By negatively influencing data collection, <u>bias</u> can have a detrimental effect on analysis.
In statistical analysis, bias occurs when the data collected is not a true representation of the group under study. Bias occurs due to various mistakes or errors that occur at the time of data collection and sampling.
If a particular data is negatively influenced, then this means that there will be a bias in the expected results. Such a case can be highly detrimental especially if the studies would be implemented for a human issue.
The bias produced by a negative influence will cause errors in the analysis of the data leading to an overall wrong result.
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Answer:
B.add.
Explanation:
boolean add(element)
The add method in java inserts an element in the vector.It's return type is Boolean it returns true if the element is successfully inserted in the vector and false if the operation is unsuccessful.There is no Push operation in vector.Hence we conclude that the answer is add.
Answer:
2.4GHz
Explanation:
In the 2.4 GHz band, 1, 6, and 11 are the only non-overlapping channels
Answer:
4. Supervised learning.
Explanation:
Supervised and Unsupervised learning are both learning approaches in machine learning. In other words, they are sub-branches in machine learning.
In supervised learning, an algorithm(a function) is used to map input(s) to output(s). The aim of supervised learning is to predict output variables for given input data using a mapping function. When an input is given, predictions can be made to get the output.
Unsupervised learning on the other hand is suitable when no output variables are needed. The only data needed are the inputs. In this type of learning, the system just keeps learning more about the inputs.
Special applications of supervised learning are in image recognition, speech recognition, financial analysis, neural networking, forecasting and a whole lot more.
Application of unsupervised learning is in pre-processing of data during exploratory analysis.
<em>Hope this helps!</em>
D) a phenomenon.
It's real, there it is. There is no current explanation for it, but there it is...
