The answer is traffic flow.
An ordinary hindering traffic law says: No individual should drive upon an interstate at such an ease back speed as to obstruct or hinder the typical and sensible development of the movement, aside from when decreased speed is essential for a safe task, on account of a review, or consistence with the law.
Answer:
The group exposed to Treatment B is the control group.
Explanation:
When conducting experiments, researchers use a control group and an experimental or treatment group. For the experimental group, the independent variable is exposed to changes, while in the control group it isn't. The results of both groups are then compared to measure the influence of the modified variable.
In this case, if the group called Treatment A is the one designated as the treatment group, the Treatment B group must be the control group.
Answer:
I think it is (C)
Explanation:
I think it is C, because if you did not have good health then you cant have a great population
Answer:
In 1894 a car company cut its workers already low pay by about 25% causing the workers to strike and boycott the company. This effected railroads nationwide bringing american business to a halt. It also allowed the workers to voice their demands as a group. So for the most part, the boycott was successful, but the boycott did have some cons too. Many of the strike workers lost their jobs, and the new hired workers conditions didn't improve. Also, the unions leader was jailed, and the federal government had to get involved to stop the strike. The boycott was successful, but it came with many downsides.
Explanation:
I just had this question on edgenuity
Answer:
Training a model using labeled data and using this model to predict the labels for new data is known as: <u>Supervised Learning.</u>
Explanation:
Supervised learning is a set of techniques that allows future predictions based on behaviors or characteristics analyzed in labeled historical data. A label is nothing more than the output that the data set has returned for historical data, already known. In supervised learning, it assumes that we start from a previously labeled data set, that is, we know the value of the target attribute for the data set that we have.
