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:
20.833 feet
Step-by-step explanation:
The light reflects off the mirror at the same angle that it hits it at. So the triangle formed by the beam and mirror is similar to the triangle formed by Kevin and the mirror.
Therefore, we can write and solve a proportion.
h / 10 = 6.25 / 3
h = 20.833
The beam is 20.833 feet tall.
Answer:
The number of data values between the lower quartile and the median is less than the number of data values between the upper quartile and the median.
Step-by-step explanation:
