All categories

2 years ago

If b=a, where one the number line will b appear

Mathematics

1 answer:

Mashcka [7]2 years ago

7 0

Right on top of 'a'. They'll look like one single point on the number line.

You might be interested in

The equation below represents Function A and the graph represents Function B:

Snezhnost [94]

Answer:

Slope of Function B = – Slope of Function A

Step-by-step explanation:

Slope of function A= $-2$

Slope of function B=$\frac{3-1}{3-2}=2$

6 0

2 years ago

Read 2 more answers

In a regular 52 deck of cards, what is the probability of picking a random spade, a 4 of any suit and then a random diamond with

meriva

$sample \: space = 52 \: cards \\ spades = 13 \: cards \\ number \: 4s = 4 \: cards \\ diamonds = 13 \: cards \\ note \: that = \\ there \: is \: replacement \\ order \: does \: matter$

$P( \gamma ) = \frac{13}{52} \times \frac{4}{52} \times \frac{13}{52} = \frac{1}{208}$

5 0

1 year ago

Write in numeral form 4*100+2*10+8(6*1/10) +(1*1/100)

Mice21 [21]

Answer:428 7/100

Step-by-step explanation:

5 0

2 years ago

2. Find tan A for the right triangle below:

Andreyy89

Answer:

$tan A=\frac{8}{15}$

Step-by-step explanation:

According to the trigonometric ratios the tangent of an angle is the ratio of perpendicular to base, i.e.

$tan\theta=\frac{Perpendicular}{Base}$

In the provided triangle the perpendicular is 8 and base is 15.

Compute value of tan <em>A</em> as follows:

$tan\theta=\frac{Perpendicular}{Base}\\tanA=\frac{8}{15}\\$

Thus, the value of tan <em>A</em> is $\frac{8}{15}$ .

8 0

2 years ago

Let X1, X2, ... , Xn be a random sample from N(μ, σ2), where the mean θ = μ is such that −[infinity] < θ < [infinity] and

Sliva [168]

Answer:

$l'(\theta) = \frac{1}{\sigma^2} \sum_{i=1}^n (X_i -\theta)$

And then the maximum occurs when $l'(\theta) = 0$ , and that is only satisfied if and only if:

$\hat \theta = \bar X$

Step-by-step explanation:

For this case we have a random sample $X_1 ,X_2,...,X_n$ where $X_i \sim N(\mu=\theta, \sigma)$ where $\sigma$ is fixed. And we want to show that the maximum likehood estimator for $\theta = \bar X$ .

The first step is obtain the probability distribution function for the random variable X. For this case each $X_i , i=1,...n$ have the following density function:

$f(x_i | \theta,\sigma^2) = \frac{1}{\sqrt{2\pi}\sigma} exp^{-\frac{(x-\theta)^2}{2\sigma^2}} , -\infty \leq x \leq \infty$

The likehood function is given by:

$L(\theta) = \prod_{i=1}^n f(x_i)$

Assuming independence between the random sample, and replacing the density function we have this:

$L(\theta) = (\frac{1}{\sqrt{2\pi \sigma^2}})^n exp (-\frac{1}{2\sigma^2} \sum_{i=1}^n (X_i-\theta)^2)$

Taking the natural log on btoh sides we got:

$l(\theta) = -\frac{n}{2} ln(\sqrt{2\pi\sigma^2}) - \frac{1}{2\sigma^2} \sum_{i=1}^n (X_i -\theta)^2$

Now if we take the derivate respect $\theta$ we will see this:

$l'(\theta) = \frac{1}{\sigma^2} \sum_{i=1}^n (X_i -\theta)$

And then the maximum occurs when $l'(\theta) = 0$ , and that is only satisfied if and only if:

$\hat \theta = \bar X$

6 0

3 years ago