Answer:
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Answer:
C
Step-by-step explanation:
Under a reflection in the line y = x
a point (x, y ) → (y, x ) , thus
Q(- 5, 2 ) → Q'(2, - 5 )
R(0, 5 ) → R'(5, 0 )
S(- 1, 2 ) → S'(2, - 1 )
Answer:
A. .325L
Step-by-step explanation:
All you have to do is had .125 with .20 to get your answer
Answer:
4x+5
Step-by-step explanation:
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.