HIM 650 Introduction to R Programming
HIM 650 Introduction to R Programming
R is a statistical application that is used to conduct data analysis processes. R is commonly used by different organizations to manage databases and to enhance effective data analysis processes. The application has inbuilt functions that enhance coding and manipulation of data. R is free software and a programming language that enhances statistical computation. The application is supported by R Foundation that always engages in the improvement processes to facilitate efficiency in its use (Jockers & Thalken, 2020). R software can also be used in surveys, polls, as well as studies involving scholarly literature. Compared to other data analysis software, R is more preferred due to its efficiency and the ability to perform accurate graphical presentation and data. R and its libraries enhance the implementation of different graphical and statistical techniques, including nonlinear and linear modelling, time-series analysis, clustering, classification, and spatial. R program can be extended through extensions and functions. R Foundation has always been recognized for the active contribution in terms of availing of different packages. Most of the R’s functions are written in R language, making it easier for the programmers or users to adhere to the algorithmic choices that have been made (Kaya et al., 2019).
Advantages and Disadvantages of R Programming
Language in The Health Care Industry
Advantages
R can easily be paired with different programming languages such as C++, C, Python, and Java. As a result, data analysts of programmers can find flexibility in performing different coding or programming process. With the above feature, programmers can also realize efficiency in database management processes. In other words, advanced R users can write C++, C, and Fortran codes which can then be linked and called at a run time. Also, through the integration of the above programming languages, programmers can directly manipulate R objects. Another advantage of R is the provision of exemplary support in data wrangling. The program has packages such as readr and dplyr that can transform disorganized data into structured and more organized data (Tippmann, 2019). As a result, the data analyst can easily use different codes to perform statistical analysis. Also, R is an open-source programming language whose features can be improved every time. The above scenario means that everyone can work with R without a fee or any need for a license. There is always the need for accuracy in data collection, management, and analysis in the healthcare system. R program has features that make it easier for programmers to conduct data analysis processes and make a meaningful conclusion that is essential in improving healthcare processes (Kruschke, 2018).
Disadvantages
One of the disadvantages of using the R program is the utilization of more memory compared to other programming languages. Even though data analysis and graphical representants are more accurate using R, the programming language used is not easy. The software has a steep learning curve. As a result, data analysis who lacks prior programming experience may find difficulty in learning R codes. R programming language and R package are always much slower compared to other packages such as Python and MATLAB.
Applications of R for Data Analysis and Visualization
R is mostly applied in data cleaning, undertaking descriptive statistics, performing regression analysis, and improving visualization of the findings. R also provides functions for performing moving averages, time-series analysis, and autoregression, which is critical in the healthcare planning processes. In healthcare, the R program is applied in performing pre-clinical trials as well as the analysis of drug-safety data. R can also be used to perform exploratory data analysis and offer visualization tools for the users. R can be used to visualize data using ggplot2.
R Statements Used for Decision-Making
Some of the R statements used in the decision-making processes include if statements, if-else statement, and if-else-if ladder (Rainer et al., 2019). An example of if statement would be: if the condition under consideration is TRUE, that statement gets executed; on the other hand, if the condition is FALSE, the statement does not get executed. If-else statement provides an optional else block, which is executed if the condition to block is FALSE and vice versa. Finally, an example of if-else-if ladder is; when the condition provided to if block is true, then the statement given is executed.
Data Visualization Options in R Programming Language
Some of the data visualization options in the R programming language include Histogram and Bar Chart. The histogram is applied with a number of precise in R. The histogram representation often breaks data into bins or breaks and initiate frequency distribution. The bar graph, on the other hand, is applied to show the comparison between two or more variables. Bar Chart often depicts the comparison between the cumulative total across different groups.
Microsoft Visual Studio
Microsoft Visual Studio is applied in developing computer programs for the Microsoft Windows web applications, web pages, mobile applications, as well as web services. Some examples of commands used to create a new R project include:
read.table(filename,header=TRUE)
read.table(filename,header=TRUE,sep=’,’)
#create a data vector with specified elements
#creat a data vector with elements 1-10
The use of these tools is direct; they provide a direct way of importing files and entering data directly into the R program.
Conclusion
R is mostly used in the healthcare system to enhance quantitative research processes by ensuring valid, applicable, and accurate outcomes in the data analysis processes. Compared to other statistical programs, R is efficient and direct due to the inbuilt functions that can perform different computation and statistical analysis types. R can easily be paired with different programming languages such as C++, C, Python, and Java. As a result, data analysts of programmers can find flexibility in performing different coding or programming process.
Review the ”Introduction to R Programming With DataCamp” video and the other study materials. Answer the R programming question related to the video and study materials (750 words minimum).
Discuss the advantages and disadvantages of R programming language in the health care industry.
Discuss applications of R for data analysis and visualization.
Discuss three R statements used for decision making. Include three corresponding example statements.
Describe two data visualization options in R programming language. Provide an example of a health care data application for each of the visualization options selected (for example, histogram).
What is the purpose of the Microsoft Visual Studio? List the commands used to create a new R project in Visual Studio. What is your impression of the ease of use for this tool?
Learners may gain additional practice in R by viewing the Microsoft Visual Studio website. There you will be able to practice using the Microsoft Visual Studio by using the interactive tool that allows you to create a new R project.
APA style is not required, but solid academic writing is expected.
RUBRIC
Introduction to R Programming
No of Criteria: 10 Achievement Levels: 5
Criteria
Achievement Levels
DescriptionPercentage
1: Unsatisfactory
0.00 %
2: Less Than Satisfactory
74.00 %
3: Satisfactory
79.00 %
4: Good
87.00 %
5: Excellent
100.00 %
Criteria
100.0
Advantages and Disadvantages of R Programming Language in the Health Care Industry
14.0
The description of the advantages and disadvantages of R programming language in the healthcare industry is not present.
