[Solved] Biology – Anatomy Assignment 6

Assignment Prompt & Instructions

– ## nonparametricsoverview.ppt – ## Assignment6-Nonparametricupdated-2.doc – assign6prob1data.sav – studentengagement-11.sav – PPT9NonparametricsHow-toLecture.ppt **## nonparametricsoverview.ppt** * – Nonparametric, or distribution free tests are so-called because the assumptions underlying their use are “fewer and weaker than those associated with parametric tests” (Siegel& Castellan, 1988, p. 34). – To put it another way, nonparametric tests require few if any assumptions about the shapes of the underlying population distributions – For this reason, they are often used in place of parametric tests if/when one feels that the assumptions of the parametric test have been too grossly violated (e.g., if the distributions are too severely skewed). * – Nonparametric statistical tests have much less restrictive assumptions concerning the distributions of the variables and the variances of comparison groups. – If all assumptions are met, use Parametric techniques – Use Nonparametric When the dependant variable is either categorical or ordinal If the distribution of the dependant variable is skewed When the assumptions are not met, specifically: Normality Homogeneity of variance Nonparametric tests do have at least two major disadvantages in comparison to parametric tests: – First, nonparametric tests are less powerful. Why? Because parametric tests use more of the information available in a set of numbers. – Parametric tests make use of information consistent with interval scale measurement, whereas parametric tests typically make use of ordinal information only. As Siegel and Castellan (1988) put it, “nonparametric statistical tests are wasteful.” * – Second, parametric tests are much more flexible, and allow you to test a greater range of hypotheses. For example, factorial ANOVA designs allow you to test for interactions between variables in a way that is not possible with nonparametric alternatives. * – There are nonparametric techniques to test for certain kinds of interactions under certain circumstances, but these are much more limited than the corresponding parametric techniques. * Parametric and Nonparametric Counterparts **## Assignment6-Nonparametricupdated-2.doc** **Assignment 6: Non-Parametrics** **Chi-Square Test of Association (Independence)** A school system is concerned about the low graduation rate among their high school students. The superintendent assigned a task force to research possible reasons that could explain the low graduation rate. The task force decided to conduct a preliminary literature review about current graduation rate research. The literature review signaled that among several key factors that are related to completion of high school is the development and execution of a school guidance intervention plan. The task force decided to investigate if such is the case in the high school with the highest dropout rate in their district. The following data was collected. (7.5 points) Valenti High School Data | | | | | — | — | — | | | Guidance Intervention Plan | | Students obtaining a high school diploma | No | Yes | | No | 577 | 46 | | Yes | 381 | 492 | In order to run the chi-square test of association (aka, chi-square test of independence), open the file named: assign 6 prob 1 data.sav Under View > Value labels you can toggle between the variable category label (no, yes) or the dummy codes (numeric representation) for the category label (0 = no, 1 = yes) Make sure you review both the “Data view” and “Variable view” so you understand the variable types and other properties – and how the variables were created and entered. Go to Analyze > Descriptive statistics > Frequencies, and move the two variables to the “Variables” box, then click “ok” This gives you the frequencies and percents of each of the variables To run the chi-square of association test, go to Analyze > Descriptive statistics > Crosstabs, then move High School Diploma (HSD) to the “Row” box, and Guidance Intervention Plan (GIP) to the “Column” box Select “Statistics” then select the “Chi square” and “Phi and Cramer’s V” boxes Click “Continue” Select “Cells” then select “Observed” and “Expected” under “Counts” (“Round cell counts” is selected by default) Click “Continue” then “ok”  You will use the output for questions 1-3. You were asked to analyze the data and present the findings in the upcoming school board meeting. Your report must include the following: 1. A short explanation about the following. Please copy and paste them into your discussion. · Chi-Square Test of Association · The Case Processing Summary table · Cross tabulation table · Chi-square Tests table · Clustered Bar Chart 2. Write down the value of the Pearson chi-square and its associated tail probability (p-value). Is it significant? (Use the Morgan text pp. 36-38, for the APA style writeup) 3. In terms of the experimental hypothesis, what has this test shown? 