Conducting A Psychology Experiment

Conducting your first psychology experiment can be a long, complicated and intimidating process. Like other sciences, psychology utilizes the scientific method and bases conclusions upon empirical evidence.

1) ASK A QUESTION THAT CAN BE TESTED The first step in conducting any psychology experiment is to come up with a research question or problem.Review psychology literature. Published studies are a great source of unanswered research questions. In many cases, the authors will even note the need for further research. Find a published study that you find intriguing, and then come up with some questions that remain unanswered. Think about everyday problems. An operational definition describes exactly what the

2) OPERATIONALLY DEFINE YOUR VARIABLES VARIABLES are and how they are measured within the context of your study. For example, if you were doing a study on the impact of sleep deprivation on driving performance, you would need to operationally define what you mean by sleep deprivation and driving performance. What is? The main purpose the purpose of operationally defining variables is control. By understanding what your are measuring, you can control for it by holding the variable constant between all of the groups or manipulating it as an independent variable. The next step is to develop

3) TESTABLE HYPOTHESIS that predicts how the operationally defined variables are related. In our example in the previous step, our hypothesis might be: “Students who are sleep deprived will perform worse than students who are not sleep deprived on a test of driving performance.” In order to determine if the results of the study are significant, it is essential to also have a null hypothesis. The null hypothesis is the prediction that one variable will have no association to the other variable. In other words, the null hypothesis assumes that there will be no difference in the effects of the two treatments in our experimental and control groups. The null hypothesis is assumed to be valid unless contradicted by the results. The experimenters can either reject the null hypothesis in favor of the alternative hypothesis or not reject the null hypothesis. It is important to remember that not rejecting the null hypothesis does not mean that you are accepting the null hypothesis. To say that you are accepting the null hypothesis is to suggest that something is true simply because you did not find any evidence against it. This represents a logical fallacy that should be avoided in scientific research.

4) CONDUCT BACKGROUND RESEARCH “Background Research”Before you start your psychology experiment, you need to review the previously existing literature on your topic.Once you have developed a testable hypothesis, it is important to spend some time conducting background research. What do researchers already know about your topic? What questions remain unanswered? You can learn about previous research on your topic by exploring books, journal articles, online databases, newspapers and websites devoted to your topic. Reasons to conduct background research: * Reading previous research helps you gain a better understanding of what you will encounter during your own experiment. * Understanding the background of your topic provides a better basis for your own hypothesis. After conducting a thorough review of the literature, you might choose to alter your own hypothesis. * Background research also allows you to explain why you chose to investigate your particular hypothesis and articulate why the topic merits further exploration. As you research the history of your topic, remember to take careful notes and create a working bibliography of your sources. This information will be valuable when you begin to write up your experiment results.

5) SELECT AN EXPERIMENTAL DESIGN”EXPERIMENTAL DESIGN” DESIGN A STUDY AND COLLECT DATA After conducting background research and finalizing your hypothesis, your next step is to develop an EXPERIMENTAL DESIGN. There are three basic types of experimental designs that you may use. Each has its own strengths and weaknesses. * Pre-Experimental Designs: This type of experimental design does not include a control group. A single group of participants is studied, and there is no comparison between a treatment group and a control group. Examples of pre-experimental designs include case studies (one group is given a treatment and the results are measured) and pre-test/post-test studies (one group is test, given a treatment and then retested). * Quasi-Experimental Designs: This type of experimental design does include a control group, but the design does not include randomization. * True Experimental Designs: A true experimental design include both of the elements that the pre-experimental designs and quasi-experimental designs lack on their own – control groups and random assignment to groups.

6) STANDARDIZE YOUR PROCEDURESStandardizing your procedures helps ensure that the things that you are comparing are equivalent.In order to arrive at legitimate conclusions, it is essential to compare apples to apples. Each participant in each group must receive the same treatment under the same conditions. For example, in our hypothetical study on the effects of sleep deprivation on driving performance, the driving test must be administered to each participant in the same way. The driving course must be the same, the obstacles faced must be the same and the time given must be the same

7) CHOOSING RESEARCH PARTICIPANTS” When conducting your experiment, you do not need to test every individual in a group. Instead, you can select a random sample of participants from the larger population.In addition to making sure that the testing conditions are standardized, it is also essential to ensure that your pool of participants is the same. If the individuals in your control group (those who are not sleep deprived) all happen to be amateur race car drivers while your experimental group (those that are sleep deprived) are all people who just recently earned their drivers licenses, your experiment will lack standardization. When choosing subjects, there are a number of different techniques you can use. A simple random sample involves randomly selecting a number of participants from a group. A stratified random sample requires randomly selecting participants from different subsets of the population. These subsets might include characteristics such as geographic location, age, sex, race or socioeconomic status After you have gained approval from your academic institutions Institutional Review Board, you will need to present informed consent forms to each of your participants. This form offers information on the study, the data that will be gathered and how the results will be used. The form also gives participants to withdraw from the study at any point in time.