The description of the advantages and disadvantages of R programming language in the healthcare industry is present but lacks detail or is incomplete.
The description of the advantages and disadvantages of R programming language in the healthcare industry is present.
The description of the advantages and disadvantages of R programming language in the healthcare industry is detailed.
The description of the advantages and disadvantages of R programming language in the healthcare industry is thorough.
Applications of R for Data Analysis and Visualization
14.0
The discussion of the applications of R for data analysis and visualization is not present.
The discussion of the applications of R for data analysis and visualization is present but lacks detail or is incomplete.
The discussion of the applications of R for data analysis and visualization is present.
The discussion of the applications of R for data analysis and visualization is detailed.
The discussion of the applications of R for data analysis and visualization is thorough.
R Statements Used for Decision Making and Corresponding Example Statements
14.0
The discussion of the three R statements used for decision making, including three corresponding example statements, is not present.
The discussion of the three R statements used for decision making, including three corresponding example statements, is present but lacks detail or is incomplete.
The discussion of the three R statements used for decision making, including three corresponding example statements, is present.
The discussion of the three R statements used for decision making, including three corresponding example statements, is detailed.
The discussion of the three R statements used for decision making, including three corresponding example statements, is thorough.
Data Visualization Options in R Programming Language and Examples of Health Care Data Applications
14.0
The discussion of two data visualization options in R programming language is not present. An example of a health care data application for each of the visualization options selected (for example, histogram) is not present.
The discussion of two data visualization options in R programming language is present but lacks detail or is incomplete. An example of a health care data application for each of the visualization options selected (for example, histogram) is present but lacks detail or is incomplete.
The discussion of two data visualization options in R programming language is present. An example of a health care data application for each of the visualization options selected (for example, histogram) is present.
The discussion of two data visualization options in R programming language is detailed. An example of a health care data application for each of the visualization options selected (for example, histogram) is detailed.
The discussion of two data visualization options in R programming language is thorough. An example of a health care data application for each of the visualization options selected (for example, histogram) is thorough.
Purpose of Microsoft Visual Studio, the Commands Used to Create a New R Project in Visual Studio, and the Impression of Ease of Use
14.0
The discussion of the purpose of Microsoft Visual Studio, the commands used to create a new R project in Visual Studio, and the impression of the ease of use for this tool is not present.
The discussion of the purpose of Microsoft Visual Studio, the commands used to create a new R project in Visual Studio, and the impression of the ease of use for this tool is present but lacks detail or is incomplete.
The discussion of the purpose of Microsoft Visual Studio, the commands used to create a new R project in Visual Studio, and the impression of the ease of use for this tool is present.
The discussion of the purpose of Microsoft Visual Studio, the commands used to create a new R project in Visual Studio, and the impression of the ease of use for this tool is detailed.
The discussion of the purpose of Microsoft Visual Studio, the commands used to create a new R project in Visual Studio, and the impression of the ease of use for this tool is thorough.
Thesis Development and Purpose
7.0
Paper lacks any discernible overall purpose or organizing claim.
Thesis is insufficiently developed or vague. Purpose is not clear.
Thesis is apparent and appropriate to purpose.
Thesis is clear and forecasts the development of the paper. Thesis is descriptive and reflective of the arguments and appropriate to the purpose.
Thesis is comprehensive and contains the essence of the paper. Thesis statement makes the purpose of the paper clear.
Argument Logic and Construction
8.0
Statement of purpose is not justified by the conclusion. The conclusion does not support the claim made. Argument is incoherent and uses noncredible sources.
Sufficient justification of claims is lacking. Argument lacks consistent unity. There are obvious flaws in the logic. Some sources have questionable credibility.
Argument is orderly, but may have a few inconsistencies. The argument presents minimal justification of claims. Argument logically, but not thoroughly, supports the purpose. Sources used are credible. Introduction and conclusion bracket the thesis.
Argument shows logical progressions. Techniques of argumentation are evident. There is a smooth progression of claims from introduction to conclusion. Most sources are authoritative.
Clear and convincing argument that presents a persuasive claim in a distinctive and compelling manner. All sources are authoritative.
Mechanics of Writing (includes spelling, punctuation, grammar, language use)
5.0
Surface errors are pervasive enough that they impede communication of meaning. Inappropriate word choice or sentence construction is used.
Frequent and repetitive mechanical errors distract the reader. Inconsistencies in language choice (register) or word choice are present. Sentence structure is correct but not varied.
Some mechanical errors or typos are present, but they are not overly distracting to the reader. Correct and varied sentence structure and audience-appropriate language are employed.
Prose is largely free of mechanical errors, although a few may be present. The writer uses a variety of effective sentence structures and figures of speech.
Writer is clearly in command of standard, written, academic English.
Paper Format (use of appropriate style for the major and assignment)
5.0
Template is not used appropriately or documentation format is rarely followed correctly.
Appropriate template is used, but some elements are missing or mistaken. A lack of control with formatting is apparent.
Appropriate template is used. Formatting is correct, although some minor errors may be present.
Appropriate template is fully used. There are virtually no errors in formatting style.
All format elements are correct.
Documentation of Sources (citations, footnotes, references, bibliography, etc., as appropriate to assignment and style)
5.0
Sources are not documented.
Documentation of sources is inconsistent or incorrect, as appropriate to assignment and style, with numerous formatting errors.
Sources are documented, as appropriate to assignment and style, although some formatting errors may be present.
Sources are documented, as appropriate to assignment and style, and format is mostly correct.
Sources are completely and correctly documented, as appropriate to assignment and style, and format is free of error.
Total Percentage 100
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