In a bolt-manufacturing factory, it is estimated that 6% of the bolts being manufactured will be defective, with a 3% margin of
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The recursive formula for the arithmetic sequence is given as follows:
- d(1) = 8.
- d(n) = d(n - 1) - 13.
In an arithmetic sequence, the difference between consecutive terms is always the same, called common difference d.
The nth term of an arithmetic sequence is given by:
In which is the first term.
The recursive formula for the sequence is given by:
In the sequence 8, -5, -18, -31,...8,−5,−18,−31, the first term and the common ratio are given as follows:
Hence, the recursive sequence is given by:
- d(1) = 8.
- d(n) = d(n - 1) - 13.
More can be learned about arithmetic sequences at brainly.com/question/6561461
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Answer:
The purpose of testing whether β1 = 0 is to determine whether or not there is a significant relationship between x and y
Step-by-step explanation:
- The purpose of testing whether β1 = 0 is to determine whether or not the mean of the x values is equal to the mean of the y values.
No, since we are not interested if the mean for the two variables x and y are equal, we want to know if we have relationship between the two variables.
- The purpose of testing whether β1 = 0 is to determine whether or not the regression line provides a good fit for the data
No, if we want to test if the regression line provides a good fit for the data we need to use a Chi square test or other type of test.
- The purpose of testing whether β1 = 0 is to determine whether or not there is a significant relationship between x and y
Yes, the idea when we have this system of hypothesis:
Null hypothesis:
Alternative hypothesis:
Is see if we have a significant relationship between x and y, that means that the slope is not equal to 0.
- The purpose of testing whether β1 = 0 is to determine whether or not there is a cause-and-effect relationship between x and y.
No, when we conduct a regression we never can conclude that we have a cause-relation effect, that's not the goal when we conduct this, the idea is check if we have a type of relationship that can be linear, quadratic or other type of relationship betwen some variables.