# Paper Writing Services understanding of the application of logistic regression in evidence-based practice. a cohesive response that addresses the following: 1) In the first line

Abstract
regression concepts, equations, and tests. Chapter 12, “Logistic Regression” Ts chapter provides an overview of logistic regression, wch is a form of statistical analysis frequently used in nursing research. Ts article discusses the results of a study of how many U.S. farmworkers accessed U.S. health care. The study considered ts question on several levels—individual, environmental, and policy—and used

Logistic regression is used to analyze a wide variety of variables that may surround a singular outcome. For example, logistic regression could be used to identify the likelihood of a patient having a heart attack or stroke based on a variety of factors including age, sex, genetic characteristics, weight, and any preexisting health conditions. The biological systems and issues with wch the health care field is concerned represent the kinds of applications for wch logistic regression is especially useful. Logistic regression is used in the health care field for many purposes, including diagnoses, predictions, and forecasting. The three articles in ts week’s Learning Resources illustrate the many uses of logistic regression in the health care field. Ts Discussion allows you to explore the different uses of logistic regression and cultivate a deeper understanding of the application of logistic regression in evidence-based practice. a cohesive response that addresses the following: 1) In the first line of your posting, identify the article you examined, providing its correct APA citation. (See attached PDF file for the article). 2) Post your critical analysis of the article as outlined above (make sure to answer all the points asked above in the area, bullets [1, 2, 3]). 3) Propose potential remedies to address the weaknesses of each study (bullets 4 and 5 in the area). 4) Analyze the importance of ts study to evidence-based practice, the nursing profession, or society (bullet 6 in the area). “ ” The approximate length of ts media piece is 5 minutes. ” The approximate length of ts media piece is 15 minutes. Chapter 24, “Using Statistics to Predict” Ts chapter asserts that predictive analyses are based on probability theory instead of decision theory. It also analyzes how variation plays a critical role in simple linear regression and multiple regression. Statistics and Data Analysis for Nursing Research Chapter 9, “Correlation and Simple Regression” (pp. 208–222) Ts section of Chapter 9 discusses the simple regression equation and outlines major components of regression, including errors of prediction, residuals, OLS regression, and ordinary least-square regression. Chapter 10, “Multiple Regression” Chapter 10 focuses on multiple regression as a statistical procedure and explains multivariate statistics and their relationsp to multiple regression concepts, equations, and tests. Chapter 12, “Logistic Regression” Ts chapter provides an overview of logistic regression, wch is a form of statistical analysis frequently used in nursing research. Ts article discusses the results of a study of how many U.S. farmworkers accessed U.S. health care. The study considered ts question on several levels—individual, environmental, and policy—and used logistic regression to analyze the multivariate data gathered. . Ts article describes the methods and results of a neural network study on the effectiveness of the influenza vaccine using storical data in three neural network algorithms. The article also provides a discussion of logistic regression in comparison to the neural network algorithms used. Ts article outlines the procedures and findings of a study on the use of two methods of neonatal sepsis diagnosis: nearest-neighbor analysis and logistic regression analysis. The results indicated that each method generates unique information useful to diagnosis, and therefore both methods should be used simultaneously for improved accuracy of diagnoses. Walden University. (n.d.). Linear regression. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_linear_regression.html

Sample references
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