Answer:
b and c
Step-by-step explanation:
1/4 divided by 4 is 1/12 so thats the incorrect one
Greater than, the highest amount you can get by multiplying 1/2 and a number lower than it, is 1.
Answer:
79
Step-by-step explanation:
171-1-91=170-91=79
Answer:
a) 9.56%
b) 0.0019
Step-by-step explanation:
a) Find the z-scores.
z = (x − μ) / σ
z₁ = (-0.0050) / 0.0030
z₁ = -1.67
z₂ = (0.0050) / 0.0030
z₂ = 1.67
Find the probability using a chart or calculator.
P(Z < -1.67 or Z > 1.67) = 2 P(Z < -1.67)
P(Z < -1.67 or Z > 1.67) = 2 (0.0478)
P(Z < -1.67 or Z > 1.67) = 0.0956
b) Use a chart or calculator to find the z-score.
P(Z < -z or Z > z) = 0.01
P(Z < -z) = 0.005
z = 2.576
Find the standard deviation.
z = (x − μ) / σ
2.576 = (0.0050) / σ
σ = 0.0019
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.
