This question can only be addressed by correlational studies. In order to do an experiment, the researcher would have to randomly assign some children to a group that gets abused; others to a group that does not get abused. Obviously, this cannot be done! Thus, we must be cautious about assuming the cause of any association between experiencing abuse as a child and perpetrating it as an adult.
Correlational studies do not support one interpretation over others. A health magazine reports that depressed people who continue medication for at least six months are less likely to relapse than are people who take medication for less than six months. What would you need to know about the design of this study, in order to interpret the report? Enough information to see whether it was a correlational study or an experiment. In a correlational study, the researcher would take advantage of the fact that some depressed people stay on medication longer than others.
The researcher does not control how long people are on medication. Suppose the researcher finds that people on medication more than six months are less likely to relapse. The researcher cannot conclude that the increased time on medication improved the relapse rate because other explanations have not been ruled out.
Perhaps people who stay on medication longer differ from the others in ways that would protect them from relapse. Maybe the people on medication longer are also more likely to receive psychotherapy. In an experimental study, the researcher controls how long people stay on medication. Half of a sample of depressed people is randomly chosen to receive medication for less than six months; the others receive medication for more than six months.
The only way the two groups differ is in the duration of the medication. A private school advertises that a group of their students recently scored 10 points higher on a math test than a group of other students from a public school? What can you conclude from this advertisment? Is this an example of an experiment? We cannot conclude anything about the cause of the difference in scores between the two groups. This is not an experiment because the researcher did not control group membership to ensure that the groups were roughly equivalent when they started school.
In a correlation study, there might be other influences on the variables that make it hard to measure how strong the relationship between the two really is. Experimental studies are often more expensive and difficult to run. Correlation studies can explore a relationship to see if it is worth the later expense of a controlled experiment, as well as study a larger data set than may be feasible in an experiment.
Some researchers will use both methods in a study, conducting an experiment and then carrying out correlation analysis on the results. Andrew Gellert is a graduate student who has written science, business, finance and economics articles for four years. He was also the editor of his own section of his college's newspaper, "The Cowl," and has published in his undergraduate economics department's newsletter.
Regardless of how old we are, we never stop learning. Classroom is the educational resource for people of all ages. Based on the Word Net lexical database for the English Language. In an experimental study, the independent variable is the factor that the experimenter controls and manipulates.
This variable is hypothesized to be the cause of a particular outcome of interest. The dependent variable, on the other hand, depends on the independent variable, and will change or not because of the independent variable. The dependent variable is the variable that we want to measure as opposed to manipulate. In a simple experiment, a researcher might hypothesize that cookies will make individuals complete a task quicker.
In one condition, participants will be offered cookies if they complete a task, while in another condition they will not be offered cookies. In this case the presence of a reward receiving cookies or not is the independent variable, and the time taken to complete the task is the dependent variable.
Effect of a Reward : Effects of receiving a cookie as a reward independent variable on time taken to complete task dependent variable. As shown in the figure, participants who received a cookie took much less time to complete the task than participants who did not receive a cookie. An experiment can have more than one independent variable. A researcher might decide to test the hypothesis that cookies will make individuals work harder only if the task is easy to begin with.
In this case, both the presence of a reward and the difficulty of the task would be independent variables. The purpose of an experiment is to investigate the relationship between two variables to test a hypothesis. By using the scientific method, a psychologist can plan and design an experiment that will answer the research question.
The basic steps of experimental design are:. The Scientific Method : The scientific method is the process by which new scientific knowledge is gained and verified. First you must identify a question and, after some preliminary research, form a hypothesis to answer that question. After designing an experiment to test the hypothesis and collecting data from the experiment, a scientist will draw a conclusion. The conclusion will either support the hypothesis or refute it.
The scientist will then either reformulate the hypothesis or build upon the original hypothesis. The scientific method cannot prove a hypothesis, only support or refute it. A poorly designed study will not produce reliable data. When a study is designed properly, the only difference between groups is the one made by the researcher.
Control groups are used to determine if the independent variable actually affects the dependent variable. The control group demonstrates what happens when the independent variable is not applied. The control group helps researchers balance the effects of being in an experiment with the effects of the independent variable. This helps to ensure that there are no random variables also influencing behavior.
In an experiment monitoring productivity, for instance, it was hypothesized that additional lighting would increase productivity in factory workers. When workers were observed in additional lighting they were more productive, but only because they were being watched. If a control group was also observed with no additional lighting this effect would have been obvious. To minimize the chances that an unintended variable influences the results, subjects must be assigned randomly to different treatment groups.
Random assignment is used to ensure that any preexisting differences among the subjects do not impact the experiment. Theoretically, the baseline of both the experimental and control groups will be the same before the experiment starts. Therefore, if there is a difference in the behavior of the two groups at the end of the experiment, the only reason would be the treatment given to the experimental group. In this way, an experiment can prove a cause-and-effect connection between the independent and dependent variables.
If the experimenter inadvertently interprets the information in a way that supports the hypothesis when other interpretations are possible, it is called the expectancy effect. To counteract experimenter bias, the subjects can be kept uninformed on the intentions of the experiment, which is called single blinding. If the people collecting the information and the participants are kept uninformed, then it is called a double blind experiment.
By using blinding, a researcher can eliminate the chances that they are inadvertently influencing the outcome of the experiment. When running an experiment, a researcher will want to pay close attention to their design to avoid error that can be introduced by not balancing the conditions properly. Consider the following example. You are running a study in which participants complete a task of pressing button A with their left hand if they see a green light and pressing button B with their right hand if they see a red light.
You find support for your hypothesis that red stimuli are processed more quickly than green stimuli. However, an alternative explanation is that people are faster to respond with their right hand simply because most people are right-handed.
In this manner, you are anticipating and controlling for this extra source of error in your design. One of the main strengths of experimental research is that it can often determine a cause and effect relationship between two variables. Another strength of experimental research is the ability to assign participants to different conditions through random assignment. Randomly assigning participants to conditions ensures that each participant is equally likely to be assigned to one condition or another, and that there are no differences between experimental groups.
Although experimental research can often answer the causality questions that are left unclear by correlational studies, this is not always the case. Sometimes experiments may not be possible or ethical. Consider the example of the studying the correlation between playing violent video games and aggressive behavior.
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