If m∠1 = 3x, m∠3 = 2x + 20 and m∠5 = 30, what is the value of x?

If temperature in potter's kiln dropped 760 degrees in 4 hours. On average, 190 degrees of  temperature drop per hour

What is Division?

A division is a process of splitting a specific amount into equal parts.

Given,

The temperature in potter's kiln dropped 760 degrees in 4 hours

We need to find the  average of temperature drop per hour

To find this we have to divide 760 by 4.

Seven hundred sixty divided by four.

760/4

One hundred ninety

190

For an hour 190 temperature is dropped.

Hence,  On average 190 temperature drop per hour.

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Answer:

-190

Step-by-step explanation:

Answer:

Step-by-step explanation:

1) Add 14 to both sides.

2) Simplify-13 + 14 to 1

3) Multiply both sides by 9.

4) Simplify 1 × 9 to 9.

5) Switch sides.

Therefor,theanswerisn=9.

Answer:

- The probability of a girl born to a couple using this​ technique = 0.935

- Yes, the technique does appear effective in improving the likelihood of having a girl​ baby.

Step-by-step explanation:

1) In a test of gender selection, there are 200 girls and 14 baby boys.

To obtain the probability of a girl born to a couple using this​ technique

P(girls) = n(girls) ÷ n(total)

n(girls) = 200

n(total) = 200 + 14 = 214

P(girls) = (200/214) = 0.9346 = 0.935

2) Does it appear that the technique is effective in increasing the likelihood that a baby will be a​ girl?

We use an hypothesis test to confirm this. For hypothesis testing, the first thing to define is the null and alternative hypothesis.

The null hypothesis plays the devil's advocate and usually takes the form of the opposite of the theory to be tested. It usually contains the signs =, ≤ and ≥ depending on the directions of the test.

While, the alternative hypothesis usually confirms the the theory being tested by the experimental setup. It usually contains the signs ≠, < and > depending on the directions of the test.

Normally, the proportion of new girl babies and new boy babies should be close to each other (around 0.5 each), but this claim is that this gender selection technique favours the girl babies more than the male babies.

The null is that there is no significant evidence to conclude that the gender selection technique does favour more girl babies than boy babies.

The alternative hypothesis is that there is significant evidence to conclude that the gender selection technique does favour more girl babies than boy babies.

Mathematically,

The null hypothesis is represented as

H₀: p ≤ 0.50

The alternative hypothesis is given as

Hₐ: p > 0.50

To do this test, we will use the t-distribution because no information on the population standard deviation is known

So, we compute the t-test statistic

t = (x - μ)/σₓ

x = sample proportion = 0.935

μ = p₀ = The standard proportion we are comparing against = 0.50

σₓ = standard error = √[p(1-p)/n]

where n = Sample size = 214

p = 0.935

σₓ = √[0.935×0.065/214] = 0.0168521609 = 0.01685

t = (0.935 - 0.50) ÷ 0.01685

t = 25.81

checking the tables for the p-value of this t-statistic

Degree of freedom = df = n - 1 = 214 - 1 = 213

Significance level = 0.05 (most tests are performed at this level)

The hypothesis test uses a one-tailed condition because we're testing only in one direction.

p-value (for t = 25.81, at 0.05 significance level, df = 213, with a one tailed condition) = 0.000000001

The interpretation of p-values is that

When the (p-value > significance level), we fail to reject the null hypothesis and when the (p-value < significance level), we reject the null hypothesis and accept the alternative hypothesis.

So, for this question, significance level = 0.05

p-value = 0.000000001

0.000000001 < 0.05

Hence,

p-value < significance level

This means that we reject the null hypothesis & say that there is enough evidence to conclude that the gender selection technique does favour more girl babies than boy babies.

So, yes, the technique does appear effective in improving the likelihood of having a girl​ baby.

Hope this Helps!!!

Answer:

AU:

Merc-0.39

Venus-0.72

Earth- 1

Mars- 1.52

Jupiter - 5.20

Uranus - 19.1

Neptune - 30

Years:

Merc-0.24

Venus-0.61

Earth- 1

Mars- 1.88

Uranus - 84?(maybe)

Neptune - 165

Step-by-step explanation:

edge

Answer:

Step-by-step explanation:

33

The sample size just be 752.

What is confidence interval?

A confidence interval (CI) for an unknown parameter in frequentist statistics is a range of estimations. The most popular confidence level is 95%, but other levels, such 90% or 99%, are occasionally used for computing confidence intervals. The fraction of related CIs over the long run that actually contain the parameter's true value is what is meant by the confidence level. The degree of confidence, sample size, and sample variability are all factors that might affect the width of the CI. A larger sample would result in a narrower confidence interval if all other factors remained constant. A wider confidence interval would also be required by a higher confidence level and would be produced by a sample with  (1.645 / 0.03)2 * 0.5 * 0.5

=752

Sample size = 752

= 1 - 0.42 = 0.58

margin of error = E =3 % = 0.03

At 90% confidence level z

Hence, The sample size just be 752.

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The number of times that both coins come up heads will be 26.25.

What is the expected value?

In parameter estimation, the expected value is an application of the weighted sum. Informally, the expected value is the simple average of a considerable number of individually determined outcomes of a randomly picked variable.

The expected value is given below.

E(x) = np

Where n is the number of samples and p is the probability.

If two coins are flipped. Then the total number of the event is given as,

Total = 2 x 2 = 4 {HH, HT, TH, TT}

Favorable event = 1 {HH}

The probability of getting both same, then we have

P = 1/4

Jenna flips two pennies 105 times. Then the number of times that both coins come up heads will be given as,

E(x) = p × n

E(x) = 1/4 × 105

E(x) = 26.25

The number of times that both coins come up heads will be 26.25.

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