Answer

Discussion-Plagiarism

Morrison was the Nobel Prize winner for literature in 1993. This recognition made her the “First African American” woman to have ever won the Nobel Prize. In fact, she was the eighth woman to receive the award since it was started many years ago. In Publishers Weekly, Maureen O’Brien recalls Morrison saying that she was very delighted to know that an African American was finally recognized and awarded with the Nobel Prize. Morison continued to thank the Almighty God because her mother was still alive to witness this great achievement. Besides, Morison was among the remarkable contributors to the American Letters. The National Book Foundation acknowledged these contributions by awarding her with the foundation’s medal in 1996.

49.QUESTION

The purpose of Assignment 4 is to apply the concepts that you learned this semester. The assignment consists of three tasks/sections.    

The purpose of Assignment 4 is to apply the concepts that you learned this semester. The assignment consists of three tasks/sections.

Task 1. Provide a paragraph or two descriptions of your proposed dissertation study (it does not have to be your dissertation study; this depends on how far along you are with your dissertation). *Because you may not have finished your dissertation proposal, the details may not be completely worked out. The goal of this task is simply to provide me with enough information that I can provide feedback.

*This is my first class; I am way too far from dissertation. In fact, I have not yet submitted any dissertation suggestion.

Task 2. Write between 3 and 5 quantitative research questions from your proposed dissertation study. These questions should be either comparison questions or relationship questions.

Task 3. Write a paragraph or so description of the statistical analysis that you plan to perform. Because each research question will call for its own analysis (although some research questions may share the same analysis), you will have an analysis description for each question.

The following template provides you with an example to follow for this assignment. My template will closely mimic the presentation of information in a typical Chapter 3 of a dissertation. Assignment 4 Example Template

Study Background The proposed study investigates the influence of an educational intervention designed to improve mathematics problem solving skills. Prior to the start of the fall semester, a sample of students will be assigned to receive the standard curriculum (the comparison or control group) or a new curriculum designed to improve problem-solving skills (the experimental group). For logistical reasons, entire classrooms will be assigned to one of two conditions (i.e., it would not be possible to implement two different teaching methods within a given classroom, so all students in a class will participate in either the experimental or the control condition). The primary dependent variable is scores on a problem-solving test at the end of the spring semester. The problem-solving measure will be administered at the beginning of the fall semester to assess baseline knowledge, then again at the end of the spring semester. Additionally, the following independent variables are of interest: gender, ethnicity (Caucasian, African American, and Hispanic), and previous academic achievement (as measured by standardized test scores from the previous year).

Research Questions

1. Do males and females differ in their end-of-year problem-solving test scores?
2. Do the three ethnic groups differ in their end-of-year problem-solving test scores?
3. Do the students in the experimental and control groups differ in their end-of-year problem solving skills?
4. Did students in experimental and control groups improve at different rates between the baseline and end of the year?
5. Is there a relationship between previous academic achievement and end-of-year problem-solving test scores?

Proposed Statistical Analyses

1. Research question 1 will be addressed using an independent t test. The independent t test is appropriate for comparison research questions where it is of interest to determine whether two groups of individuals (i.e., the independent variable is categorical such as male and female) have different averages on a dependent variable (e.g., problem-solving scores). The t test yields a probability value that describes the likelihood of the groups differing due to random chance. By convention, probability values less than 5% are deemed statistically significant because the likelihood of chance producing the difference is rather small.

1. Research question 2 will be addressed using a one-factor ANOVA. The one-factor ANOVA is appropriate for comparison research questions where it is of interest to determine whether two or more groups of individuals (i.e., the independent variable is categorical such as Caucasian, African American, and Hispanic) have different averages on a dependent variable (e.g., problem-solving scores). The ANOVA yields a probability value that describes the likelihood of the groups differing due to random chance. By convention, probability values less than 5% are deemed statistically significant because the likelihood of chance producing the difference is rather small.

1. Research question 3 will be addressed using an independent t test. The independent t test is appropriate for comparison research questions where it is of interest to determine whether two groups of individuals (i.e., the independent variable is categorical such as experimental and control) have different averages on a dependent variable (e.g., problem-solving scores). The t test yields a probability value that describes the likelihood of the groups differing due to random chance. By convention, probability values less than 5% are deemed statistically significant because the likelihood of chance producing the difference is rather small.

