. Explain the difference between Type l and Type II Errors. Provide an example o
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. Explain the difference between Type l and Type II Errors. Provide an example of each Why is random sampling used so infrequently in psychological research? What sampling method is more common? Does lack of random sampling pose problems for research? Why or why not? What advantages do factorial designs have over single factor designs? . How do between-subjects designs differ from within-subjects (or repeated measures) designs? Describe a hypothetical example of each type of design Under what conditions should researchers consider using single participant experiments? 0.What is content validity? Provide an example and explain how it differs from criterion validity and concurrent validityExplanation / Answer
Note: This response is in UK English, please paste the response to MS Word and you should be able to spot discrepancies easily. You may elaborate the answer based on personal views or your classwork if necessary.
(Answer) (5) Explain the difference between Type 1 and Type 2 errors. Provide an example for each.
Type 1 Error – Incorrect rejection of a true “null hypothesis.”
Type 2 Error – Incorrectly retaining a false “null hypothesis.”
Type 1 Error – A false positive finding.
Type 2 Error – A false negative finding.
Type 1 Error – Example, confirming your hypothesis of the earth being the middle of the universe after watching the sky for a while and noticing everything revolves around the earth.
Type 2 Error – Example, most people do believe in urban legends. You find this statement absurd as people these days can easily google facts. You do your research and decide to do your research that mostly consisted of older people. You find that this sample does believe in urban legends. And so, you incorrectly retain the null hypothesis that people believe in urban legends.
(6) Why is random sampling so infrequently used in psychological research? What sampling method is more common? Does the lack of random sampling pose problems for research? Why or why not?
Like the name suggests, random sampling involves picking test subjects at random from the larger subset. For instance, picking 50 students at random from a school of 500 students, in other words, each student has an equal chance of being picked.
Psychological studies generally consist of several criteria that a test subject should possess. This is what helps to have a sharper result when the dependent and independent variable are easily distinguishable. For instance, a study of the likelihood of getting Alzheimer’s is conducted only on people with a family history of Alzheimer’s. This is because researchers have already found out that people without a family history of the disease are not very likely to get it. This helps form a clear research and a succinct study.
Whether or not random sampling poses a problem in a study is entirely subjective. The Alzheimer’s study, for instance, would be clear if unnecessary variables are got out of the way by only sticking to individuals who have a family history of Alzheimer’s. However, calculating the television rating points for a general show like a celebrity talk show would require a mixed-bag of viewers. This is where random sampling would be useful.
Convenience sampling is the most commonly used in psychological studies. For instance, it may be entirely convenient for a researcher to go to the nearby rehabilitation place to find recovering alcoholics for the study on alcoholism. The researcher has therefore picked these individuals because it is convenient.
(7) What advantages do factorial designs have over single factor designs?
Factorial designs are those studies have multiple independent variables. These cases help a researcher check the effect of multiple independent variables on a dependent variable. The researcher is able to check the effect of all variables together and separately. This results in a well-calibrated study that leads to a more accurate result and hence has more advantages in terms of accuracy.
(8) How do ‘between-subjects’ differ from ‘within-subjects’ (or repeated measures) designs? Describe a hypothetical example of each type of design.
Between-subjects: When a different treatment is given to each group, it is known as between-subjects design. For instance, two groups what the same reality show and are asked to evaluate it. Group A is told that people say this show is boring. Group B is told that people say this show is contentious. Based on these 2 different levels of the independent variable, the dependent variable is analysed. This is a between-subjects experiment because two different subjects were used.
Within-subjects: Based on this design, groups will be given the same type of treatment. Their reaction to the treatment is then analysed. For instance, if Baskin Robins is testing new ice-cream flavours, they will give one group the same flavour to taste and note their reaction. This study differs from between-subjects because the independent variable has just one level.
(9) Under what conditions should researchers consider using single participant experiment?
Single participant or single subject experiments are used when the researcher would need to analyse the treatment where one subject functions as the treatment group and the control group. A single graph would suffice to analyse the different before and after administration of treatment.
(10) What is content validity? Provide an example and explain how it differs from criterion validity and concurrent validity.
Content validity: When a group or subject perfectly represents all facets and perspectives of the greater population, it is known as content validity.
For example, when a sample group for ADHD studies would have all the traits and symptoms perfectly mapped down to the larger ADHD population.
Criterion validity: This is the extent to which a measure matches the actual outcome.
For example, it is predicted that ADHD patients would not be able to sit through a 3 hours film and the outcome is true to the measure when the patients are unable to watch the whole film.
Concurrent validity: This is a comparison between the measure in the question and an outcome assessed at the same time.
For instance, it is assumed that the ADHD patients would get bored after 1 hour of the film and the outcome shows that the group got bored after 2 hours of the film. The measure and the outcome are measured simultaneously and compared.
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