Annotated Bibliographies

Spring 2019  |  Winter 2019  |  Fall 2018  

Winter 2019

 
Atkinson-Bonasio, A. (2015, April 7). What does gender equality mean for women researchers in the 21st century? Elsevier Foundation.
Retrieved from https://www.elsevier.com/connect/what-does-gender-equality-mean-forwomen- researchers-in-the-21st-century

 

An introductory theme to gender inequality evokes a sense of resistance from men and women in disagreement against “radical feminism” and suggest that women today are empowered to follow whatever career path they choose.

 
 
Castello, M. (2013-2014.). “Basic Data Types”. In T. Chiasson & D. Gregory (Eds.), Data + Design . Infoactive , (pp. 19-27).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf

An introduction to data types and levels of data measurement There is a variety of different data types and each type of data can be collected from a variety of databases in formats that one may need. The important types of measurement data is known as nominal, ordinal, interval ,and ratio.

Chhabra, E. (2017, January 31 ). The New Crop of Bra Entrepreneurs Are Finally Women. Forbes, (pp. 1-8).
Retrieved from https://www.forbes.com/sites/eshachhabra/2017/01/31/the-new-crop-of-bra-entrepreneurs-are-finally-women/#7bdd3abd6c18

The Female Bra Entrepreneurs. An introduction to a growing industry of social innovation and is now being taken over by women. Women Entrepreneurs today are creating more e-Commerce startups and understand the an organization’s purpose and vision that the consumer is in need of.

Coale, H. (n.d.). “Importance of Color, Font, and Icons”. In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 190-201).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

An explanation on design and the perception of information. covers basic design technique using principles and the tools that focus’ and clarifies the communication experience by using fonts, colors, icons and hierarchy.

 
Cooper, E. (n.d.). “Graphing the Results of Checkbox Responses”. In T. Chiasson & D. Gregory (Eds.), Data + Design : Infoactive, (pp. 135-169).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

An introduction to understanding checkbox or multiple response questions. This chapter focuses on checkbox responses and multiple response questions , where a question can be answered in a survey with more than one answer, based on the author’s design.

Croll, A.(n.d.). “About Data Aggregation”. In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 29-45). Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

Introduction of aggregation and applying it to data. When obtaining data information, the information that you started with is an important factoid. In some cases, data has been put through an analysis to the point where the the information can be altered as needed by the user.

 
Dyanna, G. (n.d.). “Additional Data Collection Methods”. In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 81-88).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

Determining types of measurement data that are difficult to access. Not all information are easy gathered by using survey. Measurements, weights, and events that happen over a period of time is difficult information to gather. The practices of collecting specific data types are relevant to the user in order to communicate the correct analysis.

 
Foo, J. (n.d.). “Finding External Data”. In T. Chiasson & D. Gregory (Eds.), Data + Design : Infoactive, (pp. 89-97).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

Finding and using external data for your research. Using additional resources to find data is means time and cost . By utilizing external data resource for your analysis can decrease the work required to collect and prepare data analysis for the end user.

 
Gregory, D. (n.d.). “What Data Cleaning Can and Can’t Catch”. In T. Chiasson & D. Gregory (Eds.), Data + Design : Infoactive, (pp. 124-146).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

An explanation of methods to follow when data cleaning is not enough. There is a general rule for cleaning datasets. Checking missing values for example, if the number of incorrect or missing values is greater than the number of correct values. Exclusion is not the same as deletion as It is important to leave all unnecessary data because if deleted, one may not be able to retrieve.

 
Law, G. (n.d.). “Intro to Survey Design.” In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 47-59). Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

The purpose and meaning behind designing accurate and verifiable surveys is important to identify its purpose. A well prepared survey collects accurate and verifiable data that allows for analysis to make concrete claims on specific topics.

 
 
Law, G. (n.d.). “Types of Survey Questions”. In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 60-80).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

An introduction to designing approp riate questions for a survey. When deciding what type of survey you will be conducting, it is important to determine between a variety of questions that will be used. A variety of questions that highlight specific surveys suggest open and closed questions, multiple choice (dichotomous questions) that can be used for a survey.

 
 
Makulec, A. (n.d.). “Anatomy of a Graphic.” In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 170-189). Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

Introduction to preparing and visualizing information. Once your chart or graph is built the next step is creating a visualization with all labels i.e, categories, axis, data labels are appropriately cited so your audience can view the visual and understand the meaning of the story.

 
 
PV, K. (n.d.). “Data Transformations”. In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 135-146).
Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

A summary on data transformations and statistical concepts. When taking a digital photo, sometimes the photo is too dark or to light. With transformation of data all alterations can be make so the communication is clear.

 
 
Tebbutt, I. (n.d.). “Types of Data Checks”. In T. Chiasson & D. Gregory (Eds.), Data + Design: Infoactive, (pp. 123-131). Retrieved from http://orm-atlas2-prod.s3.amazonaws.com/pdf/13a07b19e01a397d8855c0463d52f454.pdf
 

An in-depth look at data checking before and after processes. It is important to check your data because it is crucial to have trust in the information that is being presented. It is important to understand the importance of checking data , because there are many ways data can be incorrect or in a specific format than what is expected.

 
 
Wooding, C. (2017, July 4). The Power of the 21st Century Woman. Luxury Society , (pp. 1-5).
Retrieved from https://www.luxurysociety.com/en/articles/2017/07/21st-century-woman

An introduction to 21 st century? New concepts on Brand Marketing and Communications. Millenial women are taking a roles and equalizing the “playing field”. Today, women’s brands are shifting due to branding strategies of online direct communications.