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Homework 7 Instructions Chi Square Part 1: Green & Salkind: Lesson 40, Exercises 1?4




Question;SPSS Homework 7 InstructionsChi;SquarePart;1:Green;& Salkind: Lesson 40, Exercises 1?4The following helpful tips are numbered to;correspond with the exercise number to which they refer (a dash indicates that;no tips are needed):1.;Use the method reviewed in the;presentation to weight the cases for this data set. (no points?done in data;file)2.;Do a, b, and c. (2 pts for;output and 2 pts each for a?c) 3.;---------- (2 pts)4.;All homework ?Results sections?;must follow the example given in the Course Content document ?Writing Results;of Statistical Tests in Current APA Format? (Note: you do not have to refer to;a figure). (2 pts)Green;& Salkind: Lesson 41, Exercises 1?3The following helpful tips are numbered to;correspond with the exercise number to which they refer (a dash indicates that;no tips are needed):Lilly;collects data on a sample of 130 high school students to evaluate whether the;proportion on female high school students who thake advanced mathe courses in;high school varies demending upons whether they have been raised primiarily by;their father or by both their mother and their father. The SPSS data File;contains two variables: math (0 = no advanced math and 1 = some advanced math);and parent (1 = primararily father and 2 = father and mother) NOTE;This exercise does not use the weighted cases method. Use the data file ?as is.?1.;Do a, b, c, d, and e. For;letter ?e,? this question is asking specifically about effect size. (2 pts for;output and 2 pts each for a?e)Conduct a crosstabs;analysis to examing whether the proportion of female high school students who;take advanced mathe courses is different for different levels of the parent;variable. From the output, identify the following;Case Processing Summary;Cases;Valid;Missing;Total;N;Percent;N;Percent;N;Percent;Parents of female high;school student * Math classes;130;100.0%;0;0.0%;130;100.0%;Parents of female high school student;* Math classes Crosstabulation;Math classes;Total;No advanced math;Some advanced math;Parents of female high;school student;Primarily father;Count;21;9;30;Expected Count;26.1;3.9;30.0;% within Parents of;female high school student;70.0%;30.0%;100.0%;Father and mother;Count;92;8;100;Expected Count;86.9;13.1;100.0;% within Parents of;female high school student;92.0%;8.0%;100.0%;Total;Count;113;17;130;Expected Count;113.0;17.0;130.0;% within Parents of;female high school student;86.9%;13.1%;100.0%;Chi-Square Tests;Value;df;Asymp. Sig. (2-sided);Exact Sig. (2-sided);Exact Sig. (1-sided);Pearson Chi-Square;9.826a;1;.002;Continuity Correctionb;7.986;1;.005;Likelihood Ratio;8.434;1;.004;Fisher's Exact Test;.004;.004;Linear-by-Linear;Association;9.751;1;.002;N of Valid Cases;130;a. 1 cells (25.0%) have;expected count less than 5. The minimum expected count is 3.92.;b. Computed only for a;2x2 table;Symmetric Measures;Value;Approx. Sig.;Nominal by Nominal;Phi;-.275;.002;Cramer's V;.275;.002;N of Valid Cases;130;a.;Percentage of female students;who took no advanced math classes? 13.1%b.;Percent of female students who took;no advanced math classes when female students were raised by their fathers?;70.0%c.;Percent of female students;raised by their father only? d.;?2 value?2(1, N = 130) = 9.83e. Strength of relationship between taking advanced;math classes and level aof parenting2. ---------- (2 pts) Create a clustered bar graph to show differences;in the number of female students taking some advanced mathe classes for the;different categories of parenting.3.;All homework ?Results sections?;must follow the example given in the Course Content document ?Writing Results;of Statistical Tests in Current APA Format? (Note: you do not have to refer to;a figure). (2 pts)Part;2:1. An industrial/organizational (I/O) psychologist is helping a company;determine the type of work stations preferred by its employees. The business;owner believes that people who work in different departments may prefer;different work station layouts. In order to examine this claim, the I/O;psychologist sets up 3 simulated work stations: private office (PO);semi-private office (SPO), and open floor plan (OFP). She recruits employees;from 3 different departments: Information Technology, Human Resources, and;Marketing. The participants spend 30 minutes in each simulated work station;performing general pre-arranged tasks. At the end of the 1.5 hours, the;participants turn in a form on which they mark which work station they prefer.;The results are listed in the table on the following page. Perform a chi square test of independence (using an SPSS two-way;contingency table analysis) to determine whether the proportions of work;station preferences differ across departments. Use the weighted cases method.;The steps will;be the same as the ones you have been practicing in Part 1 of the assignment?the;only difference is that you are now responsible for creating the data file as;well. Remember to name and define your variables under the ?Variable View,?;then return to the ?Data View? to enter the data. (2 pts);Private Office;Semi-Private Office;Open Floor Plan;TOTAL;Information