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I need help with answering the following question. I am a mental health counselor

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One-Way ANOVA Identify a research question from your professional life or research interests that could be addressed by a one-way ANOVA. Indicate why a one-way ANOVA would be an appropriate analysis for this research question. Describe the predictor variable and levels (groups), as well as the outcome variable and its associated measurement scale. Articulate the null hypothesis. Discuss the expected outcome of the one-way ANOVA. Response Guidelines Supplement and extend consideration of the topic by including one or more of the following: new information, questions, constructive or corrective feedback, or alternative viewpoints.

Respond to person 1 and person 2

first person

A t test only allows a researcher to compare the means between two groups, such as female or male. If someone wanted to conduct a study that included more than two groups, they would need to use a technique known as analysis of variance (ANOVA). This statistical analysis is by far the most powerful, because it does not limit the comparison only to two groups (Cooper, 2013). Within the ANOVA, the variable measured is known as the dependent variable (DV), because its value is expected to be affected by another variable. The variable that influences the dependent, is known as the independent variable (IV) because it is assumed to affect. Another advantage of utilizing ANOVA is the ability for it to detect complex patterns of interaction between two, three or more independent variables, which can be far more interesting than the main effects (Cooper, 2013). One-way ANOVA may represent either naturally occurring groups or groups that are created by a researcher while being exposed to different interventions (Warner, 2013). The research question that I would like to examine and address by a one-way ANOVA, is based on a naturally occurring group. Question: Is there a significant difference in an employee’s motivation level by leadership style (authoritative, permissive, and authoritarian)? A one-way ANOVA would be an appropriate statistical analysis because this research question includes more than two groups. The DV is continuous (motivation level) and the IV is categorical (authoritative, permissive, and authoritarian). The predictor variable also referred to as a factor (Warner, 2013) is the “leadership style”. Authoritative style mobilizes the team toward a common vision and focuses on the end goal. Permissive leaders leave all the decision making to the employees, without providing any guidance. Authoritarian styles are exemplified when a leader dictates policies and procedures, decides what goals are to be achieved, and directs and controls all activities without involving their subordinates. The outcome variable is “motivation levels,” and the levels of this factor are as follows: 1, “Because You Told Me To”; 2, “Because You Want Me To”; 3, “Because I Want To”; and 4, “Because It Makes a Difference.” The null hypothesis for this research question would be that mean value of the dependent variable is the same for all groups. Leadership style is a key component when driving organizational employee behavior motivation (Wingate, Lee, & Bourdage, 2019). According to social learning theory, employees look to their leaders as role models of appropriate behavior. Employee’s that experience an authoritarian style of leadership, will have a lower level of motivation versus those that have authoritative leaders. References Cooper, C. (2003). Analysis of variance (ANOVA). In R. L. Miller, & J. D. Brewer, The A-Z of Social Research. London, UK: Sage UK. Retrieved from http://library.capella.edu/login?url=https://search.credoreference.com/content/entry/sageuksr/analysis_of_variance_anova/0?institutionId=816References Warner, R. M. (2013). Applied statistics: From bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage. ISBN: 9781412991346.Optional Companion Web Site Applied statistics: From bivariate through multivariate techniques. (2013). Available at http://www.sagepub.com/warner2e/study/chapter.htm Wingate, T. G., Lee, C. S., & Bourdage, J. S. (2019). Who helps and why? Contextualizing organizational citizenship behavior. Canadian Journal of Behavioural Science / Revue Canadienne Des Sciences Du Comportement. https://doi-org.library.capella.edu/10.1037/cbs0000125

Second person

he analysis of variance, also known as ANOVA, is a statistical method that allows a researcher to partition variability and test null hypotheses regarding fixed and random effects (Denis, 2015). A research question that pertains to this learner's research interests that could be addressed by a one-way ANOVA is as follows: Is there a difference in the burnout levels of registered nurses with different specialties? A one-way ANOVA would be appropriate for this research question because there is one categorical independent variable (i.e. type of nurse) as well as one response variable (i.e. Maslach Burnout Inventory score). A single categorical independent variable and a single continuous dependent variable defines the one-way ANOVA (Denis, 2015). In this case, the predictor variable would be the specialty of the nurse and may consist of the following groups: intensive care unit (ICU) registered nurses, emergency room (ER) registered nurses, and travel registered nurses. The outcome variable would be the associated burnout levels of the nurses measured by the Maslach Burnout Inventory. This inventory consists of 22 items that are scored on a 7-point scale and grouped according to the specific dimension of burnout that they address (Hamid & Musa, 2017). For this particular research question, the null hypothesis is: there will not be any differences concerning the burnout levels of nurses with different specialties. The expected outcome of the one-way ANOVA, however, is that nurses in some specialties (e.g. intensive care) will have higher levels of burnout than nurses in other specialties. This is expected due to the fact that the intensive care specialty is especially demanding, and researchers have found that these nurses are particularly at risk for burnout (Jennings, 2008).