CSC3501 Assignment 1: Reproducible Research and Strategic Approach

This assignment delves into several key areas within data science and communication. It begins by discussing the importance of reproducible research, emphasizing how tools like Jupyter Notebooks facilitate this process. The assignment then contrasts strategic and candid communication styles, highlighting their differences in data visualization and information delivery. Finally, it explores the formation of conjectures, outlining the requirements for a rational conjecture and providing examples to illustrate the concepts. The assignment provides a comprehensive overview of these topics, supported by relevant references and examples.

Running Head: COURSE DATA VISUALIZATION
Course Data Visualization
Name of the Student
Name of the Organization
Author Note

1COURSE DATA VISUALIZATION
Reproducible Research
Reproducible research is a term, which is produced as an end-result of a research on a
specific topic having both academic research as well as the laboratory notes used in the process.
The computational capabilities of the paper in a research having data collected, code designed
for the purpose is also able to recreate something completely new with same outcome of the
research data in a similar environment is termed as reproducible research (Begley and Ioannidis,
2015). Typically a reproducible research is made of a collection of data, text files and series of
codes, which are arranged with the help of programming languages like R, Markdown with
available source of document or even with the help of a Jupyter notebook.
Data science as a domain has some key features for integration of data comprising of
reproducibility and replicability. Reproducible research can also be termed as the innate ability to
conduct analysis of data in order to achieve similar results in a new research. The reproduction of
data as well as replication of data is directly related to generation of data, whereas reproduction
of research is basically to repeat the analytical method.
The importance of reproducible research is vastly related to correctness of a gathered
evidence, newly observable points in a previously conducted research as well as to increase the
data analysis complexity.
Accuracy of observed output in a previously conducted research is reproduced in order to
confirm the correctness of a research (Boettiger, 2015). This helps in understanding the accuracy
of a result, when a previously conducted research, when repeated by someone else and achieve
similar results it is concluded to be accurate gathering and analysis of data. Similar scenario is

2COURSE DATA VISUALIZATION
applicable for negative output of a research that helps to analyze the required changes necessary
to be made to the initial results in the first place.
Observations pertaining to a research sometimes is analyzed by using a different
approach using unrelated analysis methods (Xie, 2014). Sometimes, on conducting the research
different conclusions are established by dissimilar findings of two similar research analyzed with
different approaches creating newly observable results for the research.
Increase in the complexity of analyzed data has grown at an exponential rate. The use of
data sets, which are comparatively larger require more sophisticated computational procedures
(Leek and Peng, 2015). Thus, there is an increase of demand of creating a reproducible research
for decreasing the potential occurrence of error. Human error is a prime section, which is
unavoidable, however by repeating a research to find out errors help to achieve accurate results
where reproducible research play an important role.
Jupyter Notebook is used in reproducible research in order to facilitate a structured
design of the entire process (Coombs, 2015). There are three phases involved in conducting the
procedure, which include organizing and documenting, operating on the code and preparatory
mechanisms for sharing the conducted work. There are ten rules for dividing the procedure,
which involve creating a story for the audience, documentation of procedure, division to create
easier steps, modularizing the code, recording the involved dependencies, using version control,
creation of a pipeline, explanation of data used, enabling the notebook for exploration after run
and read and final part include contribution for reproducible research.

3COURSE DATA VISUALIZATION
Strategic Communication versus Candid Communication
Strategic communication is denoted as a guiding principle and policy making with
available information that is consistent throughout related to information available of various
works and activities conducted to analyze activities in between organizations. Alberto Cairo
states that management of business require certain technical terms like corporate communication,
institutional communication, organizational communication as well as integrated
communication. The strategic communication is defined as a planning, which is systematic with
inclusion of communicational processes, development of media, flow of information as well as
image care (Thomas and Stephens, 2015). This helps in delivering appropriated message for
targeted audience ranging from media involvement to appropriate audience base for achieving
the desirable long-term effect.
Communication is termed strategic if there is a consistency of the communicational
methodology with the values, vision and mission, which helps to enhance and provide a support
in competition and strategic positioning occurring between competitors within the industry.
Strategic communication is directly related to relay of information to the audience in a
truthful and honest perception (Kahan et al., 2017). Conveying the exact meaning of an
information so that an audience is not misguided and helps in gathering exact information is an
important aspect of strategic communication. There are certain aspects of organizing a strategic
information, where a message is written at first and the subsequent information in order to
support the findings (Cairo, 2015). The most important aspect of strategic communication is
relaying an information with truthfulness and transparency. The data visualization and

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interpretation requires strategic communication approach, because the collected information is
required to be relayed to the reader with rigidness.
The book by Alberto Cairo also provides details of designing the information graphics
with the help of candid communication procedures (Frederiksson and Pallas, 2015). The use of
candid communication unlike strategic communication is based on a simple logic where
information represented in graphical form as well as visualization of data is to help a reader
understand instead of entertaining a reader.
Candid communication is used by people from the professional sphere, where the main
purpose is to increase the overall knowledge of all readers engaging with book, article or a
specific set of information’s (Holtzhausen and Zerfass, 2014). Candid communication can be
used in different domains of statistics, journalism, and information amongst others. There are
important aspects of story-telling, which has visualization as a prime part in explaining the
information. The portrayal of information in a bit disorganized fashion is an important aspect of
candid communication unlike strategic communication, where representation of information has
an organized manner associated with it (Jones et al., 2014). Candid communication is related to
stating of an information and then next process is involved in a detailed analysis of the
information provided to identify the message required to have a widespread disclosure related to
the facts. The beginning of an information and successive collection of data to support the
argument is done in strategic communication, whereas in candid communication the information
gathered to portray an information is analyzed to find the message worth sending across to the
reader.

