good morning afternoon evening night whenever you're watching this welcome back to the Mr sin Channel today we are going to review practice 2 in the AP Psychology CED as we talk about research methods in design and I'll be honest there is a lot of information in this video so to help you out and to help you focus on all the key parts of the video I created guided notes that go along with the video you can find a link to them in the description of the video now to start we have to explain the difference between the experimental methodology and non-experimental methodologies the experimental methodology is a systematic approach that is designed to be carried out under controlled conditions with the goal being to test a hypothesis and establish a causal relationship between the independent and dependent variables so we can see that the experimental method explains behaviors on the other hand non-experimental methodologies are used in research where a controlled experiment is not possible or ethical it is important to note that non-experimental methods just describe behaviors they can't explain behavior and cannot be used to establish a causal relationship between independent and dependent variables non-experimental methods include case studies correlational studies metaanalysis and naturalistic observation a case study examines an individual group of people event or situation to provide detailed information and insight into the topic of Interest one problem that can come up with a case study is the risk of being impacted by the Hawthorne effect which is when the subject of a study Alters their behavior due to them being aware that they are being observed next there's correlational studies which allow researchers to gain insight into the relationship between two variables and can help determine the strength of the relationship between the variables now I do want to point out correlational studies do not show cause and effect and I'll say it one more time for those students in the back of the room correlation does not mean causation remember the only way to gain insight into causation is through a controlled experiment non-experimental methods are always at risk for a third variable impacting the study this is known as the third variable problem which is when an outside variable a third variable impacts the study these variables were not accounted for when creating the parameters of the study now we'll talk more about analyzing data from correlational studies in our next video now moving away from correlational studies next we have metaanalysis which is a statistical technique that combines the results of multiple studies on the same topic to reach a conclusion essentially metaanalysis studies studies instead of our other studies that are looking at participants lastly there is naturalistic observations which is when researchers observe individuals in a real world setting the goal here is to try and gather authentic data by observing people in their environments one issue that can come up with this study is depending on how long the observations are taking place The Observer may not have the proper context for what they are observing for example if you were to observe my high school in 2021 you would have been given a skewed idea on how our school is run this is because my school made a variety of changes to the school day and to the layout of our building due to covid-19 those changes were temporary and not permanent all right that is enough talk about different studies let's now talk about how to design a study first we need to State the hypothesis hypothesis is a specific testable prediction about the relationship between two or more variables often times students confuse the hypothesis with a theory a theory is supported by data from research that has been completed and explains a question thought or phenomenon theories are often based on tested hypotheses they allow us to make predictions about how things are and what might happen in the future now A hypothesis must be falsifiable meaning that the hypothesis can be proven wrong for examp example I can have the hypothesis that students who use my ultimate review packet will score higher on the AP Psychology exam compared to students who do not use the packet this hypothesis could be true but it could also be wrong meaning it is falsifiable after the hypothesis is set we need to identify the operational definitions operational definitions outline the exact procedures used in the study and outlines how the variables are measured or manipulated in the study having clear operational definitions allows for other researchers to replicate the study under the exact same conditions for example let's say that you want to conduct a study on the effects of sleep on academic performance you come up with the following hypothesis students who get more sleep the night before the exam will score higher on the exam compared to students who get less sleep we could Define more sleep as at least 8 hours of continuous sleep the night before the exam which we could have reported by having students track their sleep with apple watches for less sleep we'll Define that as fewer than 8 hours of continuous sleep before the exam and for the exam we can Define the exam as the AP Psychology National exam and we can measure performance by using the scale of 1 to five as reported by college board okay now that we've reviewed hypothesis and operational definitions we need to talk about independent dependent and confounding variables an independent variable is what is being manipulated or controlled by the researcher this is the cause while the dep dependent variable is the outcome that is being measured in the study this is the effect remember the independent variable is the cause and the dependent variable is the effect for instance if we go back to my first example of a hypothesis we can see that the independent variable is my ultimate review packet while the dependent variable is the exam score all right lastly we have confounding variables which are factors other than the independent variable that could impact the dependent variable these are variables that the researcher was not able to remove from the experiment or study for instance if we go back to our sleep study we can see that potential confounding variables could include the student study habits the amount