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3 years ago

What is the value of x in the equation −x = 3 − 4x

Mathematics

2 answers:

maria [59]3 years ago

4 0

1.)
-x=3-4x+6
3x=3+6
3x=9
X=3
c
2.)
-6+x=-2
x=4
B

NISA [10]3 years ago

3 0

Answer:

1.) c - 3

2.) b - 4

Step-by-step explanation:

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How is shading a grid to show 1/10 different than 1/100

gayaneshka [121]

They are very different 1/10 is equivalent to 10% and also 0.1 but 1/100 is equivalent to 1% and 0.01

7 0

3 years ago

Janelle has a babysitting job for the sunumer. She works from 7 AM to 2 P.M. with a 30-minute, unpaid break in the middle of the

shtirl [24]

Answer: $146.25

Step-by-step explanation:

To solve the question, we need to first calculate the number of hours between 7 AM to 2 P.M which is 7 hours but we are told that there is a 30 minutes break. Therefore, he works for 6 hours 30 minutes which is 6 1/2 hours.

She's paid $4.50 pee hour, therefore the amount paid per day will be:

= 6 1/2 × $4.50

= 6.50 × $4.50

= $29.25

The amount that she'll make in 5 days will be:

= $29.25 × 5

= $146.25

7 0

3 years ago

Scores on a certain intelligence test for children between ages 13 and 15 years are approximately normally distributed with μ=10

Tju [1.3M]

Answer: 0.8238

Step-by-step explanation:

Given : Scores on a certain intelligence test for children between ages 13 and 15 years are approximately normally distributed with $\mu=106$ and $\sigma=15$ .

Let x denotes the scores on a certain intelligence test for children between ages 13 and 15 years.

Then, the proportion of children aged 13 to 15 years old have scores on this test above 92 will be :-

$P(x>92)=1-P(x\leq92)\\\\=1-P(\dfrac{x-\mu}{\sigma}\leq\dfrac{92-106}{15})\\\\=1-P(z\leq })\\\\=1-P(z\leq-0.93)=1-(1-P(z\leq0.93))\ \ [\because\ P(Z\leq -z)=1-P(Z\leq z)]\\\\=P(z\leq0.93)=0.8238\ \ [\text{By using z-value table.}]$

Hence, the proportion of children aged 13 to 15 years old have scores on this test above 92 = 0.8238

4 0

3 years ago

P(x)=58x−311

Paladinen [302]

The graph of p is less steep because it has a smaller slope of only 58 while q has a slope of 85.

4 0

3 years ago

Read 2 more answers

According to data released by FiveThirty Eight (data drawn on Monday, August 17th, 2020), Donald Trump wins an Electoral College

sineoko [7]

Answer:

a) P = 0.274925

b) required confidence interval = (0.2705589, 0.2793344)

c) FALSE

d) FALSE

e) TRUE

f) There is still probability that he would win. And it would be highly unusual if he wins assuming that the true population proportion is 0.274925.

Step-by-step explanation:

PROBABILITY

since total number of simulations is 40,000 and and number of times Donald Trump wins an Electoral College majority in the 2020 US Presidential Election is 10,997

so the required Probability will be 10,997 divided by 40,000

P = 10997 / 40000 = 0.274925

To get 95% confidence interval for the parameter in question a

(using R)

>prop.test(10997,40000)

OUTPUT

1 - Sample proportion test with continuity correction

data: 10997 out of 40000, null probability 0.5

x-squared = 8104.5, df = 1, p-value < 2.23-16

alternative hypothesis : true p ≠ 0.5

0.2705589 0.2793344

sample estimate

0.274925

∴ required confidence interval = (0.2705589, 0.2793344)

FALSE

This is a wrong interpretation of a confidence interval. It indicates that there is 95% chance that the confidence interval you calculated contains the true proportion. This is because when you perform several times, 95% of those intervals would contain the true proportion but as the confidence intervals will vary so you can't say that the true proportion is in any interval with 95% probability.

FALSE

Once again, this is a wrong interpretation of a confidence interval. The confidence interval tells us about the population parameter and not the sample statistic.

TRUE

This is a correct interpretation of a confidence interval. It indicates that if we perform sampling with same sample size (40000) several times and calculate the 95% confidence interval of population proportion for each of them, then 95% of these confidence interval should contain the population parameter.

The simulation results obtained doesn't always comply with the true population. Also, result of one simulation can't be taken for granted. We need several simulations to come to a conclusion. So, we can never ever guarantee based on a simulation result to say that Donald Trump 'Won't' or 'Shouldn't' win.

There is still probability that he would win. And it would be highly unusual if he wins assuming that the true population proportion is 0.274925.

5 0

3 years ago