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Course Description

In this subject, students use statistical language to do analytics. Working with data, visualizing data, object types, and constructing statistical models in a business context are all important subjects to cover. 

Course Prerequisites

MIS-605 and MIS-615

Class Resources

• RStudio Essentials
• MIS-650 Course Revision History

Rfor Data Science

For extra information and additional examples of practical code, the following is recommended:
Wickham,H.,& Grolemund,G.(2017). Rfordatascience.O'ReillyMedia.ISBN-13:9781491910399
https://r4ds.had.co.nz/

MIS-650 Discussion Questions

R Studio

To complete course tasks, download the RStudio Desktop edition of the Integrated Development Environment (IDE). RStudio is a development environment for the R programming language.

https://www.rstudio.com/products/rstudio/

MIS-650ConnectingtoDSQLServerinR
Read"ConnectingtoDSQLServerinR."

MIS-650CPCAnswers

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Course Project Overview

For particular information on what should be included in each component of the Course Project, read the "Course Project Overview."

• RforEveryone: Advanced Analytics and Graphics
• Lander,J.(2017). Rforeveryone: Advanced analytics and graphics (2nded.).Pearson.ISBN-13:9780134546926
• The RProject for Statistical Computing
• Download the R programming software in the relevant version (Windows or iOS) from the R Project website. You will be sent to the closest CRAN (Comprehensive R Archive Network) Mirror site.
• https://www.r-project.org/
• Refer to the Lopes Write webpage for guidance regarding assignments requiring submission to Lopes Write: https://support.gcu.edu/hc/en-us/articles/201277380-LopesWrite

Course Instructions

For each topic, note the following: 

• Complete the assignments in accordance with the "Introduction to R Syntax" resource's instructions. 
• Include a plain text file (.txt) containing all of the assignment's performed functions. Include replies to the questions above in a Word document, along with screenshots of the outcomes of performing each function.
• Send the.txt and Word documents to your teacher.
• Although APA style is not needed, good academic writing is anticipated.
• This assignment makes use of a rubric. Please examine the rubric before beginning the project to become acquainted with the requirements for successful completion.
• This assignment is not needed to be submitted to LopesWrite.

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Topic1: Introduction to R

Sep 30, 2021-Oct 6, 2021 Max Points:105

Resources

• Programming-Part1(Writing code in RStudio)
• View "Programming- Part1 (Writing code in RStudio), "located on the RStudio website (2015). https://www.rstudio.com/resources/webinars/programming-part-1-writing-code-in-rstudio/
• R for Everyone: Advanced Analytics and Graphics
• Read Chapters 1-3 in R for Everyone: Advanced Analytics and Graphics.

Assessments

Class Introductions

Sep 30, 2021, 12:00 AM Oct 2, 2021,11:59 PM Max Points 0

Take a moment to explore your new classroom and introduce yourself to your fellow classmates. What are you excited about learning? What do you think will be most challenging?    

Introduction to RSyntax

Sep 30,2021, 12:00 AM Oct 6,2021, 11:59 PM Max Points 75

The goal of this project is to become acquainted with the R programming coding interface and grammar structure.

Topic 1 DQ1

Sep 30, 2021, 12:00 AM Oct 2, 2021, 11:59 PM Max Points 5

Summarize the necessity for and applications of statistical language software in the context of business analytics. What are some of the several statistical programming languages available? Identify two statistical languages/models, in addition to R programming, in this topic. What are the primary distinctions between the R programming language and the other available programming languages and tools?

Topic 1 DQ2

Sep 30, 2021, 12:00 AM Oct 4, 2021, 11:59 PM Max Points 5

Data analysis necessitates a thorough grasp of the programming language/particular model's properties and capabilities. What are some of the advantages of utilizing R as a statistical programming language? What are some of the most prevalent domains in which R is used for analysis?

Topic 1: Participation

Sep 30, 2021, 12:00 AM Oct 6, 2021, 11:59 PM Max Points 20

Topic 2: Basics of R and Descriptive Statistics

Oct 7, 2021-Oct 13, 2021 Max Points: 125

Resources

RforEveryone: Advanced Analytics and Graphics

• Read Chapter 4 and Sections 18.1 and 18.2 in Chapter 18 in RforEveryone: Advanced Analytics and Graphics.
• Understanding Mathematical Operations and Descriptive Statistics in R

Assessments

Oct7, 2021, 12:00 AM Oct13, 2021, 11:59 PM Max Points 95

The goal of this project is to execute mathematical operations and descriptive statistics using R technology.
Complete the task in accordance with the "Understanding Mathematical Operations and Descriptive Statistics in R" resource's instructions.

Topic 2 DQ1

Oct 7, 2021, 12:00 AM Oct 9, 2021, 11:59 PM Max Points 5

Discuss what you think will be your biggest challenges as you begin to utilize the R software. Find two resources aimed at beginner R users that you found to be helpful and share the links for these resources. Explain what was helpful about the resources you found.

