Answer:
- 15
Step-by-step explanation:
1. Si μ es un ángulo agudo y cot μ = , ¿cuáles son los valores de todas las funciones trigonométricas de μ?
1 answer:
Answer:
Funciones trigonométricas de μ
sen (μ) = b/ √(a^2+ b^2)
cos (μ) = a/ √(a^2+ b^2)
tan (μ) = b/ a
cot (μ) = a/ b
sec (μ) = √(a^2+ b^2) / a
csc (μ) = √(a^2+ b^2) /b
Step-by-step explanation:
Ya que no proportionaste el valor de cot μ podemos suponer un valor = a/b para que tengas una respuesta general y reemplaces el valor de a y b de acuerdo con tu caso.
cot (μ) = a/b
_______________________________
Funciones trigonométricas
sen (μ) = cateto opuesto/ hipotenusa
cos (μ) = cateto adyacente/ hipotenusa
tan (μ) = cateto opuesto/ cateto adyacente
cot (μ) = cateto adyacente/ cateto opuesto
sec (μ) = hipotenusa / cateto adyacente
csc (μ) = hipotenusa /cateto opuesto
cot (μ) = cateto adyacente/ cateto opuesto = cot (μ) = a/ b
Por lo tanto:
Cateto adyacente = a
Cateto opuesto = b
Hipotenusa
H^2 = Cateto adyacente^2 + Cateto opuesto^2
H= √(a^2+ b^2)
Reemplaznado los valores de los catetos y la hipotenusa se obteienen los valores de las funciones trigonométricas de μ.
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Answer:
Yes, it would be unusual.
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.
If or
, the outcome X is considered unusual.
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 question, we have that:
Would it be unusual for this sample mean to be less than 19 days?
We have to find Z when X = 19. So
By the Central Limit Theorem
, so yes, the sample mean being less than 19 days would be considered an unusual outcome.