Answer:
a) NORM.S.INV(0.975)
Step-by-step explanation:
1) Some definitions
The standard normal distribution is a particular case of the normal distribution. The parameters for this distribution are: the mean is zero and the standard deviation of one. The random variable for this distribution is called Z score or Z value.
NORM.S.INV Excel function "is used to find out or to calculate the inverse normal cumulative distribution for a given probability value"
The function returns the inverse of the standard normal cumulative distribution(a z value). Since uses the normal standard distribution by default the mean is zero and the standard deviation is one.
2) Solution for the problem
Based on this definition and analyzing the question :"Which of the following functions computes a value such that 2.5% of the area under the standard normal distribution lies in the upper tail defined by this value?".
We are looking for a Z value that accumulates 0.975 or 0.975% of the area on the left and by properties since the total area below the curve of any probability distribution is 1, then the area to the right of this value would be 0.025 or 2.5%.
So for this case the correct function to use is: NORM.S.INV(0.975)
And the result after use this function is 1.96. And we can check the answer if we look the picture attached.
Answer: 110
Step-by-step explanation:
11x20=220 220\2=110
Answer:
18 pluse 6 equals 14
Step-by-step explanation:
just add
Answer:
The correlation coefficient of the data is -0.13, which means as the weekly mileage increases, it has no effect on the average mile time.Step-by-step explanation:
The correlation coefficient of a data set describes how closely related two variables are. Correlation coefficients close to positive 1 show a strong positive correlation, while correlation coefficients close to negative 1 show a strong negative correlation. When a correlation coefficient is close to 0, it shows no correlation between the data.
For the given data set, calculate the correlation coefficient using technology.
This r-value is closer to 0 then it is to -1. Thus, the correlation coefficient of the data is -0.13, which means as the weekly mileage increases, it has no effect on the average mile time.