Topic 2 DQ2

Oct 7, 2021, 12:00AM Oct 11, 2021, 11:59 PM Max Points 5

Descriptive statistics and statistical tests can assist analysts in identifying issues with their data and/or analysis. However, after problems have been discovered, professional judgment is required to determine and execute the best effective remedy. Statistical tests, for example, can assist in identifying outlier findings, but it is up to the analyst to determine how to treat those observations in their work. Another example is that measures of central tendencies, such as mean and median, can be deceptive at times, but it is up to the analyst to determine when these measures misrepresent data patterns and what other measures are acceptable for representing the data patterns in a given context. Discuss three factors that analysts should bear in mind when they use professional judgment in their job. For example, are there circumstances under which professional judgment must be disclosed to stakeholders versus others where such disclosure is not necessary? Provide specific examples to support your position.

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Topic 2 Participation

Oct 7, 2021, 12:00 AM Oct 13,2021, 11:59 PM 20

Topic 3: Importing Data and Advanced Data Structures

Oct14, 2021-Oct20, 2021 MaxPoints:125

Resources

• RforEveryone: Advanced Analytics and Graphics
• Read Chapter 5 and 6 in RforEveryone: Advanced Analytics and Graphics.
• CourseProjectComponent1:InitialDataAnalysisandSummaryStatistics

Oct14, 2021, 12:00 AM Oct20, 2021, 11:59PM Max Points 95

• Complete Course Project Component 1: Initial Data Analysis and Summary Statistics, as recommended in the Course Materials' "Course Project Overview" document.
• Please provide the PowerPoint Presentation slides to your teacher.
• For further information on completing this project in the proper manner, see the resource "Creating Effective PowerPoint Presentations," which may be found in the Student Success Center.

Topic 3 DQ1

Oct14, 2021, 12:00 AM Oct16, 2021, 11:59 PM Max Points 5 

The R function aggregate functions like the “group by” in SQL. Provide an example of the aggregate function using detailed data loaded from the AdventureWorks 2016 database and explain the aggregate function data.

Topic 3 DQ2

Oct14, 2021, 12:00 AM Oct18, 2021, 11:59 PM Max Points 5

When you retrieve data from SQL or flat files, data is stored in a data frame. What is a data frame? List two attributes about data frames that make them useful storage objects for data analysis.

Topic 3 Participation

Oct14, 2021, 12:00 AM Oct20, 2021, 11:59 PM max Points 20

Topic4: Manipulating Data

Oct21, 2021-Oct27, 2021 Max Points:125

Resources

A Gentle Introduction to Tidy Statistics in R

• View"A Gentle Introduction to Tidy Statistics in R," by Mock (2019), located on the RStudio website. https://www.rstudio.com/resources/webinars/a-gentle-introduction-to-tidy-statistics-in-r/

What Is Tidy Data?

• Read"What Is Tidy Data? "by Neo (2020), located on the Towards Data Science website. https://towardsdatascience.com/what-is-tidy-data-d58bb9ad2458
• RforEveryone: Advanced Analytics and Graphics
• Read Chapters11and 12inRforEveryone:AdvancedAnalyticsandGraphics.

Assessments

Manipulating Data Elements in R

Oct21, 2021, 12:00 AM Oct27, 2021, 11:59 PM Max Points 95

The goal of this project is to learn about the data manipulation functions in R. The assignment covers both the fundamentals of R and the DPLYR library. Review Chapters 11 and 12 to help you finish your homework.

Complete the assignment in accordance with the "Manipulating Data Elements in R" resource.

Topic 4 DQ1

Oct21, 2021, 12:00 AM Oct23, 2021, 11:59 PM Max Points 5

Data manipulation in R is a critical and fundamental topic. What are three functions in R that may be used to manipulate data? When discussing these functions, provide an example of a circumstance in which you may want to use that function on data. Some analysts prefer to alter data in Excel or comparable software before uploading it to R for analysis, whilst others prefer to do all data operations in a single environment, such as R. What are the benefits and drawbacks of each approach? Give real instances to back up your response.

Topic 4 DQ2

Oct21, 2021, 12:00 AM Oct25, 2021, 11:59 PM Max Points 5

See the article "What Is Tidy Data?" for more information. A Must-Know Concept for Data Scientists" under the topic Resources. Explain the three tidy data principles. Identify an online dataset that breaches one or more of the tidy data criteria and includes a link to it in your response. Describe which of the principles is violated by the dataset and how you would fix the problem.

Topic 4 Participation

Oct21, 2021, 12:00 AM Oct27, 2021, 11:59 PM Max Points 20

Topic 5: Statistical Graphs

Resources

• RforEveryone: Advanced Analytics and Graphics
• Read Chapter 7 in RforEveryone: Advanced Analytics and Graphics.

