week 2 discussion

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Yorkville University *

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PSYC 6213

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Psychology

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Dec 6, 2023

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docx

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DQ 2.1 Evaluate the constructs of hypothesis testing and inferential analysis, and the two types of errors that can be made when carrying out a test of significance (see Table 4.2 in Goodwin). Assess an example of each type within the context of a research project involving a counselling situation. As you appraise some of your peers’ posts, what are some of the implications of treating human subjects and their psychological and emotional turmoil as being subject to such analysis? The purpose for carrying out a research study is to test a specific hypothesis, and allows researchers to determine where there is a statically significant difference between the conditions of a study (Goodwin & Goodwin, 2017). The null hypothesis significance test makes sure this difference is not a coincidence. Inferential analysis gives the researchers a chance to apply the result that they found in their study to a wider population, outside of the sample of the study (Goodwin & Goodwin, 2017). A type I error is when the result of a study are believed to have an effect and significance, but actually don’t. An example of this in a counselling situation is a study that found there was significant effect in CBT treating separation anxiety, but the treatment isn’t actually effective. A type II error is the exact opposite, when the conclusion of a study is that there was no significant effect in the study when there actually was (Goodwin & Goodwin, 2017). An example of this looking at depression in young adolescents and there no significance found because the sample size was too small, or the measurement/assessments used were not reliable. In the two examples I’ve created, what are some of the implications or turmoil for the participants from a type I or type II error being made? (Word count: 219) Goodwin, K. A., & Goodwin, C. J. (2017). Research in psychology: Methods and designs (8th ed.). Hoboken, NJ: John Wiley & Sons. DQ 2.2 Based on the text’s descriptions of independent, dependent, and confounding variables and sources of bias, describe a counselling-related scenario that contains examples of each. How might these factors affect the interpretation of results and how might the researcher in these scenarios control for confounding variables and other sources of bias? If a study were to be looking at the effectiveness of cognitive processing therapy (CPT) on Post traumatic stress disorder, the dependent variable is the delivery of the CBT and the independent variable is the symptoms of PTSD. Potential confounding variable could be client getting informal help from a friend or family member and making additional progress outside of CPT. I think that experimenter bias could be a possibility as Goodwin & Goodwin (2017) discuss researcher may sometimes do something accidentally or inadvertently that leads participants to change their behaviour and behave in a way that confirms the hypothesis. I think that participant bias could be present as well because a participant may change their behaviour based on what they think the desired results of the study are or if they have prior knowledge on the study and change their behaviour to help the study’s success (Goodwin & Goodwin, 2017). Is there anyway you can think of to control the confounding variable? Do you think it is a positive confounding variable? Word count: 171
Goodwin, K. A., & Goodwin, C. J. (2017). Research in psychology: Methods and designs (8th ed.). Hoboken, NJ: John Wiley & Sons.
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