TitleABC123 Version X1Week 1 Practice WorksheetPSY.docx

TitleABC123 Version X1Week 1 Practice WorksheetPSY.docx

• 1.
  Title ABC/123 Version X 1 Week1 Practice Worksheet PSY/315 Version 6 1 University of Phoenix MaterialWeek 1 Practice Worksheet Prepare a written response to the following questions. Chapter 1 1. Explain and give an example for each of the following types of variables: a. Nominal: b. Ordinal: c. Interval: d. Ratio scale: e. Continuous: f. Discrete: g. Quantitative: h. Qualitative: 2. Following are the speeds of 40 cars clocked by radar on a particular road in a 35-mph zone on a particular afternoon:
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  30, 36, 42,36, 30, 52, 36, 34, 36, 33, 30, 32, 35, 32, 37, 34, 36, 31, 35, 20 24, 46, 23, 31, 32, 45, 34, 37, 28, 40, 34, 38, 40, 52, 31, 33, 15, 27, 36, 40 Make a frequency table and a histogram, then describe the general shape of the distribution. 3. Raskauskas and Stoltz (2007) asked a group of 84 adolescents about their involvement in traditional and electronic bullying. The researchers defined electronic bullying as “…a means of bullying in which peers use electronics {such as text messages, emails, and defaming Web sites} to taunt, threaten, harass, and/or intimidate a peer” (p.565). The table below is a frequency table showing the adolescents’ reported incidence of being victims or perpetrators or traditional and electronic bullying. a. Using this table as an example, explain the idea of a frequency table to a person who has never had a course in statistics. b. Explain the general meaning of the pattern of results. Incidence of Traditional and Electronic Bullying and Victimization (N=84) Forms of Bullying N % Electronic victims 41 48.8 Text-message victim 27 32.1
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  Internet victim (websites,chatrooms) 13 15.5 Picture-phone victim 8 9.5 Traditional Victims 60 71.4 Physical victim 38 45.2 Teasing victim 50 59.5 Rumors victim 32 38.6 Exclusion victim 30 50 Electronic Bullies 18 21.4 Text-message bully 18 21.4 Internet bully
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  11 13.1 Traditional Bullies 54 64.3 Physical bully 29 34.5 Teasingbully 38 45.2 Rumor bully 22 26.2 Exclusion bully 35 41.7 4. Kärnä and colleagues (2013) tested the effects of a new antibullying program, called KiVa, among students in grades 1– 3 and grades 7–9 in 147 schools in Finland. The schools were randomly assigned to receive the new antibullying program or no program. At the beginning, middle, and end of the school year, all of the students completed a number of questionnaires, which included the following two questions: “How often have you been bullied at school in the last couple of months?” and “How often have you bullied others at school in the last couple of months?” The table below is a frequency table that shows students’ responses to these two questions at the end of the school year (referred to as “Wave 3” in the title of the table). Note that the table shows the results combined for all of the students in the study. In the table, “victimization” refers to students’ reports of being bullied and “bullying” is students’
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  reports of bullyingother students. a. Using this table as an example, explain the idea of a frequency table to a person who has never had a course in statistics. b. Explain the general meaning of the pattern of results. (You may be interested to know that the KiVa program successfully reduced victimization and bullying among students in grades 1– 3 but the results were mixed with regards to the effectiveness of the program among those in grades 7–9.). Frequencies of Responses in the Five Categories of the Self- Reported Bullying and Victimization Variables at Wave 3 Grades 1-3 Grades 7-9 Victimization Bullying Victimization Bullying Variable Freq. % Freq. % Freq.
