Write a simple report to present the results.

Please analyze the Boston housing data. Please replicate the coding and interpret the results. Write a simple report to present the results. Please read the docx file for intructions. Zip file includes the sample code for visualization /exploratory analysis and sample code for regression and variable selection. MUST KNOW and have Studio R. Submit a Word file with all the following sections and results well organized.
Links below are the description for housing data.
Boston housing data description
Kaggle description of Boston data

One page executive summary of the deal (what process did you undertake in your analysis at a high level, what are the key takeaways of each deal, what drove your ultimate opinion about each type of deal and what were your conclusions?)

1. one page executive summary of the deal (What process did you undertake in your analysis at a high level, what are the key takeaways of each deal, what drove your ultimate opinion about each type of deal and what were your conclusions?)
2.5–6 page deep analysis memo, all required concepts are attached below.

Form and retention requirement per cms

ScenarioIn response to a quality initiative at LiveWell, the
Health Information Management (HIM) department is revamping the
training process in 3 areas: patient identification in registration,
record analysis, and research using secondary databases. As the HIM
supervisor, you will be developing training materials in response to
this quality improvement initiative. In order to do this, you will focus
on problematic concepts in each area to improve the overall quality of
work performance in the Revenue Cycle.
As part of the training development, you will review resources to develop training materials and training examples.
InstructionsFollow the steps below to prepare training materials, including two training guides and a handout.
Part
1 – Recommend best practices for minimizing registration errors in a
training guide used for instructing employees. Include the following
topics: (explain and give example for each bullet point)
Naming convention best practices
Free text input
Primary and secondary data recommendations
Standard data definitions for patient registration
Part
2 – In a second training guide, recommend the required data elements
for electronic record documentation that will ensure improved record
analysis. Include the following topics: (explain and give example for each bullet point)
Purpose of record analysis
Form and retention requirement per CMS
Required elements for discharge summary and operative note per Center for Medicaid and Medicare Services (CMS)
Two samples of analysis on the required elements for each above-named report type
Part 3 – Determine
the purpose of secondary data and prepare a HANDOUT with examples to be
used with the training guide for instructing the staff. Be sure to include:
A sampling of secondary data (Sample will be on the evaluation of sales tax on cigarettes) (can use any data you want)
Tables, charts, and conclusions that demonstrate the application of data for decision making related to organizational goals
Create all three documents in Word. All documents should be free of spelling, punctuation, and grammar errors.

Think of it as reverse engineering the ui (user interface).

Create a wireframe for a main screen of an application of your choice. Think of it as reverse engineering the UI (User Interface).
Note 1: Use Balsamiq or Lucidchart to create your wireframe; This assignment is based on what we did in Week 9 (UX/UI design).
Note that the goal is practicing UI design at the wireframe-level. You will need to create wireframes for the final deliverable of your group project.
Submit a file (pdf or doc) that shows your wireframe. (Avoid submiting a link only, because sometimes links do not work).

How much economic exposure does the company have?

Task
In this assignment, you will work on a project which includes the following:Running a regression of stock returns against changes in exchange rates
Interpret the findings of the regression analysis
Estimate the degree of economic exposure based on the results from the regression analysis
You will do all of the above twice, first using some made-up data provided below; and a second time using an actual MNC you will select.
Instructions
Download the spreadsheet “Economic Exposure”. The file contains the following data over a 61month interval (these are data I made up for Part 1): Economic_Exposure.xls
Download Economic_Exposure.xls
the stock price of a multinational company,
the value of the European Currency Unit (ECU), quoted $/ECU.
PART 1
Step 1: Use the price series for the company to calculate monthly returns. Note that 61 months of price data will generate 60 months of returns. Similarly, use the ECU series to calculate the monthly percentage changes in the dollar value of the ECU. Show the two series of changes in two separate columns next to the original prices and exchange rates.
Step 2: Regress the return on the company against the percentage changes in the ECU. Stated differently, the return on the company is the dependent (y-axis) variable and the change in the value of the ECU is the independent (x-axis) variable. Report the slope coefficient and its p-value, and the R-squared of the regression. The regression output should be shown in the Excel file.
Step 3: In one Word page, interpret the results as follows:
Provide an interpretation for each of the i) p-value of the estimated slope coefficient, ii) slope coefficient and iii) R-squared
How does the value of the company change when the dollar depreciates?
How much economic exposure does the company have? Here you reach a conclusion based on your answers to 1 and 2 above.
You will submit one Excel file with the regression data and results and one Word file with the interpretation. However, you may choose to provide your interpretation in the Excel file and submit just one Excel file and no Word file if you prefer. This is Part 1 of the assignment.
PART 2
Now select a Multinational Company that has a least 60 monthly return observations available at finance.yahoo.com and estimate the firm’s level of economic exposure using regression analysis, as in Part 1. Exchange rate information is available at, for example Historical rates
Links to an external site.
As part of your answer, provide the following information:
Identify the Multinational Company
Assess qualitatively the firm’s exposure to exchange rate risk after examination of the firm’s revenue information by geographical segment (for example, from SEC 10-K filings at U.S. SECURITIES AND EXCHANGE COMMISSION Links to an external site. and then “Filings”). Use this to briefly explain your choice of currencies to use in the regression analysis.
Provide and interpret the results of your regression analysis as you did in Part 1. Assess quantitatively the level of economic exposure of the firm relative to movements in the currency or currencies you selected. In your interpretation, follow the structure of Part 1.
Important: Make sure the dates for exchange rates and stock prices match when you put them both in the same Excel file as in Part 1. Use “adjusted prices” if you get your monthly stock prices from Yahoo FinanceLinks to an external site. (i.e., stock prices adjusted for stock splits)
You will submit one Excel file with the regression data and results and one Word file with the interpretation. However, you may choose to provide your interpretation in the Excel file and submit just one Excel file and no Word file.
The most difficult but also the most important aspect of the assignment is the interpretation. To help you get started, I have some basic ideas here: Regression Analysis get started answer
Actions
Also, watch the assignment video attached with other files for clarity.

I need to compare the two networks (dolphin and karate) and the starter codes for both are also in the doc.

Please read and follow all the instructions and the requirements carefully, everything you need to know are in the docs below, READ: “A1 zip” and “sample write up” are both examples of how the submission should look like so that you have an idea (IT IS AN EXAMPLE ITS NOT THE SAME TOPIC so refter to the A2 doc for exact details . A2 doc has the instructions and the “terminology” doc is what terms you need to use in the write-up.
Along with the essay I need to submit ●The rmd file ●the knitted pdf file, it is all mentioned in the doc below this is just a reminder.
Please access the hyperlinks in the words underlined in blue, you would need to access those links to compare the two networks. I need to compare the two networks (Dolphin and Karate) and the starter codes for both are also in the doc. I have also attached a sample essay of how the report is expected to be written.

When plotting the model that you are estimating, the value that x2 takes would affect:

use attached documents for refference
QUESTION 1
An analyst calculates the mean Sharpe ratio of 25 U.S. equity mutual funds for which the population variance is unknown. The sample mean is 0.60 and the sample standard deviation of the ratio is 0.40. The analyst can state with a 90% confidence that the mean Sharpe ratio will not be greater than:
0.70528

0.70544

0.73664

0.73688

1.5 points
QUESTION 2
An analyst would like to identify the 95% confidence interval of returns around the mean for a normally distributed sample of 29 U.S. private equity firms for which population variance is known. What is the reliability factor used to construct the confidence interval?
1.650

1.701

1.960

2.048

1 points
QUESTION 3
After analyzing the average stock returns of the 500 companies in the S&P 500, you identify that the average returns are 7.05% and that the variance of returns is 0.0025. The population variance of the S&P500 is known and returns are normally distributed. With what confidence level can you ascertain that returns will not be less than 6%.
90% confidence

95% confidence

99% confidence

We do not have enough information

1.5 points
QUESTION 4
You would like to model the effect of stocks trading volumes (X1) on stock’s return (Yi) but suspect that this effect would differ depending on whether there was a COVID-19 lockdown or not (X2). The most appropriate model to estimate is:
Yi = β0 + β1X1

Yi = β0 + β2X2

Yi = β0 + β1X1 + β2X2

Yi = β0 + β1X1 + β2X2 + β3X1X2

1.5 points
QUESTION 5
You are estimating the following model Yi = β0 + β1X1 + β2X1X2 where X2 is a dummy variable that could take the value 0 or 1. When plotting the model that you are estimating, the value that X2 takes would affect:
The y-intercept of the line plotted to predict the value of Yi

The slope of the line plotted to predict the value of Yi

The y-intercept and slope of the line plotted to predict the value of Yi

The value of X2 will have no effect on the line plotted to predict the value of Yi

1.5 points
QUESTION 6
Using the Crowdfunding Dataset on Blackboard answer the question:
In our dataset, what percentage of the entrepreneurs launched a campaign in the category “Technology”?
0%

6.93%

19.43%

96.97%

1 points
QUESTION 7
Using the Crowdfunding Dataset on Blackboard answer the question:
In our dataset, what percentage of female entrepreneurs were successful?
33.39%

35.84%

41.89%

58.11%

1 points
QUESTION 8
Using the Crowdfunding Dataset on Blackboard answer the question
In our dataset, in which year did entrepreneurs have the highest success rate?
2009

2010

2011

2012

1 points
QUESTION 9
Using the Crowdfunding Dataset on Blackboard answer the question:
In our dataset, is there a statistically significant difference in success rates between the year 2009 and the year 2016?
There is no difference in means

There is a difference in means that is not statistically significant

There is a difference in means that is statistically significant at the 10% level

