Based on the 3 excel spreadsheet data, (JOPES, JCRM, and COP-I3) along with the information from the content page, develop a presentation paper with an overview, recommendations, and an executive summary.
Category: Analytics
-
Frankenstein
Use Frankenstein by Mary Shelley. This assignment asks you to examine, interpret, and explain a piece of literature from our course readings. Your goal is not to summarize the plot. Instead, you will think critically about how and why the author wrote the work and present an argument about its meaning, purpose, or effect on the reader.
Assignment Requirements
1. Choose Your Text
Select a text that meets all of the following requirements:
The text must be more than 20 words in length.
The text must not be a poem.
The text should provide enough depth to support a sustained literary analysis.
Choose a work that allows you to examine literary elements, develop a clear thesis, and support your ideas with evidence from the text.
2. Thesis Statement
Develop a clear and arguable thesis that answers a meaningful question about the text. Your thesis should explain one of the following:
How a literary element creates meaning
How a theme develops
How a character, historical moment, or social issue is revealed
Your thesis should appear in the introduction and guide the entire essay.
3. Textual Evidence
Use direct quotations and specific references from the text to support your ideas.
Each quote must be introduced, explained, and clearly connected to your thesis.
Avoid placing quotations into your writing without context or analysis.
4. Analysis
Explain how your evidence supports your thesis.
Focus on meaning, purpose, and effect rather than summarizing the text.
Your analysis should demonstrate thoughtful engagement and critical thinking.
5. Organization
Your essay should include:
An introduction with a clear thesis
Multiple body paragraphs, each focused on one main idea
A conclusion that explains why your analysis matters and what the reader should take away
Each paragraph should clearly connect back to your thesis.
6. Length
Your essay must be at least 1000 words.
The Works Cited page does not count toward the word total.
7. MLA Formatting
Use MLA format throughout your essay, including:
In-text citations using author and page number
A Works Cited page
12-point Times New Roman font
Double spacing
Possible Literary Elements or Devices to Analyze
You may focus on one or more of the following:
Literary elements:
Theme
Characterization
Setting
Tone
Point of view
Literary devices:
Symbolism
Irony
Imagery
Allusion
Motif
Narrator reliability
Foreshadowing
Diction
Syntax
Juxtaposition
Figurative language
What a Literary Analysis Is Not
This assignment is not:
A plot summary
A personal opinion piece, such as stating whether you liked or disliked the text
A biography of the author
A general research paper
Checklist Before You Submit
Before submitting your essay, review the following questions:
Do I have a clear and arguable thesis?
Did I use direct evidence from the text?
Did I explain how each piece of evidence supports my argument?
Is my analysis clearly organized and easy to follow?
Did I use MLA format correctly for citations and the Works Cited page?
Is my essay at least 1000 words, not including the Works Cited page?
Attached Files (PDF/DOCX): 169-170.pdf, 170-171.pdf, pg1-2.pdf
Note: Content extraction from these files is restricted, please review them manually.
-
Unit 5 Assignment: Class Diagram
In Unit 3, you ran a SWOT analysis for a buying a car process. In this assignment you will create a class diagram that captures that process. The diagram should be clear. Utilize the approved UML symbols. Make sure you describe all classes and objects correctly and list their attributes and methods.
Attached Files (PDF/DOCX): Unit 3 Assignment Creating a WBS.docx, Unit 2 Assignment SWOT Analysis.docx
Note: Content extraction from these files is restricted, please review them manually.
-
Integration and System Functions
Instructions
Imagine that you are a project manager with a large hospital. You are responsible for facilitating the selection of a new healthcare information system. You are asked to preview the Epic EHR, Allscripts MyWay EMR, and Waiting Room Solutions demos.
Explore all of the product modules and functions, such as the user-friendliness (interface and ease of use), patient search functionality, release of information and retrieval, record tracking, web-based standards, internet and intranet use, regulatory requirements, etc.
Create a comparison table or matrix for the various functions.
In a 2-3 page paper, provide an assessment and explanation of how product features would or would not potentially support interoperability and basic integration standards.
Provide a recommendation for a new healthcare information system based on your assessment of each product.
Your paper should be in APA format.
Submit the comparison table and paper.
Resources
Waiting Room Solutions. Go to youtube and search “Waiting Room Solutions Demo” to view this product.
Allscripts MyWay EMR. Go to youtube and search “Allscripts Demo” to view this product.
Grading Rubric
Assignment 1: Integration and System Functions
Points
Student created a comparison table or matrix for the various functions.
20
Student provided thorough outline of the functions for each product.
40
Student provided an assessment and explanation of how product features would or would not potentially support interoperability and basic integration standards
40
Total
100 points
_____________________________________________________________________________________________________________________
2018 AHIMA Entry- Level Competencies Health Information Management Baccalaureate Degree
Domain I. Data Structure, Content, and Information Governance
Competency
I.6. Evaluate data dictionaries & data sets for compliance with government standards
Domain III. Informatics, Analytics, and Data Use
Competency
III.1. Examine health informatics concepts for the management of health information.
III.2. Analyze technologies for health information management.
III.6. Manage data within a database management system.
III.7. Identify standards for exchange of health information.
Attached is the rubric.
Attached Files (PDF/DOCX): Week 2 Assignment_ Integration and System Functions__ – HIMA410 I002 Winter 2026 – APEI.pdf
Note: Content extraction from these files is restricted, please review them manually.