4. Suppose a school board member asked you whether or not there were significantly more students who did not graduate than those who did graduate when the guidance services intervention plan was not provided. Run a chi-square test to answer this question. a. Report the chi-square test of association b. Should that school board member be really concerned about the graduation rates of those who do not get the school guidance counseling intervention plan? **Spearman Rho = Use dataset: Student Engagement.sav** You want to conduct a study to determine the relationship between student engagement and student satisfaction. Two surveys were disseminated to a group of students: (a) The Student Engagement Survey, which uses a 5-point Likert scale for level of engagement, ranging from _Very Disengaged_ (1) to _Very Engaged_ (5); and (b) The Student Satisfaction Survey, which uses a 5-point Likert scale for level of satisfaction, ranging from _Very Dissatisfied_ (1) to _Very Satisfied_ (5). Conduct a Spearman Rho analysis to determine if there is a relationship between student engagement and student satisfaction. (7.5 points) 1. Why is a Spearman Rho analysis the most appropriate for this scenario? 2. Write null and alternate hypotheses. 3. Run the Spearman Rho correlation (HINT: Select Spearman Rho instead of Pearson in the SPSS dialogue box) and copy and paste the SPSS output into the assignment. 4. What is the _r_ value? What is the _p_ value? Is the result significant? Why or why not? 5. Now run the analysis using the Pearson correlation instead of the Spearman Rho. How do the findings compare to the Spearman? 5. Using the Morgan et al. (2012) text please write up a sample results section. _Total Points Earned:_ _/15 Points Possible_ **assign6prob1data.sav** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/assign6prob1data-sav) **studentengagement-11.sav** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/studentengagement-11-sav) **PPT9NonparametricsHow-toLecture.ppt** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/ppt9nonparametricshow-tolecture-ppt-9718511) **PPT9NonparametricsHow-toLecture.ppt** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/ppt9nonparametricshow-tolecture-ppt-9718511) **## nonparametricsoverview.ppt** * – Nonparametric, or distribution free tests are so-called because the assumptions underlying their use are “fewer and weaker than those associated with parametric tests” (Siegel& Castellan, 1988, p. 34). – To put it another way, nonparametric tests require few if any assumptions about the shapes of the underlying population distributions – For this reason, they are often used in place of parametric tests if/when one feels that the assumptions of the parametric test have been too grossly violated (e.g., if the distributions are too severely skewed). * – Nonparametric statistical tests have much less restrictive assumptions concerning the distributions of the variables and the variances of comparison groups. – If all assumptions are met, use Parametric techniques – Use Nonparametric When the dependant variable is either categorical or ordinal If the distribution of the dependant variable is skewed When the assumptions are not met, specifically: Normality Homogeneity of variance Nonparametric tests do have at least two major disadvantages in comparison to parametric tests: – First, nonparametric tests are less powerful. Why? Because parametric tests use more of the information available in a set of numbers. – Parametric tests make use of information consistent with interval scale measurement, whereas parametric tests typically make use of ordinal information only. As Siegel and Castellan (1988) put it, “nonparametric statistical tests are wasteful.” * – Second, parametric tests are much more flexible, and allow you to test a greater range of hypotheses. For example, factorial ANOVA designs allow you to test for interactions between variables in a way that is not possible with nonparametric alternatives. * – There are nonparametric techniques to test for certain kinds of interactions under certain circumstances, but these are much more limited than the corresponding parametric techniques. * Parametric and Nonparametric Counterparts **## Assignment6-Nonparametricupdated-2.doc** **Assignment 6: Non-Parametrics** **Chi-Square Test of Association (Independence)** A school system is concerned about the low graduation rate among their high school students. The superintendent assigned a task force to research possible reasons that could explain the low graduation rate. The task force decided to conduct a preliminary literature review about current graduation rate research. The literature review signaled that among several key factors that are related to completion of high school is the development and execution of a school guidance intervention plan. The task force decided to investigate if such is the case in the high school with the highest dropout rate in their district. The following data was collected. (7.5 points) Valenti High School Data | | | | | — | — | — | | | Guidance Intervention Plan | | Students obtaining a high school diploma | No | Yes | | No | 577 | 46 | | Yes | 381 | 492 | In order to run the chi-square test of association (aka, chi-square test of independence), open the file named: assign 6 prob 1 data.sav Under View > Value labels you can toggle between the variable category label (no, yes) or the dummy codes (numeric representation) for the category label (0 = no, 1 = yes) Make sure you review both the “Data view” and “Variable view” so you understand the variable types and other properties – and how the variables were created and entered. Go to Analyze > Descriptive statistics > Frequencies, and move the two variables to the “Variables” box, then click “ok” This gives you the frequencies and percents of each of the variables To run the chi-square of association test, go to Analyze > Descriptive statistics > Crosstabs, then move High School Diploma (HSD) to the “Row” box, and Guidance Intervention Plan (GIP) to the “Column” box Select “Statistics” then select the “Chi square” and “Phi and Cramer’s V” boxes Click “Continue” Select “Cells” then select “Observed” and “Expected” under “Counts” (“Round cell counts” is selected by default) Click “Continue” then “ok”  You will use the output for questions 1-3. You were asked to analyze the data and present the findings in the upcoming school board meeting. Your report must include the following: 1. A short explanation about the following. Please copy and paste them into your discussion. · Chi-Square Test of Association · The Case Processing Summary table · Cross tabulation table · Chi-square Tests table · Clustered Bar Chart 2. Write down the value of the Pearson chi-square and its associated tail probability (p-value). Is it significant? (Use the Morgan text pp. 36-38, for the APA style writeup) 3. In terms of the experimental hypothesis, what has this test shown? 4. Suppose a school board member asked you whether or not there were significantly more students who did not graduate than those who did graduate when the guidance services intervention plan was not provided. Run a chi-square test to answer this question. a. Report the chi-square test of association b. Should that school board member be really concerned about the graduation rates of those who do not get the school guidance counseling intervention plan? **Spearman Rho = Use dataset: Student Engagement.sav** You want to conduct a study to determine the relationship between student engagement and student satisfaction. Two surveys were disseminated to a group of students: (a) The Student Engagement Survey, which uses a 5-point Likert scale for level of engagement, ranging from _Very Disengaged_ (1) to _Very Engaged_ (5); and (b) The Student Satisfaction Survey, which uses a 5-point Likert scale for level of satisfaction, ranging from _Very Dissatisfied_ (1) to _Very Satisfied_ (5). Conduct a Spearman Rho analysis to determine if there is a relationship between student engagement and student satisfaction. (7.5 points) 1. Why is a Spearman Rho analysis the most appropriate for this scenario? 2. Write null and alternate hypotheses. 3. Run the Spearman Rho correlation (HINT: Select Spearman Rho instead of Pearson in the SPSS dialogue box) and copy and paste the SPSS output into the assignment. 4. What is the _r_ value? What is the _p_ value? Is the result significant? Why or why not? 5. Now run the analysis using the Pearson correlation instead of the Spearman Rho. How do the findings compare to the Spearman? 5. Using the Morgan et al. (2012) text please write up a sample results section. _Total Points Earned:_ _/15 Points Possible_ **assign6prob1data.sav** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/assign6prob1data-sav) **studentengagement-11.sav** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/studentengagement-11-sav) **PPT9NonparametricsHow-toLecture.ppt** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/ppt9nonparametricshow-tolecture-ppt-9718511) **## nonparametricsoverview.ppt** * – Nonparametric, or distribution free tests are so-called because the assumptions underlying their use are “fewer and weaker than those associated with parametric tests” (Siegel& Castellan, 1988, p. 34). – To put it another way, nonparametric tests require few if any assumptions about the shapes of the underlying population distributions – For this reason, they are often used in place of parametric tests if/when one feels that the assumptions of the parametric test have been too grossly violated (e.g., if the distributions are too severely skewed). * – Nonparametric statistical tests have much less restrictive assumptions concerning the distributions of the variables and the variances of comparison groups. – If all assumptions are met, use Parametric techniques – Use Nonparametric When the dependant variable is either categorical or ordinal If the distribution of the dependant variable is skewed When the assumptions are not met, specifically: Normality Homogeneity of variance Nonparametric tests do have at least two major disadvantages in comparison to parametric tests: – First, nonparametric tests are less powerful. Why? Because parametric tests use more of the information available in a set of numbers. – Parametric tests make use of information consistent with interval scale measurement, whereas parametric tests typically make use of ordinal information only. As Siegel and Castellan (1988) put it, “nonparametric statistical tests are wasteful.” * – Second, parametric tests are much more flexible, and allow you to test a greater range of hypotheses. For example, factorial ANOVA designs allow