Assessments    

• Course Project Component 2: Cumulative Statistics and Data Analysis
• Complete Course Project Component 2: Cumulative Statistics and Data Analysis as indicated in the Course Materials' "Course Project Overview" page.
• Please provide the PowerPoint Presentation slides to your teacher.
• For further information on completing this project in the proper manner, see the resource "Creating Effective PowerPoint Presentations," which may be found in the Student Success Center.

Topic 5 DQ1

Oct28, 2021, 12:00 AM Oct30, 2021, 11:59 PM Max Points 5

Visual presentation styles like charts and graphs are effective for some viewers, while tabular or raw data resonates with others. Which method do you prefer? Are there instances where you might be inclined to use one or the other? Give two advantages for each method.

Topic 5 DQ2

Oct28, 2021, 12:00 AM Nov1, 2021, 11:59 PM Max Points 5

Eight percent of males are colorblind, as well as 0.5% of females. This is something developers must consider when choosing colors for their visualizations. However, there are many more considerations when it comes to color selection for visualizations. Identify two additional considerations and strategies to address them.

Topic 5 Participation

Oct28, 2021, 12:00 AM Nov3, 2021, 11:59 PM Max Points 20

Topic 6: Data Distributions and Statistical Tests

Nov4, 2021-Nov10, 2021 Max Points: 125

Resources

• RforEveryone: Advanced Analytics and Graphics
• Review Section 18.2 and read Sections18.3 - 18.5 Chapter 18 in RforEveryone: Advanced Analytics and Graphics.

Assessments

Data Distributions in R

Nov 4, 2021, 12:00 AM Nov10, 2021, 11:59 PM Max Points 95

The goal of this project is to generate random numbers in R, create various plots to illustrate the data distribution of a numerical sample in R, and compute probability based on distributions inside R.

Topic 6 DQ1

Nov 4, 2021, 12:00 AM Nov 6, 2021, 11:59 PM Max Points 5

Identifying, comprehending, and testing data distributions are necessary abilities for business analysts. What is the significance of data distributions in analytics? What are the most prevalent ways that distributions are employed in analysis? How can an analyst find acceptable sample distributions and verify them to ensure that they match the data generation process? How can an analyst determine if data is regularly distributed? Include the R functions for the tests you explain in your response.

Topic 6 DQ2

Nov 4, 2021, 12:00 AM Nov 8, 2021, 11:59 PM Max Points 5

What are some of the available functions that can be utilized in R for carrying out a one-sample and two-sample-test? What are the differences between carrying out a test with equal and unequal variance? Please provide an example to illustrate your assertions.

Topic 6 Participation

Nov 4, 2021, 12:00 AM Nov 10, 2021, 11:59 PM Max Points 20

Topic 7: Linear Regression

Nov 11, 2021 – Nov 17, 2021 Max Points 140.

Resources

RforEveryone: Advanced Analytics and Graphics

Assessments

• Course Project Component 3: Graphical Analysis, Linear Regression, and Recommendations
• Complete Course Project Component 3: Graphical Analysis, Linear Regression, and Recommendations as directed in the "Course Project Overview" resource located in the Course Materials.
• Please turn in your final PowerPoint presentation to your instructor.

Topic 7 DQ1

Nov 11, 2021, 12:00 AM Nov 13, 2021, 11:59 PM Max Points 5

Topic 7 DQ2

What is the purpose of building a linear regression model? What could you evaluate to determine how well the model might work?

Topic 7 Participation

Nov 11, 2021, 12:00 AM Nov 17, 2021, 11:59 PM Max Points 20

Topic 8: Advanced Topics: Nonlinear models

Nov 18, 2021-Nov24, 2021 Max Points: 125

Resources

• RforEveryone: Advanced Analytics and Graphics
• Read Chapters 19 and 21 in RforEveryone: Advanced Analytics and Graphics

Assessments

Methods for Nonlinear Data in R

Nov 18, 2021, 12:00 AM Nov 24, 2021, 11:59 PM max Points 95

• The goal of this assignment is to conduct and interpret methodologies for modeling nonlinear data relationships. To help with assignment completion, go through Chapters 20 and 23.
• Complete the assignment in accordance with the "Methods for Nonlinear Data in R" resource.

Topic 8 DQ1

Nov 18, 2021, 12:00 AM Nov 20, 2021, 11:59 PM Max Points 5
Smoothing splines are one way that analysts can model nonlinear patterns in data. Discuss two benefits and two limitations of using smoothing splines to model nonlinearity in data.

Topic 8 DQ2

Nov 18, 2021, 12:00 AM Nov 22, 2021, 11:59 PM Max Points 5

What is the purpose of the "family" parameter in a generalized linear model, such as a logistic regression? When the "family" parameter is specified as “binomial” what does this say about the relationship between the dependent and independent variables?

Topic 8 Participation

Nov 18, 2021, 12:00 AM Nov 24, 2021, 11:59 PM Max Points 20

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