All categories

3 years ago

Marcia has 412 flowers for centerpieces she uses 8 flowers for each center how many center pieces can she make

Mathematics

2 answers:

UkoKoshka [18]3 years ago

6 0

Answer:

Step-by-step explanation:

To find how many centerpieces she can make, divide 412 by 8, since she has 412 flowers and uses 8 for each one:

412/8

= 51.5

Since centerpieces can only be whole numbers in the real world, this has to be rounded down to 51.

So, she can make 51 centerpieces.

a_sh-v [17]3 years ago

5 0

Answer:

5l.5

Step-by-step explanation: 412 divieded into 8 is 51 or 51.5

You might be interested in

What is 5,183.6 X 0.0016 =

DENIUS [597]

Answer:

8.3 (nearest tenth)

Step-by-step explanation:

7 0

3 years ago

5.2.14. For the negative binomial pdf p (k; p, r) = k+r−1 (1 − p)kpr, find the maximum likelihood k estimator for p if r is know

Volgvan

Answer:

$\hat p = \frac{r}{\bar x +r}$

Step-by-step explanation:

A negative binomial random variable "is the number X of repeated trials to produce r successes in a negative binomial experiment. The probability distribution of a negative binomial random variable is called a negative binomial distribution, this distribution is known as the Pascal distribution".

And the probability mass function is given by:

$P(X=x) = (x+r-1 C k)p^r (1-p)^{x}$

Where r represent the number successes after the k failures and p is the probability of a success on any given trial.

Solution to the problem

For this case the likehoof function is given by:

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

If we replace the mass function we got:

$L(p, x_i) = \prod_{i=1}^n (x_i +r-1 C k) p^r (1-p)^{x_i}$

When we take the derivate of the likehood function we got:

$l(p,x_i) = \sum_{i=1}^n [log (x_i +r-1 C k) + r log(p) + x_i log(1-p)]$

And in order to estimate the likehood estimator for p we need to take the derivate from the last expression and we got:

$\frac{dl(p,x_i)}{dp} = \sum_{i=1}^n \frac{r}{p} -\frac{x_i}{1-p}$

And we can separete the sum and we got:

$\frac{dl(p,x_i)}{dp} = \sum_{i=1}^n \frac{r}{p} -\sum_{i=1}^n \frac{x_i}{1-p}$

Now we need to find the critical point setting equal to zero this derivate and we got:

$\frac{dl(p,x_i)}{dp} = \sum_{i=1}^n \frac{r}{p} -\sum_{i=1}^n \frac{x_i}{1-p}=0$

$\sum_{i=1}^n \frac{r}{p} =\sum_{i=1}^n \frac{x_i}{1-p}$

For the left and right part of the expression we just have this using the properties for a sum and taking in count that p is a fixed value:

$\frac{nr}{p}= \frac{\sum_{i=1}^n x_i}{1-p}$

Now we need to solve the value of $\hat p$ from the last equation like this:

$nr(1-p) = p \sum_{i=1}^n x_i$

$nr -nrp =p \sum_{i=1}^n x_i$

$p \sum_{i=1}^n x_i +nrp = nr$

$p[\sum_{i=1}^n x_i +nr]= nr$

And if we solve for $\hat p$ we got:

$\hat p = \frac{nr}{\sum_{i=1}^n x_i +nr}$

And if we divide numerator and denominator by n we got:

$\hat p = \frac{r}{\bar x +r}$

Since $\bar x = \frac{\sum_{i=1}^n x_i}{n}$

4 0

3 years ago

Use the given transformation to evaluate the integral. (10x + 10y) da r , where r is the parallelogram with vertices (−3, 12), (

Sever21 [200]

.......,,.............".............

5 0

3 years ago

In an experiment involving single-cell RNA sequencing (scRNA-seq), researchers looked at the expression levels of a particular g

sineoko [7]

The population difference within the pair is normal.

The population distribution of mice with and without diabetes are identical.

mRNA population distribution for mice with diabetes is shifted relative to the population distribution for mice without diabetes.

Conclusion,

the two population has same shape , the two samples are independent simple random samples and the two samples are paired , the population means are the same .

Hence, each of the two population distribution is normal.

To learn more about population difference

brainly.com/question/14257759?

#SPJ4

8 0

10 months ago

Which of the following is the discriminant of the polynomial below x^2+4x+5

steposvetlana [31]

Answer:

$\huge\boxed{\sf Discriminant = -4}$