Hi,
None of the above is the answer.
Hope this helps.
r3t40
The refresh is a little hard was
The given statement is true, multicollinearity exists when a variable is correlated to other variables.
What is multicollinearity ?
Correlations between two or more independent variables in a multiple regression model can be referred to as multicollinearity. When a researcher or analyst tries to figure out how well each independent variable can be utilized to predict or comprehend the dependent variable in a statistical model, multicollinearity can result in skewed or misleading conclusions.
When two or more explanatory variables in a multiple regression model have strong linear relationships with one another but not with the dependent variable, this is referred to as multicollinearity.
Since a variable is multicollinear when it is correlated with other variables, the offered statement in the question is true.
To know more about multicollinearity, go to link
brainly.com/question/29437366
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Answer:
There is no enough evidence that the viscosity is not 3000. The viscosity is not significantly different from 3000.
Step-by-step explanation:
We have to perform an hypothesis test on the mean.
The null and alternative hypothesis are:
The significance level is 0.05.
The mean of the sample is:
The standard deviation of the sample is:
The statistic t can be calculated as:
The degrees of freedom are
The P-value for t=-1.338 and df=4 is P=0.2519. The P-value is greater than the significance level, so it failed to reject the null hypothesis.
There is no enough evidence that the viscosity is not 3000.
Answer: There are 210 pages that ty read in 6 hours.
Step-by-step explanation: