A bottle contains 3.6 liters of water, water drips out of the bottom of the bottle at a rate of 20 millilitres per minute, work
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Answer:
The gallons of gas the tank contain now is <u>35 1/12</u>.
Step-by-step explanation:
Given:
Fuel tank contains 1 3/4 gallons of gasoline.
Casey adds 33 1/3 gallons of gasoline to the tank.
Now, to find the total gallons of gas the tank contain.
Converting the mixed fractions into improper.
Gallons of gasoline in fuel tank .
Gallons of gasoline Casey adds .
<u>According to question:</u>
By adding we get the total gallons of gasoline now tank contain:
Therefore, the gallons of gas the tank contain now is 35 1/12.
Answer:
0.5034 = 50.34% probability that the mean weight of the sample of horses would differ from the population mean by less than 9lbs if 49 horses are sampled at random from the stable
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 the sample of horses would differ from the population mean by less than 9lbs if 49 horses are sampled at random from the stable?
This is the pvalue of Z when X = 1467 + 9 = 1476 subtracted by the pvalue of Z when X = 1467 - 9 = 1458.
X = 1476
By the Central Limit Theorem
has a pvalue of 0.7517
X = 1458
has a pvalue of 0.2483
0.7517 - 0.2483 = 0.5034
0.5034 = 50.34% probability that the mean weight of the sample of horses would differ from the population mean by less than 9lbs if 49 horses are sampled at random from the stable
Answer:
ur answer is down here in the photo thing:
Step-by-step explanation:
