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Answer:
10.57% probability that the mean contents of the 625 sample cans is less than 9.995 ounces.
Step-by-step explanation:
The Central Limit Theorem estabilishes that, for a random variable X, with mean and standard deviation
, a large sample size can be approximated to a normal distribution with mean
and standard deviation
.
Normal probability distribution
Problems of normally distributed samples can be solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
In this problem, we have that:
What is the probability that the mean contents of the 625 sample cans is less than 9.995 ounces?
This is the pvalue of Z when X = 9.995. So
has a pvalue of 0.1057
So there is a 10.57% probability that the mean contents of the 625 sample cans is less than 9.995 ounces.
Answer:
Independent variable
Step-by-step explanation:
Independent variable :
An independent variable is a variable that speaks to an amount that is being controlled in a trial. A needy variable speaks to an amount whose worth relies upon those controls.
It is the variable in a equation that may have its worth unreservedly picked without thinking about estimations of some other variable.
For example :
In equation , x is an independent variable