Английский язык для магистрантов научная деятельность. English for master students academic activity. Учебное пособие

Lesson 4. Using the Scientific Method in Technology,

Computers and Business

VOCABULARY

BEFORE YOU READ

You are going to read the text entitled USING THE SCIENTIFIC METHOD IN TECHNOLOGY AND COMPUTERS. Answer the following questions:

1.Why is the scientific method valuable in technology?

2.How can using the scientific method of hypothesis and testing simplify the process of tracking down errors?

READING

Read the text and check your answers.

Using the Scientific Method in Technology and Computers

The scientific method is incredibly valuable in technology and related fields. It is obviously used in research and development, but it is also useful in day-to-day operations because almost everything can be quantified, testing hypotheses can be easy.

Most modern computer systems are complicated and difficult to troubleshoot. Using the scientific method of hypothesis and testing can greatly simplify the process of tracking down errors and it can help find areas of improvement. It can also help when you evaluate new technologies before implementation.

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Using the Scientific Method in Business

Many business processes benefit when using the scientific method. Shifting business landscapes and complex business relationships can make behaviors hard to predict or act counter to previous history. Instead of using previous experience, a scientific approach can help businesses grow. Big data initiative can make business information more available and easier to test with.

The scientific method can be applied in many areas. Customer satisfaction and retention numbers can be analyzed and tested upon. Profitability and finance numbers can be analyzed to form new conclusions. Making predictions on changing business practices and checking the results will help to identify and measure success or failure of the initiatives.

AFTER READING TASKS

Answer the following questions.

1.Why is scientific method used in day-to-day operations?

2.What can we say about most modern computer systems? How can the scientific method help?

3.Why can many business processes benefit when using the scientific method?

4.What areas of business can the scientific method be applied in?

TRANSLATE

Read and translate the text. Make your own glossary to it. Write a summary to the text. Consult Appendix 2 if necessary.

Scientific Thinking in Business

More than technology, businesses need the scientific method. Throughout history, innovations in instrumentation–the microscope, the

telescope, and the cyclotron–have repeatedly revolutionized science by improving scientists’ ability to measure the natural world. Now, with human behavior increasingly reliant on digital platforms like the Web and mobile apps, technology is effectively “instrumenting” the social world as well. The resulting deluge of data has revolutionary implications not only for social science but also for business decision making.

As enthusiasm for “big data” grows, skeptics warn that overreliance on data has pitfalls. Data may be biased and is almost always incomplete. It can

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lead decision makers to ignore information that is harder to obtain, or make them feel more certain than they should. The risk is that in managing what we have measured, we miss what really matters.The skeptics are right that uncritical reliance on data alone can be problematic. But so is overreliance on intuition or ideology.

So if data is unreliable and so is intuition, what is a responsible decision maker supposed to do? While there is no correct answer to this question–the world is too complicated for any one recipe to apply–it is believe that leaders across a wide range of contexts could benefit from a scientific mindset toward decision making.

A scientific mind-set takes as its inspiration the scientific method, which at its core is a recipe for learning about the world in a systematic, replicable way: start with some general question based on your experience; form a hypothesis that would resolve the puzzle and that also generates a testable prediction; gather data to test your prediction; and finally, evaluate your hypothesis relative to competing hypotheses.

The scientific method is largely responsible for the astonishing increase in our understanding of the natural world over the past few centuries. Yet it has been slow to enter the worlds of politics, business, policy, and marketing, where our prodigious intuition for human behavior can always generate explanations for why people do what they do or how to make them do something different. Because these explanations are so plausible, our natural tendency is to want to act on them without further ado. But if we have learned one thing from science, it is that the most plausible explanation is not necessarily correct. Adopting a scientific approach to decision making requires us to test our hypotheses with data.

While data is essential for scientific decision making, theory, intuition, and imagination remain important as well–to generate hypotheses in the first place, to devise creative tests of the hypotheses that we have, and to interpret the data that we collect. Data and theory, in other words, are the yin and yang of the scientific method–theory frames the right questions, while data answers the questions that have been asked. Emphasizing either at the expense of the other can lead to serious mistakes.

Also important is experimentation, which doesn’t mean “trying new things” or “being creative” but quite specifically the use of controlled experiments to tease out causal effects. In business, most of what we observe is correlation–we do X and Y happens–but often what we want to know is whether or not X caused Y. How many additional units of your new product

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did your advertising campaign cause consumers to buy? Will expanded health insurance coverage cause medical costs to increase or decline? Simply observing the outcome of a particular choice does not answer causal questions like these: we need to observe the difference between choices.

Many of the most consequential decisions offer only one opportunity to succeed.

Replicating the conditions of a controlled experiment is often difficult or impossible in business or policy settings, but increasingly it is being done in “field experiments,” where treatments are randomly assigned to different individuals or communities. For example, MIT’s Poverty Action Lab has conducted over 400 field experiments to better understand aid delivery, while economists have used such experiments to measure the impact of online advertising.

