38 Questions
What is survivorship bias prone to lead researchers to form?
Incorrect conclusions
What is an example of survivorship bias in the real estate industry?
Only featuring testimonials from happy customers
What is a common misconception about Mark Zuckerberg, Steve Jobs, and Bill Gates?
They all dropped out of college and became billionaires
What is the main concern in the scenario of Wade and Lily?
That Wade may experience survivorship bias
What might be the perception of Wade regarding Ivy League school acceptance?
That it's relatively easy to get in
What might be the perception of Lily regarding Ivy League school acceptance?
That it's relatively difficult to get in
What might be a possible misconception about the stock market based on Brienna's observation?
That the stocks will always increase in value
What is the main goal of the exercise in the scenario?
To explore the concept of survivorship bias
What kind of algorithms do common conversation bots like Siri and Alexa utilize?
Complex NLP algorithms
What is a characteristic of Deep Learning algorithms?
They use complex 'black box' neural networks
What is an example of an application of Deep Learning?
Face verification algorithm on Facebook
What does DGP stand for in the context of data analysis?
Data Generating Process
Why is it important to understand how data was collected and stored?
To ensure accurate analysis and interpretation of the data
What is essential to check when examining a dataset?
What each row and column represents, and missing values
What is a key consideration when designing a survey?
The selection probabilities
What should you examine before analyzing a survey's data?
The data protocols of the survey
What is the main issue with the woman's logic in buying stock from any company?
She is not considering the company's financial health
What is the problem with the scientists' approach to developing a cure for the virus?
They only examined patients who have already recovered
Why is Morgan hesitant to invest in Dodge Coin?
She is worried about the lack of negative reviews
What is the primary driver of the rise of AI?
The availability of billions of information points
What is data analytics?
The process of analyzing raw data to find trends and answer questions
What is the main application of data analytics in the real world?
All of the above
What does the rise of AI depend on?
The availability of billions of information points and rising computational power
What is the goal of data analytics?
To find trends and answer questions
What is the primary goal of descriptive analytics?
To summarize data and describe historical trends
What is the primary advantage of advanced analytics?
It allows for the extraction of data using machine learning and deep learning
What is one of the use cases of data analytics in healthcare?
Chatbots for medical scheduling and Xray computer vision
What is the primary function of recommender systems in e-commerce?
To show targeted and useful product recommendations to customers
How does Netflix use data analytics?
To recommend movies and videos based on past viewership data
What is the primary application of AI-enabled use cases in transportation?
Fully self-driving cars that take decisions like humans
What is a potential consequence of poor data quality?
Wasted resources and incorrect insights
What is a major concern for customers in terms of data usage?
Access to their data by unauthorized parties
What is the primary requirement for enabling AI-enabled use cases in transportation?
Highly advanced compute vision algorithms
What makes it difficult to extract meaningful insights from business data?
The sheer volume of data generated
What is the primary benefit of data analytics in various industries?
It provides a competitive edge to companies
What is a challenge of combining data from multiple sources?
Siloed data sources
What is a stage in the lifecycle of data where security is crucial?
All of the above
What can overwhelmed businesses due to the large amount of data generated?
Data generation
Learn to identify and avoid selection bias in research, which can lead to incorrect conclusions. Examples include cherry-picked testimonials and misleading success stories.
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