>project of applied regression analysis (Statistical methods for the analysis of relationships between response and input variables)For the Final Project please analyze two datasets of your choice (please see 1. below) and pick one model (formula) for each dataset that you think best predicts the response variable in each set. Please assume that a client brings you these two datasets (which you have chosen) and requests that you find a “good” model for each. To convince that client that you were thorough in your analysis please type-up one “report” for each dataset: a report for one dataset — written in full sentences and divided into paragraphs — and a report for the other dataset — written in bullet points of your key/main takeaways. Please include screenshots from your analysis in JMP (or another software if you prefer to use any software alternative to JMP). Heres an outline of main things you may want to consider not necessarily in this order (use this as a general guide; this is not a complete list and you dont have to use each point of this outline): 1. Pick 2 datasets (one for a full-sentence write-up and one for bullet-points write-up) and please ensure that each has:a) minimum of 32 observations (data points) 50-500 would be idealb) minimum of 3 regressors 5-10 would be great 2. Think about the data:a) source (ex. do YOU think the source is trustworthy?)b) is the data still applicable (is there anything that makes the data outdated/no longer accurate?)c) are there any problems with the data (missing values unreasonable entries etc.?) Looking at distributions of the response and each regressor may be helpfuld) if you fix/change/exclude anything MAKE SURE to discuss it (what/why/how/etc.)e) include anything else that YOU think is important 3. Start fitting simple models and models with multiple variables:a) what regressors appear to be significant (individually and as a group) 4. Residuals (using one type of scaled residuals would probably be best) – look for patterns problematic data points: a) is some nonlinear relationship present between (a) regressor(s) and response and do we need a data transformation?b) are there any outliers and how to handle them (keep or exclude)c) test for Lack of Fit 5. Transformations (and weighting) of variables:a) what and how to transform to if possible correct non-linear relationships between the variables in the data 6. Diagnostics for Leverage and Influence 7. Selecting variable and building a model 8. Model validation I will talk more about the project during our classes and Ill make sure to keep pointing out what you may want to consider including in your project work as we discuss new topics. If you wish to use data from your employer or another non-publicly available source please ensure that you have a written and signed permission from whoever is responsible for the data to use and release the data as the data may be confidential. For that reason Id strongly discourage the use of company data. .doc file

Order a unique copy of this paper
(550 words)

Approximate price: $22

Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

We value our customers and so we ensure that what we do is 100% original..
With us you are guaranteed of quality work done by our qualified experts.Your information and everything that you do with us is kept completely confidential.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

The Product ordered is guaranteed to be original. Orders are checked by the most advanced anti-plagiarism software in the market to assure that the Product is 100% original. The Company has a zero tolerance policy for plagiarism.

Read more

Free-revision policy

The Free Revision policy is a courtesy service that the Company provides to help ensure Customer’s total satisfaction with the completed Order. To receive free revision the Company requires that the Customer provide the request within fourteen (14) days from the first completion date and within a period of thirty (30) days for dissertations.

Read more

Privacy policy

The Company is committed to protect the privacy of the Customer and it will never resell or share any of Customer’s personal information, including credit card data, with any third party. All the online transactions are processed through the secure and reliable online payment systems.

Read more

Fair-cooperation guarantee

By placing an order with us, you agree to the service we provide. We will endear to do all that it takes to deliver a comprehensive paper as per your requirements. We also count on your cooperation to ensure that we deliver on this mandate.

Read more

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
The price is based on these factors:
Academic level
Number of pages

Order your paper today and save 30% with the discount code HAPPY

error: Content is protected !!
Open chat
You can contact our live agent via WhatsApp! Via + 1 323 412 5597

Feel free to ask questions, clarifications, or discounts available when placing an order.