Answer:
304.13 mph
Explanation:
Data provided in the question :
The Speed of the flying aircraft = 300 mph
Tailwind of the true airspeed = 50 mph
Now,
The ground speed will be calculated as:
ground speed = 
or
The ground speed = 
or
The ground speed = 304.13 mph
Hence, the ground speed is 304.13 mph
The phase of the engineering design process which should be completed next is to test their work and is denoted as option C.
<h3>What is Engineering design?</h3>
These are the series of steps and techniques which are done by individuals in the making of functional product and services.This employs the use of scientific methods and also ensures an easier living for different individuals.
The first stage involves identifying the problem and then building a prototype through the use of different materials. This is then tested before the final finishing work is done to ensure the parts are properly placed before they are moved for evaluation by other people.
Read more about Engineering design here brainly.com/question/411733
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Answer:
b) decreased
Explanation:
Viscosity is the measure of the resistance between the layers of the liquid. On increasing temperature, the kinetic energy of the molecules of the liquid increases which in turn increase in the random motion of the molecules. Thus, the relative motion of the molecules in the liquid become easier and hence, viscosity decreases.
Answer: output value
Explanation: Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.
Supervised learning infers a function from labeled training data consisting of a set of training examples.
In supervised learning, each example consists of a pair of an input object (a vector) and a desired output value (the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way
A wide range of supervised learning algorithms are available, each having its own strengths and weaknesses.
You should now that, there is no single learning algorithm that works better than the other on all supervised learning problems
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