The statement that explains such a relationship is that as the percent of woodland increases, the number of deer observed in a group decreases quickly at first and then more slowly
- Nonlinear relationship is a type of relationship that changes that takes place in the output change not in direct proportion to alterations (changes) in any of the inputs.
- This type of relationship does not produce any straight line but produces a curve line.
- Negative relationship is simply known as negative or inverse correlation that occurs between two variables. That is when that one variable increases, the other decreases, and vice-versa. As in the case of the woodland and the beer. When woodland increases, the deer decreases and vice versa
Conclusively, we can say that as the statement that explains such a relationship is that as the percent of woodland increases, the number of deer observed in a group decreases quickly at first and then more slowly
Learn more from:
brainly.com/question/18101129
Answer:
60 sec.
Explanation:
The first person has to travel 200m at 2 m/s. It will take him 200/2=100 seconds to reach the gate. The second person is moving towards the gate at 2 + 3 meters per second so it will take her 200/5 = 40 seconds to reach the gate. Therefore, person #1 needs an extra 100-40 = 60 seconds.
The Machine Learning is known to be a textbook that was written by Tom Mitchell, McGraw Hill in the year 1997.
<h3>What is the book about?</h3>
This book is known to give student a kind of single source introduction to the scope or field of machine learning.
Note that It is said to be a kind of a well written text book that is made for advanced undergraduate, graduate students, and also it can be used by developers and researchers in regards to artificial intelligence or statistics is assumed.
Learn more about Machine Learning from
brainly.com/question/25523571
#SPJ1
Answer:
b. The number of digits in a randomly selected row until a 3 is found.
Explanation:
A random variable often used in statistics and probability, is a variable that has its possible values as numerical outcomes of a random experiment or phenomenon. It is usually denoted by a capital letter, such as X.
In statistics and probability, random variables are either continuous or discrete.
1. A continuous random variable is a variable that has its possible values as an infinite value, meaning it cannot be counted.
2. A discrete random variable is a variable that has its possible values as a finite value, meaning it can be counted.
Also, any random variable that meets certain conditions defined in a research study.
Hence, an example of a geometric random variables is the number of digits in a randomly selected row until a 3 is found.
