Answer:
D physiological condition
Explanation:
Sensation and perceptions are complimentary to each other but have different roles within the brain. Sensations are the process of experiencing the world with the five senses and sending that information to the brain. Perceptions are the way we interpret sensations.
Yea what he said good luck
Answer:
Explanation:
A charge is produced when an atom losses or gains an electron. The law of static electricity states that like charges repels, while unlike charges attracts.
1. To determine the charge on the polystyrene rod.
Place the polystyrene rod on the non-conducting rotating stand, and bring the positively charged rod close to it. If attraction occurs, it shows that it is oppositely charged. If repulsion occurs, it shows that it is positively charged.
Bringing a negatively charged rod close to the rotating polystyrene rod would attract it if the charge is opposite. But if the charge on the two rods are the same, repulsion occurs.
2a. When the polystyrene rod is positively charged, it would attract the negatively charged rod but repel the positively charged rod.
b. When the polystyrene rod is negatively charged, it would repel the negatively charged rod but attract the positively charged rod.
c. When the polystyrene rod is uncharged, no reaction would be observed when either the positively charged or negatively charged rod is brought close to it.
Explanation:
It is given that,
When the front wheels are over the scale, the weight recorded by the scale is 5800 N, F₁ = 5800 N
When the rear wheels are over the scale, the scale reads 6500 N, F₂ = 6500
The distance between the front and rear wheels is measured to be 3.20 m, x₂ = 3.2 m
We need to find the location of center of mass behind the front wheels. Let the center of is located at a distance of x₁. Thus balancing the torques we get :
On solving the above equation we get, x₂ = 1.69 m
So, the center of mass is located at a distance of 1.69 meters behind the front wheels.
Answer:
c. Performs better on training data as the training process proceeds, while performing worse on a held-out test data
Explanation:
An over-fitted model is one that will perform best on training but would fail or do worse on a held-out test data.
Such models are optimum for a just a particular set of data but would grossly failed when extrapolated to some other data set not novel to it.
- Over-fitting a model implies that a model closely corresponds to a set of data but would not perform well with others.
- It is usually as a result of a model adapting the noise and other details of a particular data set and thereby incorporates it.
- This makes it difficult for the model to fit into another data set.
