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3 years ago

Point b is on ac between a and c. if ab is doubled and bc is also doubled, predict the effect on ac

Mathematics

1 answer:

Anton [14]3 years ago

6 0

Answer:

ac will also be doubled.

Step-by-step explanation:

We are given that the Point b is on line ac and lies between a and c.

ab is doubled

bc is also doubled

Now we have to predict the effect on ac.

Let ab= x

bc=y

ac=ab+BC

ac=x+y ----(A)

Now after increasing the length

AB =2x

BC=2y

AC=AB+BC

AC=2x+2y

AC=2(x+y)

AC=2ac (From eqn A)

Hence the length of ac will also be doubled up.

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Inessa [10]

Answer:

75%

Step-by-step explanation:

7 0

3 years ago

The time a randomly selected individual waits for an elevator in an office building has a uniform distribution with a mean of 0.

Amiraneli [1.4K]

Answer:

The mean of the sampling distribution of means for SRS of size 50 is $\mu = 0.5$ and the standard deviation is $s = 0.0409$

By the Central Limit Theorem, since we have of sample of 50, which is larger than 30, it does not matter that the underlying population distribution is not normal.

0% probability a sample of 50 people will wait longer than 45 seconds for an elevator.

Step-by-step explanation:

To solve this problem, 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 $\mu$ 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.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size, of at least 30, can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$

In this problem, we have that:

$\mu = 0.5, \sigma = 0.289$

What are the mean and standard deviation of the sampling distribution of means for SRS of size 50?

By the Central Limit Theorem

$\mu = 0.5, s = \frac{0.289}{\sqrt{50}} = 0.0409$

The mean of the sampling distribution of means for SRS of size 50 is $\mu = 0.5$ and the standard deviation is $s = 0.0409$

Does it matter that the underlying population distribution is not normal?

By the Central Limit Theorem, since we have of sample of 50, which is larger than 30, it does not matter that the underlying population distribution is not normal.

What is the probability a sample of 50 people will wait longer than 45 seconds for an elevator?

We have to use 45 seconds as minutes, since the mean and the standard deviation are in minutes.

Each minute has 60 seconds.

So 45 seconds is 45/60 = 0.75 min.

This probability is 1 subtracted by the pvalue of Z when X = 0.75. So

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

By the Central Limit Theorem

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

$Z = \frac{0.75 - 0.5}{0.0409}$

$Z = 6.11$

$Z = 6.11$ has a pvalue of 1

1-1 = 0

0% probability a sample of 50 people will wait longer than 45 seconds for an elevator.

8 0

3 years ago

How many terms are there in a geometric series if the first term is 4, the common ration is 3 and the sum of the series is 160

Marina CMI [18]

$\bf \qquad \qquad \textit{sum of a finite geometric sequence}
\\\\
S_n=\sum\limits_{i=1}^{n}\ a_1\cdot r^{i-1}\implies S_n=a_1\left( \cfrac{1-r^n}{1-r} \right)\quad 
\begin{cases}
n=n^{th}\ term\\
a_1=\textit{first term's value}\\
r=\textit{common ratio}\\
----------\\
a_1=4\\
r=3\\
S_n=160
\end{cases}$

$\bf 160=4\left( \cfrac{1-3^n}{1-3} \right)\implies 160=4\left( \cfrac{1-3^n}{-2} \right)\implies 160=-2(1-3^n)
\\\\\\
160=2(3^n-1)\implies \cfrac{160}{2}=3^n-1\implies 80=3^n-1
\\\\\\
81=3^n~~
\begin{cases}
81=3\cdot 3\cdot 3\cdot 3\\
\qquad 3^4
\end{cases}\implies 3^4=3^n\implies 4=n$

3 0

3 years ago

Lucy throws a fair six sided dice . so like the letter that matches the probability of the dice landing on a number between 1 an

irakobra [83]

Answer:

Letter B matches the probability.

Step-by-step explanation:

Lucy throws a fair six sided dice.

Probability of the dice landing on a number between 1 and 6 = $\frac{\text{Favorable outcome}}{\text{Number of events}}$

= $\frac{1}{6}$

On a number line fraction $\frac{1}{6}$ can be represented by,

An small section (A to B) will represent the fraction = $\frac{1}{6}$

Therefore, letter B will match the probability of a dice landing on a number between 1 and 6.

4 0

3 years ago

1. Solve the following system of equations, using matrix inversion method.

Jet001 [13]

Answer:

x = 142/83

y = 111/83

z = 452/83

8 0

3 years ago