Technology;9;6;4;19;Human Resources;6;10;3;19;Marketing;7;3;9;19;TOTAL;22;19;16;57;2. Create a clustered bar graph;depicting your results. (2 pts)3. Write an APA-style Results section describing the outcome. All;homework ?Results sections? must follow the example given in the Course Content;document ?Writing Results of Statistical Tests in Current APA Format? (Note;you do not have to refer to a figure). (2 pts)Part;3: Cumulative Homework1. A researcher wants to find out if the number of absences from a;chemistry class are predictive of final exam scores at a local university. The data;from the past term are in the table below. Are number of absences predictive of;final exam scores? Choose the correct test to analyze this question, set up the;SPSS file, and run the analysis. Follow the directions on the following page.;Number of Absences;Final Exam Scores;1;1;2;3;4;5;5;5;6;6;6;7;7;98;95;89;89;80;85;80;75;76;69;70;62;60;a);Paste appropriate SPSS output.;(2 pts)b);Paste appropriate SPSS graph. (2;pts)c);Write an APA-style Results;section describing the outcome. All homework ?Results sections? must follow the;example given in the Course Content document ?Writing Results of Statistical;Tests in Current APA Format? (Note: you do not have to refer to a figure). (2;pts)Submit this assignment by 11:59 p.m. (ET);on Monday of Module/Week 7.Part;4: Phase StudyIt is time to;present your findings. During this phase, you will write a short Results;section in current APA style that presents the results of your statistical test;as well as interprets these results in light of the research question. The;Results section must be 1?2 paragraphs must include:1.;The results of your analysis;including the value of the appropriate test statistic, the significance level;and any other pertinent information (sample size, etc.).2.;Several sentences that;interpret these results, includingthe;following information:?;Were the results significant or;not??;Do these results lead you to;accept or reject the null hypothesis??;What are the strengths and;weaknesses of the statistical test that was used??;Are there any characteristics;of the sample or the data collection method that should be taken into;consideration when interpreting these results that you would mention briefly to;the reader?Remember that the;Results section is not a Discussion section. Therefore, it is NOT the place to;make any wide-ranging statements about doctrine in general, how surprised (or;not surprised) you are by the results, whether they correspond with other;research, etc. You will have a chance in the last phase of the lab to share;your thoughts and insights, but remember for this phase that Results sections;focus on data. Use the sections in your textbooks as guides concerning content;and style. You can also use the Publication;Manual of the American Psychological Association as a guide (if you have;one), or visit this website for more guidance:;Descriptive Statistics;Mean;Std. Deviation;N;per_god;4.2857;1.06904;14;jc_god;4.1429;1.16732;14;jc_rose;4.1429;1.16732;14;plp_good;3.0714;.82874;14;jc_sacrifice;4.1429;1.09945;14;gdev_cir;2.6429;1.00821;14;gdwrd_true;4.5714;.51355;14;fthjc_hvn;4.4286;.75593;14;gfgs_ghs;4.5000;.75955;14;total_und;35.9286;35.08334;14;Correlations;per_god;jc_god;jc_rose;plp_good;jc_sacrifice;gdev_cir;gdwrd_true;fthjc_hvn;gfgs_ghs;total_und;per_god;Pearson Correlation;1;.951**;.951**;-.025;.944**;-.326;.240;.027;.189;.216;Sig. (2-tailed);.000;.000;.933;.000;.255;.408;.926;.517;.458;N;14;14;14;14;14;14;14;14;14;14;jc_god;Pearson Correlation;.951**;1;1.000**;.068;.942**;-.215;.367;.274;.434;.276;Sig. (2-tailed);.000;.000;.817;.000;.461;.197;.343;.121;.339;N;14;14;14;14;14;14;14;14;14;14;jc_rose;Pearson Correlation;.951**;1.000**;1;.068;.942**;-.215;.367;.274;.434;.276;Sig. (2-tailed);.000;.000;.817;.000;.461;.197;.343;.121;.339;N;14;14;14;14;14;14;14;14;14;14;plp_good;Pearson Correlation;-.025;.068;.068;1;.072;.033;-.103;.070;.061;.117;Sig. (2-tailed);.933;.817;.817;.806;.911;.725;.812;.836;.691;N;14;14;14;14;14;14;14;14;14;14;jc_sacrifice;Pearson Correlation;.944**;.942**;.942**;.072;1;-.367;.253;.198;.276;.341;Sig. (2-tailed);.000;.000;.000;.806;.197;.383;.497;.339;.232;N;14;14;14;14;14;14;14;14;14;14;gdev_cir;Pearson Correlation;-.326;-.215;-.215;.033;-.367;1;.127;.115;.251;.021;Sig. (2-tailed);.255;.461;.461;.911;.197;.664;.695;.386;.943;N;14;14;14;14;14;14;14;14;14;14;gdwrd_true;Pearson Correlation;.240;.367;.367;-.103;.253;.127;1;.510;.789**;-.164;Sig. (2-tailed);.408;.197;.197;.725;.383;.664;.063;.001;.575;N;14;14;14;14;14;14;14;14;14;14;fthjc_hvn;Pearson Correlation;.027;.274;.274;.070;.198;.115;.510;1;.804**;.317;Sig. (2-tailed);.926;.343;.343;.812;.497;.695;.063;.001;.269;N;14;14;14;14;14;14;14;14;14;14;gfgs_ghs;Pearson Correlation;.189;.434;.434;.061;.276;.251;.789**;.804**;1;.206;Sig. (2-tailed);.517;.121;.121;.836;.339;.386;.001;.001;.479;N;14;14;14;14;14;14;14;14;14;14;total_und;Pearson Correlation;.216;.276;.276;.117;.341;.021;-.164;.317;.206;1;Sig. (2-tailed);.458;.339;.339;.691;.232;.943;.575;.269;.479;N;14;14;14;14;14;14;14;14;14;14;**. Correlation is significant at the 0.01;level (2-tailed).;="msonormal">


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