Suppose you have two six-sided dice where each side is equally likely to land face up when rolled.
2 answers:
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Answer:
A
Step-by-step explanation:
We are given that:
And we want to find:
Remember that tangent and cotangent are co-functions. In other words, they follow the cofunction identities:
Therefore, since tan(θ) = 1.3 and cot(90° - θ) = tan(θ), then cot(90° - θ) must also be 1.3.
Our answer is A.
Answer:
1963.2 pounds (lbs.)
Step-by-step explanation:
Things to understand before solving:
- - <u>Normal Probability Distribution</u>
- The z-score formula can be used to solve normal distribution problems. In a set with mean ц and standard deviation б, the z-score of a measure X is given by:
The Z-score reflects how far the measure deviates from the mean. After determining the Z-score, we examine the z-score table to determine the p-value associated with this z-score. This p-value represents the likelihood that the measure's value is less than X, or the percentile of X. Subtracting 1 from the p-value yields the likelihood that the measure's value is larger than X.
- - <u>Central Limit Theorem</u>
- The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean ц and standard deviation б , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean ц and standard deviation
As long as n is more than 30, the Central Limit Theorem may be applied to a skewed variable. A specific kind of steel cable has an average breaking strength of 2000 pounds, with a standard variation of 100 pounds.
This means, ц = 2000 and б = 100.
A random sample of 20 cables is chosen and tested.
This means that n = 20,
Determine the sample mean that will exclude the top 95 percent of all size 20 samples drawn from the population.
This is the 100-95th percentile, or X when Z has a p-value of 0.05, or X when Z = -1.645. So
- By the Central Limit Theorem
The sample mean that will cut off the top 95% of all size 20 samples obtained from the population is 1963.2 pounds.