LibGuides: Business Division Faculty LibGuide: Course: Data Analytics OER/ZTC

What is the Difference Between OER and ZTC?

OER and ZTC are often used interchangeably but they are not necessarily the same thing.

A zero textbook cost course is one that uses learning materials that cost the students zero dollars. For example, materials from Western Library's Databases are considered ZTC but not OER. Why? While the learning materials cost the students zero dollars, there is a cost to Western Library in the form of database subscription fees and other material costs.

Adopting Open Educational Resources (OER) is a common method of eliminating textbook costs in courses. OER carry an open license. This is a type of license (Creative Commons - CC) that grants permission to access, re-use and redistribute a work for free, with few or no restrictions.

If you see an open license symbol like the this one, that's how you know it's OER!

Course Competencies (WIP, retrieved from WIDS 5/5/21)

Apply methods to retrieve data

identify the purpose of retrieving subsets of data
experiment with techniques used to select subsets of data

Demonstrate methods to summarize data

research software environments used to summarize data
explain the features of a statistical computer software

Prepare data dashboards

define data dashboard
explore characteristics of data dashboards
identify types of data dashboards

Analyze historical data

identify methods for collecting historical information
discuss time series analysis

Predict data trends

explore methods used to forecast data
examine how forecasts are utilized to make business decisions
identify risk involved in predicting data trends

Interpret statistical data

explain the purpose of statistical functions
identify tools used to calculate statistical significance
analyze the meaning of statistical results

Use financial evaluation methods

demonstrate financial calculations
relate financial results to effective decision-making

Evaluate optimal solutions

classify optimal solutions
explore tools used to identify optimal solutions
identify how to determine the optimal solution

Use data to make business decisions

summarize data relevance
differentiate between methods utilized to make business decisions
connect the decision to the intended audience

Data Analytics - OER

Introduction to Data Analysis Using Excel and Lab Report Writing Using LaGCC Institution Data
Part 1: An Introduction to Data Analysis Using Excel --- interpret, summarize and present numerical data; plot numerical data as a graph and determine an equation of a line; use the appropriate formatting functions to label your graph and creating a best fit line.
Part 2: Lab Report Writing Using (LaGCC) Institutional Data (NOTE: Could use Western's)
To communicate interpretations of research data. This is done writing discussions and conclusions (using scientific language) and is often accompanied by data tables and graphs.
To use your Microsoft Excel graphing skills to interpret, inquire and extrapolate meaning data to support your lab report conclusions
To structure your written lab report in the format of: Abstract, Introduction, Material, Methods,Results, Discussion/Conclusion and References
Click the Download button for access to PDF Textbook.
Sampling and Data (LibreText)
.0: Introduction to Sampling and Data
1.1: Definitions of Statistics, Probability, and Key Terms
1.2: Data, Sampling, and Variation in Data and Sampling
1.3: Levels of Measurement
1.4: Experimental Design and Ethics
1.5: Chapter Key Terms
1.6: Chapter References
1.H: Sampling and Data (Homework)
1.R: Sampling and Data (Review)
1.S: Sampling and Data (Solutions)
Source: Introductory Business Statistics - OpenStax (OER)
Introductory Business Statistics - OpenStax (OER)
Presenting Data with Charts
This chapter explores numerous charts that can be used for a variety of purposes. In addition, we will examine formatting charts and using those charts in Word and PowerPoint documents.
From: Beginning Excel 2019 (OER)
Beginning Excel 2019
Fundamentals of Data Visualization
The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data visualizations.
Forecasting; Principles and Practices
This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details. (Updated Sept. 2022)

