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3 years ago

Can Someone answer this ASAP

Mathematics

1 answer:

Andrei [34K]3 years ago

6 0

Answer:

exponential, base 3

Step-by-step explanation:

It is an exponential function, and the base is 3

You might be interested in

What is the value of sinθ given that (3, −7) is a point on the terminal side of θ ? −758√58 758√58 358√58 −358√58?

Svetach [21]

Answer:

$\boxed{\sin(\theta)=-\frac{7}{58}\sqrt{58}}$

Step-by-step explanation

The given point $(3,-7)$ tells us that the terminal side of $\theta$ is in the fourth quadrant.

From the diagram in the attachment,

We can use the Pythagoras Theorem to find the length of the hypotenuse of the right triangle.

Let the hypotenuse be $h\: units$ . Then,

$h^2=7^2+3^2$

$h^2=49+9$

$h^2=58$

$\Rightarrow h=\sqrt{58}$

Now we use the sine ratio;

$\sin(\theta)=\frac{Opposite}{Hypotenuse}$ .

But since the terminal side of $\theta$ is in the fourth quadrant, the sine ratio must be negative.

This implies that;

$\sin(\theta)=-\frac{7}{\sqrt{58}}$ .

We rationalize the denominator to get;

$\sin(\theta)=-\frac{7}{58}\sqrt{58}$ .

3 0

3 years ago

American adults are watching significantly less television than they did in previous decades. In 2016, Nielson reported that Ame

goldenfox [79]

Answer:

1. 0.271 = 27.1% probability that an average American adult watches more than 309 minutes of television per day.

2. 0.417 = 41.7% probability that an average American adult watches more than 2,250 minutes of television per week.

Step-by-step explanation:

To solve this question, we need to understand the Poisson distribution and the normal distribution.

Poisson distribution:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

$P(X = x) = \frac{e^{-\lambda}*\lambda^{x}}{(x)!}$

In which

x is the number of sucesses

e = 2.71828 is the Euler number

$\lambda$ is the mean in the given interval, which is the same as the variance.

Normal distribution:

When the distribution is normal, we use the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

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.

The Poisson distribution can be approximated to the normal with $\mu = \lambda, \sigma = \sqrt{\lambda}$