-
Decision tree model for Titanic survival prediction
You are tasked with building and optimizing a decision tree model to predict survival on the Titanic dataset. Using the embedded titanic dataset, you will tune the models hyperparameters to maximize performance. 1. Dataset: Use the titanic dataset from Pythons seaborn library: Python Code import seaborn as sns titanic = sns.load_dataset(“titanic”) Relevant features: * Input variables: pclass, sex, age, sibsp, and fare. * Target variable: survived (1 = survived, 0 = did not survive). 1. Steps: * Data Preprocessing: * Handle missing values (e.g., fill missing age values with the median). * Convert categorical variables (e.g., sex) into numeric format using one-hot encoding. * Split the data into training and test sets. * Baseline Model: * Train a basic decision tree model using default hyperparameters. * Evaluate the model using metrics such as accuracy, precision, recall, and F1 score. * Hyperparameter Tuning: * Use GridSearchCV from scikit-learn to optimize hyperparameters, such as: * max_depth: Maximum depth of the tree. * min_samples_split: Minimum number of samples required to split an internal node. * min_samples_leaf: Minimum number of samples required to be at a leaf node. * Evaluate the optimized model on the test set. * Visualization: * Plot the decision tree using graphviz or plot_tree from scikit-learn. * Compare performance metrics (e.g., accuracy, precision, recall) between the baseline and optimized models. 2. Analysis: * Summarize the results of the optimization process and discuss how the tuned hyperparameters improved the model. * Reflect on any trade-offs between complexity and performance (e.g., overfitting vs. generalization). Submit a Word Document containing your assignment and the following requirements: * A Python Jupyter Notebook containing: * Code for data preprocessing, model training, and hyperparameter tuning. * Visualizations of the decision tree and performance metrics. * A written summary comparing baseline and optimized model results (1-2 pages).
-
Water Quality Impact Analysis
Need to utilize formulas and the excel spreadsheet provided and charts on different tabs
1. Introduction and Problem Description (2+ pages)
o Explain the problem you’re addressing and the purpose of your project.
o Describe the source of the dataset, how you collected it, and what kind of data you used.
o Provide a list or table of the variables (data points) you used to solve the problem.
o Example: If youre studying how weather impacts sales, list variables like Temperature, Rainfall, and Sales.
2. Techniques Used to Analyze Data (2+ pages)
o Describe what data analysis methods you applied to the dataset to answer your problem.
o You can use methods covered in class (e.g., regression, clustering) or explore new ones.
o Example: For a weather-sales problem, you could apply linear regression to see how temperature affects sales.
3. Results (1+ page)
o Present your findings using graphs, figures, or outputs from Excel or R.
o Explain what the results show in relation to your problem. Do they support your initial questions or not?
o Example: Show a graph with sales vs. temperature and explain how temperature increases or decreases sales.
4. Challenges and Summary (1+ page)
o Describe any difficulties you faced in the project and summarize what you learned.
5. Appendix (Optional)
o If needed, add any detailed steps, such as Excel formulas or R code, here.
6. References
o List any books, articles, or websites you used for the project.
-
Week 2 and discussion replies – 5870 and 5890
please see attached,
Attached Files (PDF/DOCX): Discussion 2 and 3 replies.docx, Discussion info.docx, Week 1 discussion post replies.docx
Note: Content extraction from these files is restricted, please review them manually.
-
AI And Analytics
Attached Files (PDF/DOCX): CustomerRetentionMgmt.pdf, AI ADvanced analytics.pdf, DSforBiz_2020_Ch13.pdf, IBM_Salesforce_Mgmt_Analytics.pdf, MegaBank_research_paper.pdf, Mims WSJ article.pdf, Investing in AI_Data Science.pdf, SalesforceOptimizationIBM.pdf, DSforBiz_2020_Ch11.pdf
Note: Content extraction from these files is restricted, please review them manually.
-
Week 3 practice assignment – 5890
NO AI, No CHAT BOTS. Please use reading text to complete in text citations and to support your work. ( readings are listed in the file with readings ) please let me know if you have issues accessing the documents or any of the readings. Please use the formatting of the assignment that I provide, please follow all instructions provided on the assignment that I provide to you as well as my instructions here. Please list and number exactly like the assignment provided thanks.
Please use 7th edition APA format. Please list references used. Please use in text citations.
Attached Files (PDF/DOCX): Practice assignment 1.docx, prep guide errors.docx, Stress and burnout lecture.docx, How to write SMART Goals v2.pdf, Week 3 agenda and readings.docx, Videos for this week.docx, Videos for apa format.docx
Note: Content extraction from these files is restricted, please review them manually.
-
Week 3 prep guide – 5890
NO AI, No CHAT BOTS. Please use reading text to complete in text citations and to support your work. ( readings are listed in the file with readings ) please let me know if you have issues accessing the documents or any of the readings. Please use the formatting of the assignment that I provide, please follow all instructions provided on the assignment that I provide to you as well as my instructions here. Please list and number exactly like the assignment provided thanks.
Please use 7th edition APA format. Please list references used. Please use in text citations.
Attached Files (PDF/DOCX): Videos for this week.docx, Week 3 agenda and readings.docx, Videos for apa format.docx, Week 3 Prep Guide.docx, Stress and burnout lecture.docx, How to write SMART Goals v2.pdf, prep guide errors.docx
Note: Content extraction from these files is restricted, please review them manually.