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Health, Medicine, Nursing
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Topic:

Univariate vs. Bivariate Analyses and Regression (MHS506 Case)

Essay Instructions:

Module 4 - Case
UNIVARIATE VS. BIVARIATE ANALYSES AND REGRESSION
Case Assignment
Using the materials in the module homepage and in the background section, please address the following:
What is the difference between "univariate" and "multivariate" analyses? (1 page)
Define and contrast dependent versus independent variables. (1 page)
Describe the difference between logistical regression and linear regression. What types of variables are used for the dependent variable? (1 page)
Assignment Expectations
Length: Case Assignment should be at least 3 pages (750 words) in length.
References: At least two references from academic sources must be included (e.g., peer-reviewed journal articles). You may use any required readings from this module for your two references. Quoted material should not exceed 10% of the total paper (since the focus of these assignments is critical thinking). Use your own words and build on the ideas of others. When material is copied verbatim from external sources, it MUST be enclosed in quotes. The references should be cited within the text and also listed at the end of the assignment in the References section (APA formatting recommended).
Organization: Subheadings should be used to organize your paper according to question.
Format: APA formatting is recommended for this assignment. See Syllabus page for more information on APA formatting.
Grammar and Spelling: While no points are deducted, assignments are expected to adhere to standards guidelines of grammar, spelling, punctuation, and syntax. Points may be deducted if grammar and spelling impact clarity.
Your assignment will not be graded until you have submitted an Originality Report with a Similarity Index (SI) score <20% (excluding direct quotes, quoted assignment instructions, and references). Papers not meeting this requirement by the end of the session will receive a score of 0 (grade of F). Do keep in mind that papers with a lower SI score may be returned for revisions. For example, if one paragraph accounting for only 10% of a paper is cut and pasted, the paper could be returned for revision, despite the low SI score. Please use the report and your SI score as a guide to improve the originality of your work.
The following items will be assessed in particular:
Achievement of learning outcomes for Case Assignment.
Relevance: all content is connected to the question.
Precision: specific question is addressed; statements, facts, and statistics are specific and accurate.
Depth of discussion: points that lead to deeper issues are presented and integrated.
Breadth: multiple perspectives, references, and issues/factors are considered.
Evidence: points are well supported with facts, statistics, and references.
Logic: presented discussion makes sense; conclusions are logically supported by premises, statements, or factual information.
Clarity: writing is concise, understandable, and contains sufficient detail or examples.
Objectivity: use of first person and subjective bias are avoided.

Essay Sample Content Preview:

CASE MOD 4 MHS506 univariate vs. Bivariate analyses and regression
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Difference between "univariate" and "multivariate" analyses
Under univariate analysis the number of variable are considered separately, but in multivariate analysis, the multiple regression techniques are used when there are more than two levels of measurement analyzing there or more simultaneously (Daniel, 2009). Since univariate analysis focuses on individual variables it is associated with the measures of central tendency. Univariate analysis extends from multivariate analysis, and both focus on how variables affect outcomes. Analyzing the statistically significant factors under multivariate analysis highlights that the approach gives better accuracy by considering multiple attributes.
Under univariate analysis only one dependent variable is considered for analysis, compared to multiple dependent variables considered in multivariate analysis (Daniel, 2009). These differences also imply that the univariate analysis tends to be descriptive and not explanatory, emphasizing levels and distributions. On the other hand, multivariate analysis focuses on the degree of relationship among the variable. Considering the number of variables, in analysis is necessary to determine the best statistical technique, and univariate analysis may use descriptive or inferential statistics.
The case for multivariate analysis over univariate analysis is that it that it helps in analyzing various subjects/ variables when in need to conduct a more complex analysis. In any case, univariate analysis is inappropriate when the data research requires multiple levels of analysis. Multivariate analysis also helps in the prediction of outcomes and explanation of the variables that are most associated with predicting the outcome (Daniel, 2009). Multivariate regression also considers using models to determine that they fit with the data, indicating that multivariate data analysis leads to better reliability and validity compared to univariate analysis.
Dependent versus independent variables
A dependent variable is an attribute that depends on other factors, and can be considered the outcome that varies because the independent variables change (Daniel, 2009). In a study the dependent variable is the attribute that is observed and measured when the independent changes. The independent variable is the attribute that is controlled or changed to determine how it affects the dependent variable. There may be more than one independent variable in a study/ experiment, and is depicted as the x-axis in graphical representation.
Statistical analysis and considering the p value helps to determine whether an independent value affects the dependent variable. It is only the independent variables that are manipulated while the dependent variables are registered and measured to determine the relationship...
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