal, their primary interests and methods of receiving a non-random sample differ. In case studies, emphasis is placed on obtaining a representative sample. As MacNealy states, “if several subjects are [being] studied, then the researcher may want to consider how to best achieve a representative sample” (201). A representative sample is key within case studies, because case studies are designed to help build upon preexisting theories and help generate new ones, so it is important that the subjects providing insight actually have some relevance to the study. MacNealy makes this clear when she states, “a researcher will want to select a subject who is typical of some area of interest to begin to collect insights which, when combined with other insights from other empirical projects, could be used to build a general theory” (201). For example, in Engineering Writing/Writing Engineering, Winsor chose her subject, John Phillips, because he is an Engineer, and therefore relevant to her study; her case study can help frame future research within the scope of engineering and writing only because Phillips represents the sample of people within this field. However, in case studies, researchers cannot generalize beyond their representative sample. On the other hand, in quasi-experiments, pretests are of high importance and “research design hypotheses,” in which researchers make generalizations in order to “account for ineffective treatments and threats to internal validity” are crucial (179). Lauer and Asher state that the “quasi-experiment must have at least one pretest or prior set of observations on the subjects in order to determine whether the groups are initially equal or unequal on specific variables tested in the pretest” (179). This practice is seen in Kroll’s Explaining How to Play a Game,”
Design variables are important to be conducted the appropriate experiment analyzing and getting the accurate values for integer, discrete, zero-one (binary), and continuous variables. The researchers should classify design factors before the experiment is conducted. In literature, there are several factors such as quantitative, qualitative, discrete, continuous, zero-one (binary), non-zero-one (non-binary), controlled and uncontrolled variables (Sanchez & Wan, 2009).
The first method to be discussed and analysed are experimental methods. There is a variety of experimental methods including; laboratory, field and natural experiments. These methods are the most scientific method due to them being highly objective and systematic. In addition, this method is regarded as the most powerful research method used in psychology because of the potential to investigate the causes of events and therefore, identifying the cause and effect relationship. When carrying out an experiment the researcher intervenes directly in the situation being investigated. The researcher manipulates an independent variable (IV) in order to investigate whether there is a change in the dependent variable (DV). Any other variables that could have an
According to Mouton, research designs are tailored to address different kinds of research questions. Thus, when attempts are made to classify different kinds of research studies to different design types, they are classified by the kind of research questions they are able to answer. Research designs can be mapped out to the types of research questions (research problem) using four dimensions: 1) empirical versus non-empirical dimension, 2) using primary versus using secondary data, 3) the nature of the data (numerical versus textual data) and 4) the degree of control (structured (laboratory) conditions versus natural field settings)