There is a difference in means that is statistically significant at the 1% level

1.5 points
QUESTION 10
Using the Crowdfunding Dataset on Blackboard answer the question
In our dataset, is there a statistically significant difference in success rates between sustainable projects launched by male entrepreneurs vs sustainable projects launched by female entrepreneurs?
There is no difference in means

There is a difference in means that is not statistically significant

There is a difference in means that is statistically significant at the 10% level

There is a difference in means that is statistically significant at the 1% level

1.5 points
QUESTION 11
Using our dataset, we run the following commands:

What is the y-intercept for projects launched by female entrepreneurs?
0.2117

0.4597

3.6659

4.1256

1.5 points
QUESTION 12
Using our dataset, we run the following commands:

According to our estimation model, on average, female entrepreneurs raise:
$45.97 more than male entrepreneurs

$45.97 less than male entrepreneurs

45.97% more than male entrepreneurs

45.97% less than male entrepreneurs

1.5 points
QUESTION 13
Using our dataset, we run the following commands:

According to our estimation model, on average, a 10% increase in the project goal is associated with:
$0.2117 increase in amount raised

$2.1174 increase in amount raised

0.2117% increase in amount raised

2.1174% increase in amount raised

1.5 points
QUESTION 14
Using our dataset, we run the following commands:

According to our estimation model, for a project with a projectgoal of $10,000 and launched by a female entrepreneur, what is the predicted amountraised?
$434

$2,117

$6,714

$43,373

1.5 points
QUESTION 15
Using our dataset, we run the following commands:

According to our estimation model, is the coefficient on female (0.4597) statistically significantly different from 0.4000?
It is not statistically significantly different at the 1%, 5%, and the 10% level

It is statistically significantly different at the 1% level

It is statistically significantly different at the 5% level

It is statistically significantly different at the 10% level

1.5 points
QUESTION 16
Using our dataset, we run the following commands:

According to our estimation model, is the coefficient on the constant term (3.6659) statistically significantly different from 3.6000?
It is not statistically significantly different at the 1%, 5%, and the 10% level

It is statistically significantly different at the 1% level

It is statistically significantly different at the 5% level

It is statistically significantly different at the 10% level

1.5 points
QUESTION 17
Using our dataset, we run the following commands:

According to our estimation model, the benefit of an additional prior successful experience (experiencesuccess) on the amount of funds raised (lnamountraised) is:
41.58% more for females relative to males

45.13% more for females relative to males

30.54% less for females relative to males

11.04% less for females relative to males

1.5 points
QUESTION 18
Using our dataset, we run the following commands:

According to our estimation model, on average, for a male entrepreneur, an additional successful experience is associated with:
41.58% increase in amount raised

45.13% increase in amount raised

30.54% increase in amount raised

11.04% increase in amount raised

However, also feel free to be adventurous and source your own text!

Investigation #6: Analytic Memo
Instructions
The Analytic Memo, will be your culminating experience from the ‘analytics’ section of our course, allowing you to demonstrate your big data skill set through text analysis. In this investigation you will demonstrate framing a data question, data acquisition, data preparation, analysis, and the presentation of your findings.
There are several options for completing this assignment:
1) Text Analysis using Voyant Tools: In this option, you will frame a data question around a static text or texts (i.e., a corpus) and develop insights into the text(s). You will need to acquire the text in which you analyze. This could be text you have written, texts of publicly available documents, or any other form of text that may interest you. Below is a sample collection of classic texts which you are free to use as a starting point. However, also feel free to be adventurous and source your own text!
Full US Constitution.txt
VoyageOfTheBeagleDarwin.txt
TravelsOfMarcoPolo.txt
MagellanVoyagesAnthonyPiagafetta.txt
Little Red Hood.txt
InnocentsAbroadMarkTwain.txt. (files are all attached)
2) MonkeyLearn Batch Sentiment Analysis: In this option, you will frame a data question around static data that you source. The focus of your data acquisition will be to find short pieces of text (no more than 300) of which you would like to determine the sentiment. Using the batch file that is produced by MonkeyLearn, you can construct a bar chart to describe the overall sentiment.
Regardless of the option selected above, the final deliverable takes on the same form: a 1 page, single spaced, Times New Roman, 12 point font, memo.
The memo should include an introduction that orients the reader to the data question you are attempting to answer, your acquisition and preparation methods, and the analysis process you undertook. Following this introductory section, you will make “claims” about your data. You should aim to make 3-5 claims about the data, supporting each claim with evidence from your analysis in your memo.
You might be asking, what does an analytical claim look like? Think back to the Harry Potter text from class. A simple claim would be: the name Harry appeared most frequently in the text, and was distributed through the entirety of the text. This claim could be supported with frequency counts of the word Harry, compared to other names, and a chart showing the frequency of the word Harry in the text.
Above all, assert a point/claim about the text, then make sure it is supported with analytical rigor.