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  % Freq. % Occurrence Not at all 3,203 53.6 4,296 72 10,660 77.4 10,880 79.5 Onlyonce or twice 1,745 29.2 1,333 22.3
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  2,031 14.7 1,987 14.5 2 or 3times a month 446 7.5 197 3.3 402 2.9 344 2.5 About once a week 297 5 90 1.5 312 2.3 196 1.4 Several times a week 281 4.7
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  49 0.8 375 2.7 279 2 Participants Respondents n 5,972 100 5,965 100 13,780 100 13,686 100 Missing n
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  955 962 2,723 2,817 Total N 6,927 6,927 16,503 16,503
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  Copyright © XXXXby University of Phoenix. All rights reserved. Copyright ©2013 by Pearson Education, Inc. All rights reserved. Used with permission. Model1Model 1: Single Channel, Poisson Arrival, Exponential Service TimeArrival ratel =3Service ratem =4Interarrival Time1/l =0.3333Service time1/m =0.2500System Utilizationr =0.7500Probability system is emptyP0 =0.2500Average number in lineLq =2.2500Average number in systemLs =3.0000Average time in lineWq =0.7500Average time in systemWs =1.0000n =2P(2 units in system) =0.1406P(n < 2 units in system) =0.4375nP(n)P(n < n)00.250010.18750.250020.14060.437530.10550.578140.07910. 683650.05930.762760.04450.822070.03340.866580.02500.8999 90.01880.9249100.01410.9437110.01060.9578120.00790.96831 30.00590.9762140.00450.9822150.00330.9866160.00250.99001 70.00190.9925180.00140.9944190.00110.9958200.00080.99682 10.00060.9976220.00040.9982230.00030.9987240.00030.99902 50.00020.9992260.00010.9994270.00010.9996280.00010.99972 90.00010.9998300.00000.9998310.00000.9999320.00000.99993 30.00000.9999340.00000.9999350.00001.0000360.00001.00003 70.00001.0000380.00001.0000390.00001.0000400.00001.00004 10.00001.0000420.00001.0000430.00001.0000440.00001.00004 50.00001.0000460.00001.0000470.00001.0000480.00001.00004 90.00001.0000500.00001.0000510.00001.0000520.00001.00005 30.00001.0000 Model 2Model 2: Single Channel, Poisson Arrival, Constant Service TimeArrival ratel =10Service ratem =12Interarrival Time1/l =0.1000Service time1/m =0.0833System Utilizationr =0.8333Average number in lineLq =2.0833Average number in systemLs =2.9167Average time in lineWq =0.2083Average time in systemWs =0.2917nP(n)P(n < n)00.166710.13890.166720.11570.305630.09650.421340.08040.
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  517750.06700.598160.05580.665170.04650.720980.03880.7674 90.03230.8062100.02690.8385110.02240.8654120.01870.88781 30.01560.9065140.01300.9221150.01080.9351160.00900.94591 70.00750.9549180.00630.9624190.00520.9687200.00430.97392 10.00360.9783220.00300.9819230.00250.9849240.00210.98742 50.00170.9895260.00150.9913270.00120.9927280.00100.99392 90.00080.9949300.00070.9958310.00060.9965320.00050.99713 30.00040.9976340.00030.9980350.00030.9983360.00020.99863 70.00020.9988380.00020.9990390.00010.9992400.00010.99934 10.00010.9994420.00010.9995430.00010.9996440.00010.99974 50.00000.9997460.00000.9998470.00000.9998480.00000.99984 90.00000.9999500.00000.9999510.00000.9999520.00000.99995 30.00000.9999 Model 3Model 3:Multichannel, Poisson Arrival, Exponential Service TimeArrival Ratel =100.0100.0100.0100.0100.0100.0Calculations:Service Ratem =120.0120.0120.0120.0120.0120.0Number of serversS =2.03.04.05.06.07.0MP0MP01.00.1671.01.0005.0000.1672.00.4 122.01.8330.5950.412Average number being servedr =0.8330.8330.8330.8330.8330.8333.00.4323.02.1810.1340.432 Average number in lineLq =0.1750.0220.0030.0000.0000.0004.00.4344.02.2770.0250.434 Average number in systemLs =1.0080.8560.8360.8340.8330.8335.00.4355.02.2970.0040.435 Average time in lineWq =0.0020.0000.0000.0000.0000.0006.00.4356.02.3000.0010.435 Average time in systemWs =0.0100.0090.0080.0080.0080.0087.00.4357.02.3010.0000.435S ystem Utilizationrho =0.4170.2780.2080.1670.1390.1198.00.4358.02.3010.0000.435P (zero units in system)P0 =0.4120.4320.4340.4350.4350.4359.00.4359.02.3010.0000.435 Average waiting timeWa =0.0070.0040.0030.0020.0020.00110.00.43510.02.3010.0000.43 5P(wait)Pw =0.2450.0580.0110.0020.0000.00011.00.43511.02.3010.0000.43
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  512.00.43512.02.3010.0000.435Note: The Lqvalue in Exhibit 7.12 may differ slightly from the Lqon this template. The value of Lq in this template isbased on a queue formula. &A Page &P