of stress or overall health all of which could impact the students's performance on the exam regardless of the amount of sleep that they get when looking at a study we can see that the more control there is in the study the less confounding variables there will be however in the real world this is not always possible and the more you try to control an experiment the more you risk creating an inauthentic environment which could create new confounding variables as participants might change their behaviors now if you need more help with identifying the IV the DV creating operational definitions and breaking down a hypothesis you can check out the practice resources and quizzes that focus on these topics and skills in my ultimate review packet once you finish this video just click the link in the description of the video sign up for the free preview and go to unit zero to start practicing all right now that we have the hypothesis set the variables defined and the parameters for the experiment set we need to move on to our participants which means we need to understand the difference between the population and Sample the population refers to the entire group that the research is studying while the sample is the selected group of individuals in a population that are selected to represent the population in the study for instance if we are conducting a study on students at your school the population would be the entire student body and the sample would be the students that we selected out of the student body when trying to select individuals from a population to create a sample group researchers can use random sampling which is when each individual in a population has an equal chance of participating in the study researchers can also use stratified sampling which is when the population is divided into different subcategories and a random sample is taken from each subcategory whenever researchers are creating a sample the goal is always to create a representative sample this means that the sample group in the study represents all the different people in the population however one issue that comes up when picking a sample group is sampling bias this is when the sample group that is representing the population in the study does not represent the entire population accurately sampling bias occurs when the process of picking the sample group is flawed for instance if certain members of a population have a higher chance of being selected compared to other people in the population this can happen for a variety of different reasons but I want to focus on one in particular and that's convenience sampling this is when individuals are selected to participate in a study based on their availability which I'm sure none of you have done when trying to create a study for your class or won't do again maybe convenient sampling is convenient it's an easy way to get a sample group but it can often introduce sampling bias into the study and limit the generalizability of the results generalizability refers to the extent to which the findings of a study can be applied to the larger population now once a sample group is picked the researcher will need to set the experimental and control group the experiment group is the group in an experiment that receives the independent variable while the control group gets a placebo which is why the control group is also sometimes referred to as the placebo group a placebo is something that is as close as possible to the independent variable but is missing a key component of the independent variable this way the placebo does not impact the participants but also does not let the participants know that they are not receiving the actual IV in order to determine who is put in the experimental and control group researchers use random assignment which is when participants are randomly assigned to be part of the control or experimental group now don't get this confused with random selection which again is when participants are randomly selected to be part of a study now I just want to reiterate that this is crucial for experiments and studies to have appropriate representation of participants a study that has appropriate representation has a sample that accurately reflects the demographics and characteristics of the population being studied this can increase the chance that the results of the study are more likely to be valid increase the chance that the results will be generalizable and reduce the chance of bias impacting the study so that's why researchers will use random assignment to determine who is part of the experimental group and the control group now there are times when it is not ethical or possible to have participants be randomly assigned in an experiment or study for instance if I want to conduct a study on depression I could not randomly assign participants to the control group or experimental group because I cannot just assign participants to become depressed or not so instead of doing a traditional experiment I would have to run a quasi experiment this is an experiment that does not include the random assignment of participants one thing to note here is this type of experiment cannot determine cause and effect this is because differences between groups are not controlled by random assignment remember the experimental method must use random assignment and will always involve independent and dependent variables but the non-experimental methods will not always use random assignment okay so I realized that there's a lot of terms and Concepts in this video already and we have more to go so to help you remember everything I created a practice quiz on all the terms and Concepts in this video to help make sure that it's all making sense to you you can check it out for free today in my ultimate review packet now the next thing we have to talk about is procedures we can see that researchers can use either a single blind or double blind procedure a single blind procedure is when the participants in the study do not know whether they are in the experimental or control group which helps prevent the social desirability bias and PBO effect the social desirability bias is when participants skew their answers to create a more favorable impression of themselves this generally happens when an individual thinks a study is supposed to reach a certain conclusion and the placebo effect is