8) .”COLLECTING DATA” AFTER CAREFULLY DESIGNING YOUR STUDY, now is the time to actually conduct the experiment. Administer your testing procedures and then collect the data from the participants you have selected participants, the next steps are to conduct tests and collect the data. Prior to doing any testing, however, there are a few important concerns that need to be addressed.

9) ” ANALYZE RESULTS AND REACH CONCLUSION Analyze data”The next step is to analyze the data that you collected during your psychology experiment After collecting your data, it is time to analyze the results of your experiment. Researchers utilize statistics to determine if the results of the study support the original hypothesis and to determine if the results are statistically significant. Statistical significance means that the results of the study are unlikely to have occurred simply by chance.The types of statistical methods you use to analyze your data depend largely on the type of data that you collected. If you are using a random sample of a larger population, you will need to utilize inferential statistics. These statistical methods make inferences about how the results related to the population at large. Because you are making inferences based upon a sample, it has to be assumed that there will be a certain margin of error. Once the data from the simple experiment has been gathered, researchers then compare the results of the experimental group to those of the control group to determine if the treatment had an effect. But how do researchers determine this effect? Due to the always present possibility of errors, we can never be 100% sure of the relationship between two variables. However, there are ways to determine if there most likely is a meaningful relationship.

Experimenters use inferential statistics to determine if the results of an experiment are meaningful. Inferential statistics is a branch of science that deals with drawing inferences about a population based upon measures taken from a representative sample of that population.

The key to determining if a treatment had an effect is to measure the statistical significance. Statistical significance shows that the relationship between the variables is probably not due to mere chance and that a real relationship most likely exists between the two variables.

Statistical significance is often represented like this: p < .05 A p-value of less than .05 indicates if the particular results are due merely to chance, the probability of obtaining these results would be less than 5%. Occasionally, smaller p-values are seen such as p < .01. There are a number of different means of measuring statistical significance. The type of statistical test used depends largely upon the type of research design that was used. Experimenters use inferential statistics to determine if the results of an experiment are meaningful. Inferential statistics is a branch of science that deals with drawing inferences about a population based upon measures taken from a representative sample of that population.

The key to determining if a treatment had an effect is to measure the statistical significance. Statistical significance shows that the relationship between the variables is probably not due to mere chance and that a real relationship most likely exists between the two variables.

Statistical significance is often represented like this: p < .05 A p-value of less than .05 indicates if the particular results are due merely to chance, the probability of obtaining these results would be less than 5%. Occasionally, smaller p-values are seen such as p < .01. There are a number of different means of measuring statistical significance. The type of statistical test used depends largely upon the type of research design that was used.

8) SHARE THE RESULTS WITH THE SCIENTIFIC COMMUNITY Write Up and Share Your Results “Writing psychology paper” The final step in conducting your psychology experiment is to communicate your results. Learn more about the structure of a psychology paper and find tips for writing each section.

In order to determine if the results of the study are significant, it is essential to also have a NULL HYPOTHESIS. To say that you are accepting the null hypothesis is to suggest that something is true simply because you did not find any evidence against it. This represents a logical fallacy that should be avoided in scientific research. conducting background research. What do researchers already know about your topic? What questions remain unanswered? You can learn previous research about on your topic by exploring books, journal articles, online databases, newspapers and websites devoted to your topic gain a better understanding of what you will encounter during your own experiment. a better basis for your own hypothesis. you might choose to alter your own hypothesis. why the topic merits further exploration. * explain why you chose to investigate your particular hypothesis and articulate bibliography of your sources. This information will be valuable when you begin to write up your experiment results.

In order to arrive at legitimate conclusions, it is essential to compare apples to apples. Each participant in each group must receive the same treatment under the same conditions.

A simple random sample involves randomly selecting a number of participants from a group. A stratified random sample requires randomly selecting participants from different subsets of the population. These subsets might include characteristics such as geographic location, age, sex, race or socioeconomic status.

Researchers utilize statistics to determine if the results of the study support the original hypothesis and to determine if the results are statistically significant. Statistical significance means that the results of the study are unlikely to have occurred simply by chance. The types of statistical methods you use to analyze your data depend largely on the type of data that you collected. If you are using a random sample of a larger population, you will need to utilize inferential statistics. These statistical methods make inferences about how the results related to the population at large. Because you are making inferences based upon a sample, it has to be assumed that there will be a certain margin of error The final step in conducting your psychology experiment is to communicate your results. Learn more about the structure of a psychology paper and find tips for writing each section.