Overview
ESSAY ASSIGNMENT INSTRUCTIONS
OVERVIEW Counselors are increasingly required to demonstrate the efficacy of their interventions and treatment strategies. Within the helping profession, there is increasing pressure to provide treatments that are evidence-based. The essays provided in this course will assist you with developing meaningful contributions to scientific literature as you eventually develop your dissertation.
INSTRUCTIONS
In each module there will be two essay prompts related to the textbook material for that specific module. For each essay assignment, answer both essay questions using a minimum of 300 words for each essay. A title page (no abstract) and reference page are required. Current APA 7 must be used to cite sources. Course textbooks and materials are allowed for the essay assignments.
TEXT BOOKS
Warner, R. M. (2021). Applied statistics I: Basic bivariate techniques (3rd ed.). Thousand Oaks, CA: Sage Publications. ISBN: 978-1-5063-5280-0.
Warner, R. M. (2021). Applied statistics II: Multivariable and Multivariate Techniques. Los Angeles, CA: Sage Publications. ISBN: 978-1-5443-9872-3
IBM Statistics Standard GradPack (to include Statistics Base, Advanced Statistics, and Regression) (Current ed.)
Your answers to the provided prompt are clearly presented in at least 300 words, showing a clear reflection on key concepts. • You have interacted with course textbook or scholarly research (including at least 3 citations) that demonstrates mastery of key issues and critical thinking. • You have thoroughly answered the statistical question or problem posed in the essay.
Each essay response requires at least 3 citations with the text book being one… there’s 2 essay questions in each module. Also, please put each module on a different word document.
1. Module 5 Essay: Comparing Two Independent Groups
ESSAY: COMPARING TWO INDEPENDENT GROUPS ASSIGNMENT PROMPTS There are several assumptions for the use of an independent samples t test. State each of these and the implications should these assumptions be violated. Is it possible for a p value to equal 0? Why or why not? There are several indices on effect sizes for independent samples t tests. Describe three of these and when one might be used over the others. Next, given a situation in which a research reports a large eta squared effect size (eta squared = .64), why might their reported t value be small and not statistically significant? What may be inference from such a situation? Indicate and provide examples of three of the factors that influence the size of t.
2.Module 6 Essay: Comparing Two or More Groups
ESSAY: COMPARING TWO OR MORE GROUPS ASSIGNMENT PROMPTS Provide an example of a hypothetical study that would use a one-way between-subjects ANOVA. Be sure to describe the different groups, conditions, and hypotheses involved. What would the null be and does successful rejection indicate a mean significantly different from every other mean? How would you decide on the necessary sample size (one which provides adequate statistical power)? State two common post hoc procedures for the comparison of means in an ANOVA. How do these differ from planned contrasts? Given a situation where a researcher intends to demonstrate that a treatment variable will have a significant difference on outcomes, which would the research want to be larger: MS between or MS within? Explain.
3. Module 7 Essay: Correlation Assignment
ESSAY: CORRELATION ASSIGNMENT PROMPTS Provide an example of a hypothetical situation in which a Pearson’s r is used. Explain how the sign and magnitude of r would contribute to a researcher’s understanding of the relationship between X and Y. Given the assumptions for use of Pearson’s r, what would a thorough data screening entail to use of (think statistical tests and data visualization)? How might a researcher attempt to decrease the risk of a Type I error while reporting several correlations? Discuss the two forms of the regression equation, raw score and z score, and provide examples of situations in which one would be more useful than the other. Explain how r, R, and B are related to one another in bivariate regression.