when an individual's physical or mental state improves after taking a placebo this happens because the individual believes they are taking the real drug or substance so the single blind procedure helps keep participants in the dark since they're not sure if they're getting the placebo or the actual independent variable which can help reduce the chance of participant bias impact ing the study the other procedure researchers can use is the double blind procedure which is when both the participants and researchers do not know who is in the experimental group or controlled group this helps counter both the experimentor bias and social desirability bias the experimental bias occurs when the researchers expectations preferences or beliefs influence the outcome of the study now one thing to note here is the researcher does this unknowingly they do not realize they are influencing the outcome of of the study Okay so we've talked about the hypothesis selecting participants the control group and procedures now we're going to move on to talk about measurements the first is qualitative measures which collect non-numerical data that provide detailed descriptive insights into participants thoughts feelings and behaviors for instance structured interviews which are where researchers ask open-ended questions that allow the participant to provide an in-depth answer about their perspective and experiences qualitative measures often produce information that is descriptive and subjective the data can provide insight into participants's experiences but is Up For Debate and is hard to replicate now researchers can also use quantitative measures which collect numerical data that can be statistically analyzed to identify different relationships patterns and differences for instance researchers can use the lyer scale to gain insight into a particular topic the lyer scale has participants rate their agreement with statements on a scale to provide the researcher with quantifiable data on the participant's attitudes or opinions for example here we have a variety of questions that are focused on specific topics related to online learning each statement has a range of answers from strongly disagree to strongly agree this allows researchers to measure the attitude of the participant quantitative measures often produce information that is more objective and focuses on measuring variables in a numerical form ultimately allowing statistic iCal analysis to occur and allows the study to be replicated all right changing gears now we have to also talk about protecting our participants whenever a researcher is conducting a study it's crucial that participants are protected participants have to understand the necessary information to make an informed decision they must also understand the risks of the study and of course be free to choose whether or not they want to participate all of this is known as informed consent researchers must give adequate information to their participants so they understand the risks of the study and can make a rational decision this is different from informed Ascent which is when the participant is not legally able to provide full consent on their own typically because they are a minor in these cases the participant must agree to the study along with the parent or guardian of the participant it is important that researchers set their studies up in an ethical manner ethical studies make sure they create a positive environment for the subjects where the participants can trust the researcher this way the participants can be assured that they will not be harmed and that the study will have a net benefit for society researchers also need to make sure that the study has integrity and is transparent with participants including debriefing participants at the end of the study to explain to the participants information about the study now in 1892 the American Psychological Association was established as the governing board to study behavior and in 1947 the APA created the first first ethical committee to create standards that all psychological research must follow and in 1974 the institutional review board was created the IRB was created to protect human participants all colleges and universities use the IRB to conduct any experiments or research studies in Psychology institutional review boards look at proposed research studies that have human participants if the IRB does not believe that people participating in the study are being protected they will reject the study one other protection committee that I want to briefly touch on is the IU which stands for institutional Animal Care and use committee this committee regulates and oversees Animal Care and research teaching and testing with animals today the APA has created ethical standards that must be followed by all researchers in order to protect their human and animal subjects at the end of the day researchers who create ethical studies will make sure that the studies respect people's rights and dignity all right now we're almost done with the video but we do have to talk about one last part and that is conclusions specifically peer review and replication experiments and research that can be replicated and go through peer review ensure that scientific findings are reliable and valid peer review is a critical part in evaluating the outcome of research this is where other experts in the field assess the studies's methodology data and conclusions before it is published replication on the other hand involves other individuals conducting the study again this allows others to check the original findings and verify the results at the end of the day peer review and repeated replication allow scientific research to evolve and helps make sure that the standards of the experiment remain high all right now I know that was a lot and I'm sure you're ready to be done but trust me this is the important part you need to practice you can answer the quiz questions on the screen or you could also head on over to my ultimate review packet for some extra help I have multiple free resources in there that'll help you review all the different concepts in this video also when you finish answering the questions on the screen don't forget to check your answers in the comment section down below as always I'm Mr sin thank you so much for watching and I'll see you next time online