Answer: i believe it’s $45
Step-by-step explanation:
Answer:
In order to test the hypothesis if the correlation coefficient it's significant we have the following hypothesis:
Null hypothesis:
Alternative hypothesis:
The statistic to check the hypothesis is given by:
And is distributed with n-2 degreed of freedom. df=n-2=10-2=8
For this case the null hypothesis represent that we don't have association betwen the dependent variable Y and the independent variable X and that means r=0. So then the best option for this case is:
The null hypothesis for the Pearson correlation coefficient states that the correlation coefficient is zero
Step-by-step explanation:
Previous concepts
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
And in order to calculate the correlation coefficient we can use this formula:
Solution to the problem
In order to test the hypothesis if the correlation coefficient it's significant we have the following hypothesis:
Null hypothesis:
Alternative hypothesis:
The statistic to check the hypothesis is given by:
And is distributed with n-2 degreed of freedom. df=n-2=10-2=8
For this case the null hypothesis represent that we don't have association betwen the dependent variable Y and the independent variable X and that means r=0. So then the best option for this case is:
The null hypothesis for the Pearson correlation coefficient states that the correlation coefficient is zero
X^3 - x^2 - x + 1 = 0
Plug in x = 1:-
1 -1 - 1 + 1 = 2 - 2 = 0 so x =1 is a root.
If it has multiplicity 3 then the function will factor to (x - 1)^3:-
(x - 1)^3 = (x - 1)(x^2 - 2x + 1) = x^3 - 2x^2 + x - x^2 + 2x - 1
= x^3 - 3x^2 + 3x - 1 so it is FALSE
The standard unit for measuring mass (in <span>International System of Units</span>) is kilogram (kg). The answer to you question is FALSE.
Answer:
11 .21 add the number together