Jeff brought a bottle of water for $2.He also brought some hot dogs for $3 each.Jeff did not spend more than $14 on the hot dog
and bottle of water.Which inequality can be used to find h,the number of hot dogs that Jeff could have -------------------------------------------------------------
2 answers:
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Check the picture below.
now, the diagonals cut each other in two equal halves, thus, the midpoint of GF is the same coordinates as the midpoint for EH, so let's check what the midpoint for GF is then
now, the diagonals cut each other in two equal halves, thus, the midpoint of GF is the same coordinates as the midpoint for EH, so let's check what the midpoint for GF is then
Answer:
99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are 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.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this problem, we have that:
What is the probability that the mean weight of a 50-box case of crackers is above 16 ounces?
This is 1 subtracted by the pvalue of Z when X = 16. So
By the Central Limit Theorem
has a pvalue of 0.0001
1 - 0.0001 = 0.9999
99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces