SW 430 –Final – 1 of 19 SW 430: Research Methods in Social Work I Final Examination 1.21. When we use the Method of Intuition, we hold a belief because a. evidence from a systematic observation of events supports our belief better than it supports any other belief. b. holding the belief helps us avoid anxiety associated with not knowing. c. it was endorsed by someone who has been socially or politically defined as a qualified producer of knowledge d. the belief was deduced by strictly following the forms and rules of logical argument. e. the majority of a random sampling of sources says the belief is true. 1.80. When we work to maximize “good outcomes for science, humanity, and the individual research participants while avoiding or minimizing unnecessary, risk, harm, or wrong,” we are implementing which one of the following ethical principles. a. Beneficence b. Competence c. Comprehension d. Justice e. Respect 2.02. S.S. Stevens defined four levels of measurement used to classify measurement schemes: Nominal, Ordinal, Interval, and Ratio. For each of the following, identify the level of measurement by writing Nominal, Ordinal, Interval, or Ratio in the space provided. Do NOT use initials. 2.02.03. INTERVAL Amount of household income above (positive numeral) or below (negative numeral) poverty level. Numerals represent amount of income; Equal intervals between numerals represent equal amounts of income; Zero does not represent absence of income; negative values are possible, so the zero is arbitrary. 2.02.05. INTERVAL Body temperature in degrees Fahrenheit. Numerals represent amount of heat; Equal intervals between numerals represent equal amounts of heat; Zero does not represent absence of heat (below zero temperatures can occur), so the zero is arbitrary. 2.02.07. NOMINAL Classification of residence location (1 = rural, 2 = urban – [city], 3 = urban – [township], 4 = suburban – [city] or 5 = suburban urban – [township]). Numerals do not represent “amount” of location; they label unordered categories of location. 2.02.14. INTERVAL Deviation score (YμYy−=). Numerals represent amounts of difference from the mean of the distribution; Equal intervals between numerals represent equal amounts of difference from the mean of the distribution; While zero represents absence of difference from the mean of the distribution, negative deviation scores will occur for amounts less than the average amount for the distribution, so the zero is arbitrary.SW 430 –Final – 2 of 19 2.02.25. RATIO Number of days a case is open in intake. Numerals represent amount of days a case is open in intake; Equal intervals between numerals represent equal amounts of days; Zero represents an absence of days open (for a case that was never opened); one cannot have a case open for a negative number of days, so the zero is absolute. 2.02.30. ORDINAL Rating of agreement with a statement about self (1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = Neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree). Numerals represent amount of agreement from lesser to greater agreement; Equal intervals between numerals do not represent equal amounts of agreement. 3.12. The following are a set of 25 social competency scores. Present them in a grouped frequency table. The bottom interval should have a lower limit of zero (real lower limit of –0.5). The interval width should be i = 5. {23, 30, 32, 31, 28, 18, 7, 17, 32, 22, 25, 23, 21, 38, 25, 26, 3, 34, 23, 21, 20, 13, 36, 11, 27} The number of class intervals will be less than the number of spaces that the table provides. Class Interval Frequency 35-39 2 30-34 5 25-29 5 20-24 7 15-19 2 10-14 2 5-9 1 0-4 1 4.18. We typically set the criterion maximum probability of committing a Type I Error – P[Type I Error] –at α = .05. This implies that the criterion probability of not committing a Type I Error – P[~Type I Error] = 1 – P[Type I Error] – would be 1 – α = .95. We have evaluated the effectiveness of a program at two different times (conducted two distinct comparisons). On both occasions, we used a statistical hypothesis test at α = .05 to evaluate the outcome data. Evaluate the following across these c = 2 comparisons. 4.18.1. Assuming that the Null Hypothesis is true, what is the probability that you will not commit a Type I Error on either or both of the c = 2 comparisons? Please show your work and do not round your final answer. .9025==−=−22.95.05)(1cα)(1 4.18.2. Assuming that the Null Hypothesis is true, what is αexp (the experiment-wise α; the probability that you will commit a Type I Error on at least one of the c = 2 comparisons)? Please show your work and do not round your final answer. .0975=−=−=−−=−−= .90251.951.05)(1122cexpα)(11αSW 430 –Final – 3 of 19 4.31. You have a sampling frame containing the names of N = 5,000 individuals. You wish to draw a sample of n = 5 individuals. You assign consecutive identification numerals from 1 to 5,000 to each of the individuals. 03991 10461 20097 76794 23287 31630 01272 Then you take a table of random digits and look at the last four digits of the random digits in the table. If the last four digits were greater than 5000, you would ignore that random digit. For example, in the table of random digits to the left, you would read 03991 as 3991, 10461 as 0461, 20097 as 0097, 76794 as 6794, 23287 as 3287, 31630 as 1630, and 01272 as 1272. Since 6794 is greater than 5000, you would drop this number. You would use the remaining numerals select sampling units for inclusion in the sample. Thus, you would select those individuals from the population assigned numbers 3991, 461, 97, 3287, and 1630 for the sample. If you follow this procedure you have drawn a(n) a. purposive sample b. quota sample c. random sample d. stratified sample e. systematic sample 5.10 A characteristic of a population (such as average age) is called a(n) parameter while the same characteristic of a sample is called a(n) statistic. 5.20. The score (Y) in the following table represents the score on a social skills checklist. Y f cf 76-80 1 48 71-75 1 47 66-70 2 46 61-65 6 44 56-60 8 38 51-55 11 30 46-50 7 19 41-45 6 12 36-40 3 6 31-35 2 3 26-30 0 1 21-25 1 1 Use the following formula to find the score at the 25th percentile. (i)c-n(p)YYibLPff+= where YP stands for the score at the percentile