Standard Bearer Academy

The study of computer hardware An interdisciplinary field that uses scientific methods and algorithms to extract knowledge from data A branch of philosophy that studies the meaning of numbers The practice of building websites and applications

Data scientists should recycle their computers Sophisticated analysis cannot compensate for poor-quality data All data is unreliable and should not be trusted Only new data is useful; old data should be discarded

They mean exactly the same thing Correlation means two variables move together; causation means one directly causes the other Causation is weaker than correlation Correlation can only exist between three or more variables

To make reports look more attractive To hide data that contradicts your conclusions To make complex data accessible and reveal patterns that inform understanding To replace written reports entirely

Learning that requires a human teacher in the room Training an algorithm on labeled data where the correct answers are known An algorithm that supervises other computers on a network A type of learning that only works with text data

It makes the algorithm run more slowly It causes the model to learn and perpetuate existing biases, leading to unfair outcomes Biased data is actually more useful because it represents real-world conditions It only affects image recognition, not other applications

Government databases from hackers Corporations' intellectual property Individuals' personal data and privacy rights Military communications

God does not care about measurement accuracy God detests dishonest measurement; data must be collected and reported honestly Dishonest scales are acceptable if the purpose is good This verse only applies to physical weights and measures, not data

Machines cannot process data as quickly as humans Machines can identify patterns but cannot understand meaning, make moral judgments, or possess wisdom Machine learning is always more accurate than human judgment There are no fundamental limitations; machines will soon surpass human wisdom

It does not apply to technology It means we should share all data freely with everyone It means we should treat others' data with the same care and respect we would want for our own It means data scientists should always agree with their employers