Although field experiments are not an invention of the Internet era– randomized trials have been the gold standard of medical research for decades–digital technology has made them far easier to implement. Thus, as companies like Facebook, Google, Microsoft, and Amazon increasingly reap performance benefits from data science and experimentation, scientific decision making will become more pervasive.

Nevertheless, there are limits to how scientific decision makers can be. Unlike scientists, who have the luxury of withholding judgment until sufficient evidence has accumulated, policy makers or business leaders generally have to act in a state of partial ignorance. Strategic calls have to be made, policies implemented, reward or blame assigned. No matter how rigorously one tries to base one’s decisions on evidence, some guesswork will be required.

Exacerbating this problem is that many of the most consequential decisions offer only one opportunity to succeed. One cannot go to war with half of Iraq and not the other just to see which policy works out better. Likewise, one cannot reorganize the company in several different ways and then choose the best. The result is that we may never know which good plans failed and which bad plans worked.

Even here, though, the scientific method is instructive, not for eliciting answers but rather for highlighting the limits of what can be known. We can’t help asking why Apple became so successful, or what caused the last financial crisis, or why “Gangnam Style” was the most viral video of all time. Nor can we stop ourselves from coming up with plausible answers. But in cases where we cannot test our hypothesis many times, the scientific

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method teaches us not to infer too much from any one outcome. Sometimes the only true answer is that we just do not know.

Some people find this conclusion depressing, but a scientific mind should always remain skeptical of what it knows. Be skeptical of data by all means, but also be skeptical of plausible explanations, conventional wisdom, inspiring ideologies, compelling anecdotes, and most of all your own intuition. The result should be neither total paralysis nor a slavish adherence to data, nor should it in any way exclude creativity or imagination. Rather, it should lead us to a more rational, evidence-based world.

HOME ASSIGNMENT

Find information about successful implementation of scientific methods in technology or business. Prepare a presentation. Consult Appendix 2 if necessary.

Lesson 5. Common Pitfalls in Using

the Scientific Method

VOCABULARY

BEFORE YOU READ

You are going to read the text entitled COMMON PITFALLS IN USING THE SCIENTIFIC METHOD. Answer the following questions:

1.What type of phenomenon can the scientific method be used for?

2.Are both proving and disproving the hypothesis equally valid outcomes of testing?

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READING

Read the text and check your answers.

Common Pitfalls in Using the Scientific Method

The scientific method is a powerful tool. Like any tool, though, if it is misused it can cause more damage than good.

The scientific method can only be used for testable phenomenon. This is known as falsifiability. While much in nature can be tested and measured, some areas of human experience are beyond objective observation.

Both proving and disproving the hypothesis are equally valid outcomes of testing. It is possible to ignore the outcome or inject bias to skew the results of a test in a way that will fit the hypothesis. Data in opposition to the hypothesis should not be discounted.

It is important to control for other variables and influences during testing not to skew the results. While difficult, not accounting for these could produce invalid data. For example, testing bandwidth during a holiday or measuring registrations during a sale event may introduce other factors that influence the outcome.

Another common pitfall is mixing correlation with causation. While two data points may seem to be connected, it is not necessarily true that once is directly influenced by the other. For example, an ice cream stand in town sees drops in business on the hottest days. While the data may look like the hotter the weather, the less people want ice cream, the reality is that more people are going to the beach on those days and less are in town.

AFTER READING TASKS

Answer the following questions.

1.Can we claim that the scientific method is a powerful tool? Why/Why

not?

2.Is it possible to ignore the outcome of testing?

3.Can data in opposition to the hypothesis be discounted?

4.Why is it important to control for different variables and influences during testing? Can you give an example?

5.Is mixing correlation with causation a usual pitfall? Can you give an example?

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Match the words with their definitions.

Match the words having the opposite meaning.

TRANSLATE

Read and translate the text. Make your own glossary to it. Write a summary to the text. Consult Appendix 2 if necessary.

Scientific Method Limitations

The scientific method has a number of limitations including:

Constrained by the extent of existing knowledge – developing a hypothesis and designing an experiment is based on current human knowledge. However, until viruses were discovered many diseases could not be explained e.g. smallpox.

Design of experiment is limited to observation method and instrument – e.g. discovery of viruses depended on the discovery of the electron microscope.

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BEFORE YOU READ

1.What is the most difficult before you start your research?

2.What is the difference between rational and creative thinking?

READING

Read the text called TECHNIQUES FOR GENERATING RESEARCH IDEAS and check your answers.

Techniques for generating research ideas

Before you start your research you need to have at least some idea of what you want to do. This is probably the most difficult, and yet the most important, part of your research project. Without being clear about what you are going to research it is difficult to plan how you are going to research it.

Formulating and clarifying the research topic is the starting point of your research project. Once you are clear about this you will be able to choose the most appropriate research strategy and data collection and analysis techniques.

If you have not been given an initial research idea there is a range of techniques that can be used to find and select a topic that you would like to research. They can be thought of as those that are predominantly rational thinking and those that involve more creative thinking. It is usually better to use a variety of techniques. In order to do this you will need to have some understanding of the techniques and the ways in which they work.

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