Multiple Choice Questions (20%)
Write 6 well-crafted multiple choice questions with 5 answer choices for each question.
The questions must include an explanation of the answer – why the correct answer is correct
AND why the incorrect choices cannot be correct.
Indicate the correct answer with (***) AND the page number reference in the chapter.
Here a few sample.
(from another class on ‘big data,’ related to but not research methods)
Sample Question #1: What is one of the most difficult things for society to accomplish in order to succeed
in the era of big data?
a. New processing technologies
b. Not knowing why, only knowing what (***, pp. 18-19)
c. By changing the amount of big data, we change the essence
d. Big data is about predictions
e. Big data is about descriptions
Explanation: Choice (b) is correct because, according to Mayer-Schönberger and Cukier, “big data refers
to things one can do at a large scale that cannot be done at a smaller one” (p.18). In this way, our society
must “shed some of its obsession for causality in exchange for simple correlations” (p.18). This is the
hardest concept for our society to understand and adopt because of our long history with making decisions
and viewing reality that is always based on why. You can find the specific quote and answer on pp. 18-19,
“Most strikingly, society will need to shed some of its obsession for causality in exchange for simple
correlations: not knowing why but only what.”
Choice (a) is incorrect because big data is more than just technology. Although “Initially the idea was that
the volume of information had grown so large that the quantity being examined no longer fit into the
memory that computers use for processing,” Mayer-Schönberger and Cukier say there is no single,
specific definition of big data. Our society is constantly evolving and innovating new technologies, and
this has never been a new concept to us. While new processing technologies are, indeed, important to the
success of big data, they are not the most crucial aspect that we, as a society, must learn to overcome. AS
stated in the text, “the real revolution is not in the machines that calculate data but in data itself and how
we use it” (p. 19).
Choice (c) is incorrect because although this is a true statement, it is not an obstacle that our society must
overcome in order to ensure that big data is successful. The example used in the book to explain this
concept is that “A movie is fundamentally different from a frozen photograph,” but that a picture drawn
by hand and a photograph of the same image are quite similar (p. 22). While it is important to be aware of
the new characteristics that are created so that we can adapt, this is a familiar act to our society. We are
constantly changing and evolving and adding new and increasing information to computers. Unlike
choice (b), we do not have a long history or tradition of being unable to grow with the acquisition of new
information of the maths and sciences. Choice (b) is a better answer because changing mindsets and
attitudes is always more difficult.
Choice (d) is incorrect because this is not a problem for our society. This is exactly why we want to use
big data. The machines that are built to operate and help calculate large amounts of information “change
fundamental aspects of life by giving it a quantitative dimension it never had before” (p. 24). Already
these systems look out for patterns so they can constantly improve predictions and be more accurate. An
example is Amazon and how it can give recommendations based off of what you and other users have
clicked on and showed a liking to. This is not an appropriate answer to the question because this is
precisely why big data exists, to help apply large amounts of data and make predictions that we could not
Choice (e) is incorrect because this is not a problem for our society. Descriptions are the opposite of
predictions in (d), and the use of big data is not for description.
Sample Question #2: Which of the following is an example of ways that random sampling succeeds in
gathering the accurate information for populations?
a. Random sampling scales easily to include subcategories
b. Random sampling reaches a niche audience effectively and precisely.
c. Random sampling reduces big data problems to more manageable data problems (***, pp. 23-25)
d. Random sampling removes all chances of biases.
e. Random sampling is for nonparametric tests.
Explanation: According to Chapter 2, pp. 23-25, random sampling is effective in low cost and
efficiency terms, yet the data can be skewed due to many different variables.
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