Scottish philosopher Adam Smith was known for what two philosophical ideas during the Enlightenment movement, _______________________________________ and ______________________________________________.

Social Contract and Laissez Faire

_____________________, ___________________________, and ___________________________ were discovered during the Scientific Revolution.

Chemistry, physics, and geometry

Scientific Revolution and Enlightenment Quiz

Review Scientific Revolution and Enlightenment

Standard 13: Scientific Revolution and Enlightenment

1.1 Scientific Revolution and the Enlightenment/Industrial Revolution Content Review

The Enlightenment and Scientific Revolution

During the Scientific Revolution, scientists used reason to explain the world around them. This led to the Enlightenment. The Enlightenment was a time period of new ideas about government. Enlightenment thinkers challenged the power of absolute monarchs. Absolute monarchs are kings and queens with total power. One Enlightenment thinker was John Locke. Locke believed that people were born with natural rights. These rights are Life, Liberty and Land. Locke believed that governments should protect people's natural rights and that if a government does not then the people have a right to overthrow it. Another Enlightenment thinker was Baron de Montesquieu. Montesquieu believed that the powers of government should be separated into 3 branches. This separation of powers would stop anyone from becoming too powerful. Montesquieu believed that governments ruled with the consent of the governed. That means that governments get their power from the people.

Scientific Revolution and Age of Exploration

Frankenstein's regret and the scientific revolution

Create MCQs from this text "For as long as we can remember, innovation has been a top priority—and a top frustration—for leaders. In a recent McKinsey poll, 84% of global executives reported that innovation was extremely important to their growth strategies, but a staggering 94% were dissatisfied with their organizations’ innovation performance. Most people would agree that the vast majority of innovations fall far short of ambitions. On paper, this makes no sense. Never have businesses known more about their customers. Thanks to the big data revolution, companies now can collect an enormous variety and volume of customer information, at unprecedented speed, and perform sophisticated analyses of it. Many firms have established structured, disciplined innovation processes and brought in highly skilled talent to run them. Most firms carefully calculate and mitigate innovations’ risks. From the outside, it looks as if companies have mastered a precise, scientific process. But for most of them, innovation is still painfully hit-or-miss. What has gone so wrong? The fundamental problem is, most of the masses of customer data companies create is structured to show correlations: This customer looks like that one, or 68% of customers say they prefer version A to version B. While it’s exciting to find patterns in the numbers, they don’t mean that one thing actually caused another. And though it’s no surprise that correlation isn’t causality, we suspect that most managers have grown comfortable basing decisions on correlations. Why is this misguided? Consider the case of one of this article’s coauthors, Clayton Christensen. He’s 64 years old. He’s six feet eight inches tall. His shoe size is 16. He and his wife have sent all their children off to college. He drives a Honda minivan to work. He has a lot of characteristics, but none of them has caused him to go out and buy the New York Times. His reasons for buying the paper are much more specific. He might buy it because he needs something to read on a plane or because he’s a basketball fan and it’s March Madness time. Marketers who collect demographic or psychographic information about him—and look for correlations with other buyer segments—are not going to capture those reasons. After decades of watching great companies fail, we’ve come to the conclusion that the focus on correlation—and on knowing more and more about customers—is taking firms in the wrong direction. What they really need to home in on is the progress that the customer is trying to make in a given circumstance—what the customer hopes to accomplish. This is what we’ve come to call the job to be done. We all have many jobs to be done in our lives. Some are little (pass the time while waiting in line); some are big (find a more fulfilling career). Some surface unpredictably (dress for an out-of-town business meeting after the airline lost my suitcase); some regularly (pack a healthful lunch for my daughter to take to school). When we buy a product, we essentially “hire” it to help us do a job. If it does the job well, the next time we’re confronted with the same job, we tend to hire that product again. And if it does a crummy job, we “fire” it and look for an alternative. (We’re using the word “product” here as shorthand for any solution that companies can sell; of course, the full set of “candidates” we consider hiring can often go well beyond just offerings from companies.)"

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