Data Analytics - Zero Textbook Cost

Big Data for Qualitative Research
Covers everything small data researchers need to know about big data, from the potentials of big data analytics to its methodological and ethical challenges. Big data is large volume, rapidly generated, digitally encoded information that is often related to other networked data, and can provide valuable evidence for study of phenomena. This book explores the potentials of qualitative methods and analysis for big data, including text mining, sentiment analysis, information and data visualization, netnography, follow-the-thing methods, mobile research methods, multimodal analysis, and rhythmanalysis. It debates new concerns about ethics, privacy, and dataveillance for big data qualitative researchers.
Database: eBook Collection (EBSCO) Login with your Western ID.
Big-Data-Based Architectures and Techniques - Predictive Intelligence Using Big Data and the Internet of Things
This chapter covers the essentials of big data analytics ecosystems primarily from the business and technology context. It delivers insight into key concepts and terminology that define the essence of big data and the promise it holds to deliver sophisticated business insights. The various characteristics that distinguish big data datasets are articulated. It also describes the conceptual and logical reference architecture to manage a huge volume of data generated by various data sources of an enterprise. It also covers drivers, opportunities, and benefits of big data analytics implementation applicable to the real world.
Database: Credo Reference. Login with Your Western ID.
Predictive Intelligence Using Big Data and the Internet of Things
Predictive Intelligence Using Big Data and the Internet of Things highlights state-of-the-art research on predictive intelligence using big data, the IoT, and related areas to ensure quality assurance and compatible IoT systems.
Database: Credo Reference. Login with your Western ID.
Data Mining - Encyclopedia of Emerging Industries
Modern data mining is a process by which special software applications, utilizing statistical techniques, analyze multiple sets of data and find useful patterns or relationships between them. Once patterns or links have been established between information sets (normally large databases), data mining techniques enable users to make informed decisions or predictions based on the results of their analyses.
Database: Credo Reference. Login with your Western ID.
Analysis - Palgrave Key Concepts: Key Concepts in Business and Management Research Methods
The term analysis describes the process whereby, for example, data, a subject area or domain is examined in detail in order to better understand it. This process is likely to involve the breaking down or categorization of the area under scrutiny into manageable or understandable units or groupings. In doing this, the intention is to allow complex issues and problems to be presented and considered in a more simplified manner. (Linkable concepts embedded in this short article.)
Database: Credo Reference. Login with your Western ID.
Palgrave Key Concepts: Key Concepts in Business and Management Research Methods
Table of Contents.
Database: Credo Reference. Login with your Western ID.
Business Analysis Techniques: 99 Essential Tools for Success
The role of the business analyst is to formulate options for a way forward and produce business cases setting out conclusions and recommendations. This professional discipline requires the widest possible array of tools and the ability to use each when and where it is needed.
Database: Credo Reference. Login with your Western ID.
The PMI Guide to Business Analysis
The Standard for Business Analysis 1st ed. is a new PMI foundational standard, developed as a basis for business analysis for portfolio, program, and project management. This standard illustrates how project management processes and business analysis processes are complementary activities, where the primary focus of project management processes is the project and the primary focus of business analysis processes is the product. This is a process-based standard, aligns with A Guide to the Project Management Body of Knowledge (PMBOK Guide) 6th ed.o be used as a standard framework contributing to the business analysis body of knowledge.
Database: eBook Collection (EBSCO) Login with your Western ID.
A Guide to the Project Management Body of Knowledge (PMBOK® Guide) Sixth Edition
The PMBOK Guide – 6th ed, is PMI's flagship publication and has been updated to reflect the latest good practices in project management. Each knowledge area will contain a section entitled Approaches for Agile, Iterative and Adaptive Environments, describing how these practices integrate in project settings. It will also contain more emphasis on strategic and business knowledge—including discussion of project management business documents—and information on the PMI Talent Triangle and the essential skills for success in today's market.
Database: eBook Collection (EBSCO). Login with your Western ID.

Tableau Training Resources

R: OER/ZTC

Introduction to R
R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.
R Studio
RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.
RStudio is available in open source and commercial editions and runs on the desktop (Windows, Mac, and Linux) or in a browser connected to RStudio Server or RStudio Workbench (Debian/Ubuntu, Red Hat/CentOS, and SUSE Linux).
R for Data Science (OER Textbook)
Explore:
2 Introduction
3 Data visualisation
4 Workflow: basics
5 Data transformation
6 Workflow: scripts
7 Exploratory Data Analysis
8 Workflow: projects
Introduction to R (OER Textbook)
R is an integrated suite of software facilities for data manipulation, calculation and graphical display.
Linear Regression Using R
Linear Regression Using R: An Introduction to Data Modeling presents one of the fundamental data modeling techniques in an informal tutorial style. Learn how to predict system outputs from measured data using a detailed step-by-step process to develop, train, and test reliable regression models. Key modeling and programming concepts are intuitively described using the R programming language. All of the necessary resources are freely available online.
Basic R (STAT484 course from PennState)
The main goal here is to become familiar with basic operations in R. The R code file and data files for this lesson can be found on the Essential R - Notes on learning R page at the link.

Power BI: OER/ZTC

Power BI: A Quick Guide
Power BI is a Data Visualization and Business Intelligence tool that converts data from different data sources to interactive dashboards and BI reports. Power BI suite provides multiple software, connector, and services - Power BI desktop, Power BI service based on Saas, and mobile Power BI apps available for different platforms. These set of services are used by business users to consume data and build BI reports.
What is Power BI?
Bridge the gap between data and decision making. Connect to and visualize any data using the unified, scalable platform for self-service and enterprise business intelligence (BI) that’s easy to use and helps you gain deeper data insight. Easily connect to, model, and visualize your data, creating memorable reports personalized with your KPIs and brand. Get fast, AI-powered answers to your business questions—even when asking with conversational language.

Python: OER/ZTC

Python - Encyclopedia of Computer Science and Technology
Python is a powerful scripting and general purpose computer language. The name comes from the well-known British comedy group Monty Python. Python is particularly useful for system administrators, webmasters, and other people who have to link various files, data sources, or programs to perform their daily tasks. The language has built-in list and dictionary data structures, making it amenable to processing text and data. Python has achieved widespread use, consistently ranking among the top five to ten programming languages. (As a scripting language, it has displaced Perl to a considerable extent.)
Database: Credo Reference. Login with your Western ID.
Developing Graphics Frameworks with Python and OpenGL
Topics explored include generating geometric shapes, transforming objects with matrices, applying image-based textures to surfaces, and lighting your scene.
Database: eBook Collection. Login with your Western ID.
Python for Everybody: Exploring Data Using Python 3 (OER Textbook)
Data- oriented exercises. Topics are presented in the order needed to build increasingly sophisticated data analysis solutions. Focuseson real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming, using web services, parsing XML and JSON data, creating and using databases using Structured Query Language, and visualizing data.
Think Python: How to Think Like a Computer Scientist - 2e
Think Python is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. Includes glossary and exercises which formi a good scaffolding structure. Case studies are presented after each set of congruent concepts,

Business Division Faculty LibGuide