you to test for interactions between variables in a way that is not possible with nonparametric alternatives. * – There are nonparametric techniques to test for certain kinds of interactions under certain circumstances, but these are much more limited than the corresponding parametric techniques. * Parametric and Nonparametric Counterparts **## Assignment6-Nonparametricupdated-2.doc** **Assignment 6: Non-Parametrics** **Chi-Square Test of Association (Independence)** A school system is concerned about the low graduation rate among their high school students. The superintendent assigned a task force to research possible reasons that could explain the low graduation rate. The task force decided to conduct a preliminary literature review about current graduation rate research. The literature review signaled that among several key factors that are related to completion of high school is the development and execution of a school guidance intervention plan. The task force decided to investigate if such is the case in the high school with the highest dropout rate in their district. The following data was collected. (7.5 points) Valenti High School Data | | | | | — | — | — | | | Guidance Intervention Plan | | Students obtaining a high school diploma | No | Yes | | No | 577 | 46 | | Yes | 381 | 492 | In order to run the chi-square test of association (aka, chi-square test of independence), open the file named: assign 6 prob 1 data.sav Under View > Value labels you can toggle between the variable category label (no, yes) or the dummy codes (numeric representation) for the category label (0 = no, 1 = yes) Make sure you review both the “Data view” and “Variable view” so you understand the variable types and other properties – and how the variables were created and entered. Go to Analyze > Descriptive statistics > Frequencies, and move the two variables to the “Variables” box, then click “ok” This gives you the frequencies and percents of each of the variables To run the chi-square of association test, go to Analyze > Descriptive statistics > Crosstabs, then move High School Diploma (HSD) to the “Row” box, and Guidance Intervention Plan (GIP) to the “Column” box Select “Statistics” then select the “Chi square” and “Phi and Cramer’s V” boxes Click “Continue” Select “Cells” then select “Observed” and “Expected” under “Counts” (“Round cell counts” is selected by default) Click “Continue” then “ok”  You will use the output for questions 1-3. You were asked to analyze the data and present the findings in the upcoming school board meeting. Your report must include the following: 1. A short explanation about the following. Please copy and paste them into your discussion. · Chi-Square Test of Association · The Case Processing Summary table · Cross tabulation table · Chi-square Tests table · Clustered Bar Chart 2. Write down the value of the Pearson chi-square and its associated tail probability (p-value). Is it significant? (Use the Morgan text pp. 36-38, for the APA style writeup) 3. In terms of the experimental hypothesis, what has this test shown? 4. Suppose a school board member asked you whether or not there were significantly more students who did not graduate than those who did graduate when the guidance services intervention plan was not provided. Run a chi-square test to answer this question. a. Report the chi-square test of association b. Should that school board member be really concerned about the graduation rates of those who do not get the school guidance counseling intervention plan? **Spearman Rho = Use dataset: Student Engagement.sav** You want to conduct a study to determine the relationship between student engagement and student satisfaction. Two surveys were disseminated to a group of students: (a) The Student Engagement Survey, which uses a 5-point Likert scale for level of engagement, ranging from _Very Disengaged_ (1) to _Very Engaged_ (5); and (b) The Student Satisfaction Survey, which uses a 5-point Likert scale for level of satisfaction, ranging from _Very Dissatisfied_ (1) to _Very Satisfied_ (5). Conduct a Spearman Rho analysis to determine if there is a relationship between student engagement and student satisfaction. (7.5 points) 1. Why is a Spearman Rho analysis the most appropriate for this scenario? 2. Write null and alternate hypotheses. 3. Run the Spearman Rho correlation (HINT: Select Spearman Rho instead of Pearson in the SPSS dialogue box) and copy and paste the SPSS output into the assignment. 4. What is the _r_ value? What is the _p_ value? Is the result significant? Why or why not? 5. Now run the analysis using the Pearson correlation instead of the Spearman Rho. How do the findings compare to the Spearman? 5. Using the Morgan et al. (2012) text please write up a sample results section. _Total Points Earned:_ _/15 Points Possible_ **assign6prob1data.sav** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/assign6prob1data-sav) **studentengagement-11.sav** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/studentengagement-11-sav) **PPT9NonparametricsHow-toLecture.ppt** This file is too large to display. [View in new window](https://www.sweetstudy.com/files/ppt9nonparametricshow-tolecture-ppt-9718511) – 1 – 2 – 3 – 4 – 5