Select a specific clinical problem and post a clinical question that could potentially be answered using data mining. Identify data mining techniques you would apply to this challenge, and provide your rationale. Are there any specific data mining techniques you would not use? Support your decision.
Also read:
- Health Screening and History of an Adolescent or Young Adult Client. Project description Assignment Health Screening and History of an Adolescent or Young Adult Client (A Direct Care Experience) View Rubric Due Date: Nov 17, 2013 23:59:59 Max Points: 150 Details: In this assignment, you will be completing a comprehensive health screening and history on a young adult. To complete this assignment, do the following: Select an adolescent or young adult client on whom to perform a health screening and history. Students who do not work in an acute setting may “practice” these skills with a patient, community member, neighbor, friend, colleague, or loved one. Complete the “Health History and Screening of an Adolescent or Young Adult Client” worksheet. Format the write-up in a manner that is easily read, computer-generated, neat, and without spelling errors. Complete the assignment as outlined on the worksheet, including: 1. Biographical Data 2. Past Health History 3. Family History: Obstetrics History (if applicable) and Well Young Adult Behavioral Health History Screening 4. Review of Systems 5. Include all components of the health history 6. Use correct acronyms or abbreviations when indicated 7. Develop three Nursing Diagnoses for this client based on the health history and screening. Include: one actual nursing diagnosis, one wellness nursing diagnosis, one “Risk For” nursing diagnosis, and your rationale for the choice of each nursing diagnosis for this client. While APA format is not required for the body of this assignment, solid academic writing is expected and in-text citations and references should be presented using APA documentation guidelines, which can be found in the APA Style Guide, located in the Student Success Center. This assignment uses a grading rubric. Instructors will be using the rubric to grade the assignment; therefore, students should review the rubric prior to beginning the assignment to become familiar with the assignment criteria and expectations for successful completion of the assignment.
- CLOSING THE GREAT HEALTH CARE DIVIDE WITH PATTERN RECOGNITION AND DATA-MINING TECHNOLOGIE
- Strayer CIS500 Assignment 4: Data Mining
- Question: Q: Chapter Chapter 11 of Mertler and Vannata; answer exercises on pages 306 and 307: This exercise utilizes the SPSS data setprofile-e.sav, which can be downloaded from this Web site: www.Pvrczak.com/data Conduct a Forward: LR logistic regression analysis with the following variables: IV—age, educ, hrsl, sibs, rincom91, life2 (categorical) DV—satjob2 Note: The variable Iife2 is categorical such that dull = 1, routine/exciting = 2, and all other values are system missing. Develop a research question for the following scenario. Conduct a preliminary Linear Regression to identify outliers and evaluate multicollinearity among the five continuous variables . Complete the following: a. Using the Chi-Square table in Appendix B, identify the critical value atp< .001 for identifying outliers. Use Explore to determine if there are outliers. Which cases should be eliminated? b. Is multicollinearity a problem among the five continuous variables? Conduct Binary Logistic Regression using the Forward: LR method. IV—age, educ, hrsl, sibs, rincom91, life2 (categorical; last is the reference category) DV—satjob2 Note: Make sure that any outliers identified in Exercise 2a are removed from data before running the logistic regression. Also, designating life2 as a categorical covariate with the last category as the reference, essentially makes "routine/exciting" = 0 and "dull" = 1, so interpret the results accordingly. a. Which variables were entered into the model? b. To what degree does the model fit the data? Explain. c. Is the generated model significantly different from the constant-only model? d. How accurate is the model in predicting job satisfaction? e. What are the odds ratios for the model variables? Explain. Module 14 – Multi-level linear analyses: When do you use multi-level linear analyzes? Chapter 8 of Cronk (chapter below I wasn’t sure what was being asked) and answer all practice exercises; post your results here:
- Shipping costs at Columbia Mining Company are a mixture of v
- SAN JOSE MINE, Copiapo, Chile – 2010 – Chilean Mining Incident
- Considerations that might prohibit or limit the mining of certain minerals
- By reviewing demographic data and comparing county data with state and national data, you will be able to determine how your county compares to others across the nation.