1. Research question 4 will be addressed using a two-factor ANOVA. The two-factor ANOVA is appropriate for comparison research questions where it is of interest to determine whether two categorical independent variables influence a dependent variable. In this study, the two independent variables are the timing of the test administration (baseline and end-of-year) and experimental condition (control and experimental). In particular, the interaction of these two variables is of interest because it is hypothesized that students in the experimental condition will experience greater improvement than students in the comparison condition (i.e., the two variables exert a synergistic influence on problem solving). The two factor ANOVA yields a probability value for the two independent variables and the interaction. This probability describes the likelihood of the groups differing due to random chance. By convention, probability values less than 5% are deemed statistically significant because the likelihood of chance producing the difference is rather small.

1. Research question 5 will be addressed using a correlation. The correlation is appropriate for relationship research questions where it is of interest to determine whether a trend exists between two continuous variables (e.g., previous test scores and end-of-year problem-solving scores). The correlation analysis yields a statistic (Pearson’s r) that describes the direction of the trend (positive or negative) as well as the strength of the trend. Additionally, the analysis yields a probability value that describes the likelihood of the trend occurring due to random chance. By convention, probability values less than 5% are deemed statistically significant because the likelihood of chance producing the trend is rather small.

ANSWER

Application of Concepts Learned in this Semester to Quantitative Research Study

Study Background

The rates of graduation in high school American-Indian learners within North Carolina remain significantly lower than that of their peers from other ethnic backgrounds (Skinner-Coleman, 2015). As such, certain institutions provide title seven Indian learning programs to enhance engagement and increase graduation rates among students. The proposed study will compare the rates of dropout and school suspension rates for Indian American learners, who are registered in government-funded high schools, backed by title-seven Indian learning interventions, to the levels of dropout and school suspension levels for Indian-American learners registered in government-sponsored high schools that lack title-seven Indian learning interventions. The dependent variable of interest includes title-seven programs, whereas the dependent variables will be student suspension rate and student dropout rate. Besides, the control variables of type of suspensions, gender, and grade level will be statistically controlled.

Research Questions

1. What is the impact of the title-seven Indian learning intervention on the engagement of male Native-Americans in learning as indicated by rates of dropout?
2. What is the impact of the title-seven Indian learning intervention on the engagement of female Native-Americans in learning as indicated by rates of dropout?
3. What is the impact of the title-seven Indian learning intervention on male Native-American engagement in learning as indicated by rates of suspension?
4. What is the impact of the title-seven Indian learning intervention on female Native-American engagement in learning as indicated by rates of suspension?
5. What is the association between the dropout rates and rates of school suspension for indigenous American learners?

Proposed Statistical Analyses

Research question 1 will be addressed using the correlation or dependence method. The correlation will be used to determine if the identified variables are linearly related (Esser & Vliegenthart, 2017). For example, this statistical method will determine whether there exists a statistically significant impact on the identified learning intervention when comparing to the rates of dropout. With this method, the researchers will be able to establish a line of best fit between the two variables. A significance level of 0.05 indicates that there is a statistical significance even if there is no apparent difference.

Research question 2 will be addressed using the correlation method. This comparative method is effective when a researcher wants to identify an existing relationship between a dependent variable and an independent variable (Esser & Vliegenthart, 2017). In this case, the education program is the independent variable, and the female Native American students represent the dependent variable. A significance level of 0.05 indicated that there is a statistical significance even if there is no apparent difference.

Research question 3 will be addressed using the Analysis of Variance (ANOVA) t-test. This experiment is used to determine whether there is a significant relationship between variables (Esser & Vliegenthart, 2017). In broader prospects, it will enable the researchers to either consider accepting or rejecting the alternate hypothesis. A significance level of 0.05 indicated that there is a statistical significance even if there is no apparent difference.

Research question 4 will be addressed using the independent t-test method. This statistical test helps in determining whether there exists a statistical significance between two unrelated groups. In this case, the two groups are female Native American students and the Title VII Indian Education program. Thus test assumes that variances of the identified groups being measured are equal (Esser & Vliegenthart, 2017). If they are unequal, the research is bound to be affected by the Type I error rate. A significance level of 0.05 indicated that there is a statistical significance even if there is no apparent difference.

Research question 5 will be addressed using two-factor ANOVA. This approach will be most effective in determining whether two independent variables influence the identified dependent variable (Esser & Vliegenthart, 2017). In this research, the two independent variables are dropout rates and school suspension rates while the dependent variable is Native American learners. A significance level of 0.05 indicated that there is a statistical significance even if there is no apparent difference.

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