The measured data is
x=[10.56, 9.52, 9.73, 9.80, 9.78, 10.91].
Calculate the mean.
m = (10.56+9.52+9.73+9.80+9.78+10.91)/6 = 10.05
Calculate the deviations from the mean.
k = x - m
= [0.51, -0.53, -0.32, -0.25, -0.27, 0.86]
Calculate the absolute deviation from the mean.
Answer: 0
Answer:
A
Step-by-step explanation:
Answer:
200.96in^2
Step-by-step explanation:
If the 1st cookie cake is 8" for its diameter and the 2nd cookie cake will have twice the length diameter of the 1st cookie cake .You will do 2 × 8 to get the diameter of the 2nd cookie cake.
First cookie cake diameter is 8".
Second cookie cake's diameter is 16".
Since we need the radius to find the area of the 2nd cookie cake we're going to do 16 / 2 which equals 8 so 8 is the radius.
A=(pi)r^2
A=(pi)8^2 *to the 2nd power means times by the same number
A=(pi)64
A= (3.14)(64)
A=200.96
=200.96^2
pi= 3.14 *for this problem
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.
