introduce Stratified sampling in R studio

A. Topic is Stratified sampling. If you are interested in sampling, how to modify the estimation methods we have learned when the sample is not simple random sampling,.

B. Content

You will prepare a document summarizing the most important aspects of what you have learned. It should be written in your own words, considering the other students in the course as your audience. You know exactly what they are supposed to know, and what they are not, so you can explain your findings to them at the right level

Your document must include the following sections:

1. General Purpose and Description (10 points)
   Describe the general purpose of the branch of statistics that covers your topic. Then describe the general purpose and the type of research questions of your particular topic. Give examples of disciplines that use this technique. Why are you interested in it? Length: One or two paragraphs at most.
2. Fundamental Equations (25 points)
   Describe any equations, formulas, hypotheses, statistics, distributions, assumptions, etc. required for using the technique. You do not have to derive the formulas. Explain them intuitively instead. Length: Three to five pages.  You are focusing on one technique.
3. A Simple Example (25 points)
   Complete a simple example by hand (if possible). If the equations are not easily doable by hand, follow the steps of a simple example using calculations already performed with technology, and focus on how to interpret the values to answer the research question. Whatever the case, explain the example in detail, as intuitively as possible. (No length requirements: use as little or as much as you need to explain an easy example completely.)
4. R Implementation
   4.1 Data. Find or create a data set that can be analysed by the technique you have described.
   Import it into R and summarize it. Note that listing three pages of numbers in a list is not a summary. Summarize it with the purpose of conveying information. Your summary should include appropriate descriptive measures and at least one relevant plot. (10 points)

4.2 R Implementation. Teach your readers how to implement the technique using R. Use your workshop handouts as a guide on how you can achieve this (write the instruction(s), show the output, and explain it). Your objective here is to lead your reader by the hand from the loading and summary of data to the final conclusion of the estimation or test. There might be R functions that solve your problem. If there aren’t any, then perform step-by-step calculations as required. (20 points)

5. References
You must use at least two reputable sources (NOT Wikipedia). Every source that you use must be properly referenced. You are supposed to explain ideas in your own words; if you are using someone else’s words, please use quotations (except for equations, formulas, etc.). If the example you use is based on a textbook or a website, make sure to say where it is coming from at the top of the example (you don’t need quotes there). You are not expected to come up with your own examples, so make sure that you acknowledge whose example it is originally. Failure to reference your sources correctly is plagiarism.

C. Format

You must submit a pdf of your document uploaded via Blackboard. You may use any software of your preference to produce your document. If you use RMarkdown, the file must be professionally formatted, not a long list of ##s. If you use a different word processor, make sure to include the R summaries, plots, and instructions from part 4 in your document. Points will be lost for issues in formatting and professionalism as follows (10 points):

Spelling and grammar (1 or 2 points) Clarity and readability (1 to 4 points) Formatting (1 or 2 points) Professionalism (1 or 2 points)

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