Answer:
(1,1)
Step-by-step explanation:
1=-2(1)+3
1= -2 +3
1=1
1=-4(1)=5
1=-4=5
1=1
Answer:
Option B - False
Step-by-step explanation:
Critical value is a point beyond which we normally reject the null hypothesis. Whereas, P-value is defined as the probability to the right of respective statistic which could either be Z, T or chi. Now, the benefit of using p-value is that it calculates a probability estimate which we will be able to test at any level of significance by comparing the probability directly with the significance level.
For example, let's assume that the Z-value for a particular experiment is 1.67, which will be greater than the critical value at 5% which will be 1.64. Thus, if we want to check for a different significance level of 1%, we will need to calculate a new critical value.
Whereas, if we calculate the p-value for say 1.67, it will give a value of about 0.047. This p-value can be used to reject the hypothesis at 5% significance level since 0.047 < 0.05. But with a significance level of 1%, the hypothesis can be accepted since 0.047 > 0.01.
Thus, it's clear critical values are different from P-values and they can't be used interchangeably.
No idea sorry! If I knew I would tell you
If we join the points we are gonna end up with a triangle, from there by finding the centroid of the triangle we will get a point which is equidistant from all the three points given in the diagram.
Formula for Centroid:
