Question

Review these Skill Builders (and all of the other Course Materials): -Evaluating p-values -Statistical Power Identify the scenario you are evaluating and name the population. Estimate the size of that population. Example: the population of scenario 1 seems to be students at a State University so you could estimate the number of students at a typical State University. The University of South Florida up the road from me has about 40,000 students Identify the independent variable (IV) and the dependent variable (DV). Sometimes this is stated by the researchers and sometimes you have to ferret it out. In scenario 2, the IV and DV are given as Race and Education, respectively. Write a null hypothesis. If the null hypothesis is not provided in the scenario, write a null hypothesis based on the information that is provided in the scenario. Each scenario addresses differences in an interval or ratio DV among a Nominal or Ordinal IV made up of 2 or more groups. So write the null hypothesis this way: There is no difference in Education based on Race among (state/name the population). Critically evaluate the sample size. This is tricky because the scenarios do not provide us with the right information to calculate an appropriate sample size. And you want to avoid stating that a sample size ‘seems’ to be the right size (very amateurish). What to do? Go to this sample size calculator: https://www.surveysystem.com/sscalc.htm. Use the box labeled Calculate Sample Size, Enter .95 for the confidence level, your estimate of the population, 5 for the confidence interval and see what pops up for the ideal sample size. Compare that number to the sample size in the scenario and critically evaluate the sample size in terms of making a Type I or Type II error. For example, if the sample size is smaller than the ideal sample size, does the probability of making a Type I error increase or decrease. Do the same drill with a Type II error. Critically evaluate the scenario for meaningfulness. Follow the guidance I provided in the Announcement Week 5 Discussion: How To Critically Evaluate The Discussion Scenario. Note: we can often relate meaningfulness to social change. That is, if the research is meaningful then it may have implications for social change. Try evaluating meaningfulness and social change in the same paragraph. But first, define meaningfulness and define social change. Cite, cite, cite. Critically evaluate the statements for statistical significance. Compare the researcher reported p-value for the hypothesis test they conducted (either a t-test or an ANOVA) to the confidence level (usually .05). If the reported p-value is greater than .05, then the researcher should fail to reject the null hypothesis and state that there is no statistical significance. If the reported p-value is less than .05, then the researcher should reject the null hypothesis and state that there is statistical significance. I know this is counter-intuitive. Just do it. Add this for grins, “There is no such decision as ‘rapidly approaching significance.’ This is statistics, not a hurricane watch.” Select 1 response to the following multiple choice question: What scenario would you find to be the least fun?Having a root canal performed by an experienced dentist. Having 4 root canals performed by an unsupervised novice dentist. Having 21 root canals performed by a trained Capuchin monkey. Trying to statistically determine differences in patient post-root canal pain levels based on the dentist’s training.

Answer 1

answer:

• populace = individuals of portland
• test = 100 panclamey chasens perusing in Portland
• varibles= salary of the individual
• parameterstatistics= normal salary of the portland individuals
• statistics=average salary of test
• perceptions unit= cash of portland varible is quantiative and decreate
• (1) populace: understudy and facult of legitimacy americal
• test: understudy and personnel of 30 chose college
• varibles=no of understudies and staff
• parameter statistics= staff proportion of solidarity of understudy
• statistics= staff proportion chosen college
• observational unit= understudy and faculity information is quantative and descretive
• populace: of callfornes of genuine wood
• sample:selected 100 realwood
• varibles:no of in excess of 500 feet and no of frang no less then 500 feet
• parameter: properties in excess of 100 feet genuine wood tures in test
• information is categrical and descretive.
• populace 1 = frag speces of litmbartes
• sample= slected frag for the perception of seze zero
• varible= no of eggs laid by each cloth
• parmeters: normal no of eggs laid by frag of species litrobelts
• measurements: normal eggs laid by the frag in test
• information is quantitive and descretive.

note: i have little bit doubt about this answer , once check it and if any problem with this answer please give comment and please don't give thumb down,thank you.