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.
Answer:
1
Step-by-step explanation:
10x -6 = 3x - 1
7x - 6 = -1
7x = 5
x = 0.71428571428 or 5/7
Answer:
x= -4
Step-by-step explanation:
distribute
combine like terms
subtract 4x from both sides
subtract 8 from both sides
divide both sides by -2
Her within reach work be 54 percent with the chance of getting to work
Answer:
27
Step-by-step explanation:
f(x) = 5x - 8
f(7) = 5(7) - 8 = 27