5COURSE DATA VISUALIZATION
Strategic and candid communication have differences in between them where the
collection of data for either of the methods is done, where one is used to form the message and
on the other hand is used to display the information gathered from successive analysis.

6COURSE DATA VISUALIZATION
Curiosity to Conjectures
There is a direct relation between spending a huge amount of time on the internet with a
person’s ability to express themselves. Use of Facebook leads to decreased productivity of a
lyricist, who spends more time on communicating with a lot of people on Facebook instead of
writing lyrics for a song (Falkheimer, 2014). Therefore, it can be said that t percent increase in
use of Facebook leads to z percent decrement in productivity of a lyricist. There is an interesting
pattern, which helps to establish a probable cause-effect relationship (more Facebook = less
lyrics), and a conjecture is devised based on the provided logic.
The conjecture states that, this is an assumption, which is made based on the known
factors associated with the domain. This can be tested, if the required substances are having a
natural as well as logical flow, which means changing a variable will lead to a change in the
conjectures failure. The stated facts denote the legitimacy of a conjecture from a given point of
view. Example of conjecture can be given, where it is stated that playing with an away jersey for
Barcelona leads to loss of match. This conjecture can be stated in different ways, where one can
say this is bad luck, however given the track record of successive wins, it can simply be said that
occurrence of such an event is solely because of a better performing opponent instead of stating
that wearing away jersey leads to loss of a match.
Conjectures can be termed as appropriate it should be testable. This suggests the use of
evidence instead of claiming the occurrence of an event. There are different forms of evidence
where the analysis can be mathematical, rigorous or logical experimentation. Conjecture, which
is testable can also be falsifiable. However, a conjecture which has both the attributes of making
sense as well as testable does not conclude the process. Conjectures are created with inclusion of
various types of components where the important parts should be hard to change unless the

7COURSE DATA VISUALIZATION
meaning of the conjecture changes making it completely useless. Another aspect of a conjecture
is hypothesis. This can be given where the claim use of Facebook decreases productivity of a
lyricist has certain variables associated with it.
Thus, it can be said that a given conjecture, which is testable and has variables present in
the hypothesis also has certain elements that are naturally occurring as well as unchangeable.
The use of internet in the modern world does not have only negative aspects but some positive
aspects as well. Use of internet has become an invariable part of life, which is a naturally
occurring event, which basically suggests that a lyricist can use Facebook for his advantage
instead of wasting time which is hindering his writing capabilities. The use of conjectures is
mostly done in hypothesizing the occurrence of a situation.

8COURSE DATA VISUALIZATION
References
Begley, C.G. and Ioannidis, J.P., 2015. Reproducibility in science: improving the standard for
basic and preclinical research. Circulation research, 116(1), pp.116-126.
Boettiger, C., 2015. An introduction to Docker for reproducible research. ACM SIGOPS
Operating Systems Review, 49(1), pp.71-79.
Cairo, A., 2015. Graphics lies, misleading visuals. In New Challenges for Data Design (pp. 103-
116). Springer, London.
Coombs, W.T., 2015. The value of communication during a crisis: Insights from strategic
communication research. Business Horizons, 58(2), pp.141-148.
Falkheimer, J., 2014. The power of strategic communication in organizational development.
International Journal of Quality and Service Sciences, 6(2/3), pp.124-133.
Fredriksson, M. and Pallas, J., 2015. Strategic communication as institutional work. The
Routledge handbook of strategic communication, pp.143-156.
Holtzhausen, D. and Zerfass, A., 2014. Strategic communication: Opportunities and challenges
of the research area. In The Routledge handbook of strategic communication (pp. 27-41).
Routledge.
Jones, P., Simmons, G., Packham, G., Beynon-Davies, P. and Pickernell, D., 2014. An
exploration of the attitudes and strategic responses of sole-proprietor micro-enterprises in
adopting information and communication technology. International Small Business Journal,
32(3), pp.285-306.

9COURSE DATA VISUALIZATION
Kahan, D.M., Landrum, A., Carpenter, K., Helft, L. and Hall Jamieson, K., 2017. Science
curiosity and political information processing. Political Psychology, 38, pp.179-199.
Leek, J.T. and Peng, R.D., 2015. Opinion: Reproducible research can still be wrong: Adopting a
prevention approach. Proceedings of the National Academy of Sciences, 112(6), pp.1645-1646.
Thomas, G.F. and Stephens, K.J., 2015. An introduction to strategic communication.
Xie, Y., 2014. knitr: a comprehensive tool for reproducible research in R. Implementing
reproducible computational research, pp.3-32.