find the mean of the distribution​

Answer:

x=9

Step-by-step explanation:

It’s 9 trust me I know it’s 9 ok it’s 9 I’m sure it’s 9 ok the answer is 9 got it 9 byee

Answer:

0.57 inches of rainfall is equivalent to 6 inches of snow

Step-by-step explanation:

The given data are presented here as follows;

[tex]\begin{array}{cc}x&y\\16&1.5\\12&1.3\\18&1.8\\15&1.5\\20&2.1\\23&2.4\\\end{array}[/tex]

The data points are approximately linear

From the the trend line of the plotted points of the graph, created with Microsoft Excel, with Forecasting, when there is 6 inches of snow the rainfall is 0.575 inches

By linear regression, we have;

Y = a + b·X

Where;

[tex]b = \dfrac{n \cdot \sum XY - \left (\sum X \right ) \cdot \left (\sum Y \right )}{n \cdot \sum X^{2} - \left (\sum X \right )^{2}}[/tex]

[tex]a = \dfrac{\sum Y - b \cdot \sum X}{n}[/tex]

∑x = 104

∑y = 10.6

∑(x·y) = 191.7

(∑x)·(∑y) = 1102.4

(∑x)² = 10816

n = 6

SigX^2 = 1878

Plugging in the values, gives;

[tex]b = \dfrac{6 \times191.7 - 1102.4}{6 \times 1878 - 10816} \approx 0.10575[/tex]

[tex]a = \dfrac{10.6 - 0.10575 \times 104}{6} \approx -0.06637[/tex]

Therefore;

Y = 0.10575·x - 0.06637

When x = 6 inches, we have;

Y = 0.10575 × 6 - 0.06637 = 0.56813

Y = 0.56813 inches ≈ 0.57 inches of rainfall

Therefore;

0.57 inches of rainfall is equivalent to 6 inches of snow

Answer:

40% probability that it lands on a number that is prime.

Step-by-step explanation:

A probability is the number of desired outcomes divided by the number of total outcomes.

10 sided dice

So 10 total outcomes.

Prime numbers:

Of those, 2, 3, 5 and 7 are prime, so 4 of the outcomes.

4*100/10 = 40%

40% probability that it lands on a number that is prime.

Answer:

I think this ans may help you

Answer:

26-33-40-47-54-61-68-75-82-89-96

Answer:

0.3409 = 34.09% probability that under 70% color their hair in a group of 85 older women.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the Central Limit Theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

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 normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex].

72% report that they color their hair to hide their gray.

This means that [tex]\mu = p = 0.72[/tex]

What is the probability that under 70% color their hair in a group of 85 older women?

For a sample of 85, we have that [tex]s = \sqrt{\frac{0.72*0.28}{85}} = 0.0487[/tex]

This probability is the pvalue of Z when X = 0.7. So

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{0.7 - 0.72}{0.0487}[/tex]

[tex]Z = -0.41[/tex]

[tex]Z = -0.41[/tex] has a pvalue of 0.3409

0.3409 = 34.09% probability that under 70% color their hair in a group of 85 older women.

Answer:

6.8 miles

Step-by-step explanation:

First, create the equation representing Chelsey's miles compared to Kyle's:

c = k + 2.8

Next, find how many miles Chelsey runs if Kyle runs 4 miles.

Plug in 4 as k into the equation:

c = k + 2.8

c = 4 + 2.8

c = 6.8

So, Chelsey runs 6.8 miles

Answer:

Each day after school, Chelsey runs 2.8 miles farther than Kyle.

Part A. Write an equation that represents the number of miles Chelsey runs, c, compared with Kyle, k.

plzz help

Part B. If Kyle runs 4 miles, how many miles does Chelsey run?

Let the miles walk by Chelesy be x

Now,

x = 4 + 2.8

x = 6.8 miles

Therefore,

[tex] \\ [/tex]

Answer:

[tex] A_{sector} \approx \: 80.38 \: {ft}^{2} [/tex]

Step-by-step explanation:

[tex] A_{sector} = \frac{ \theta}{360 \degree} \times \pi {r}^{2} \\ \\ A_{sector} = \frac{144 \degree}{360 \degree} \times 3.14 \times {(8)}^{2} \\ \\ A_{sector} = 0.4 \times 3.14 \times {(8)}^{2} \\ \\ A_{sector} = 80.384 \\ \\ A_{sector} \approx \: 80.38 \: {ft}^{2} [/tex]

Answer:

0.43

Step-by-step explanation:

x = sin^-1(0.4)

x = 23.57

tan(23.57) = 0.436

Answer:

11. 1/3

12. 2/5

13. 1/4

14. 1/5

15. 1/3

Step-by-step explanation:

Divide by GCF

Answer:

???

Step-by-step explanation:

moris code?

Answer:

c, none of the above

Step-by-step explanation:

khan

Answer:

The sampling distribution of the time spent studying has an approximately normal distribution, with mean 2.2 and standard deviation 0.1414.

Step-by-step explanation:

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Each student:

Mean of 2.2 hours, standard deviation of 2 hours.

Sampling distribution of the time spent studying has approximate distribution

Sample of 200.

By the Central Limit Theorem,

Approximately normal

Mean 2.2

Standard deviation [tex]s = \frac{2}{\sqrt{200}} = 0.1414[/tex]

The sampling distribution of the time spent studying has an approximately normal distribution, with mean 2.2 and standard deviation 0.1414.

W=4 ANS. FOR THE WIDTH. L=2*4=8 ANS.

Mark as brainlist

Answer:

puro puto✌✌✌✌

Answer:

1.23× 10 ^8

Step-by-step explanation:

mark brainliest

Answer:

x= 2 or x=3

Step-by-step explanation:

Both satisfy the equation. I hope this helped.

Answer:

x=2 or x=3

Step-by-step explanation:

just took the test it is C

Answer:

184

Step-by-step explanation:

What you can do is just divide 904/360 and the remeinder is the answer so for this 1080 is too big so 720 and it is 904-720=184

Answer:

24√2

Step-by-step explanation:

Let the side of the square be x

If the diagonal is 12m (hypotenuse), then;

x^2 + x^2 = 12^2

2x^2 = 144

x^2 = 144/2

x^2 = 72

x = √72

x = √36*2

x = 6√2

Perimeter of the square garden = 4x

Perimeter of the square garden = 4(6√2)

Perimeter of the square garden = 24√2

Answer:

1800/60=30

Step-by-step explanation:

Answer:

the first answer is correct

Answer:

$4.58

Step-by-step explanation:

Add all of your numbers up.

$27.50

Divide by 6

4.58 is the average.

i hope this helps, good luck :)

Answer:

Population = 75,342 households

Sample = 400 randomly selected households

The percentage who live in a single household unit = Parameter

The average of 2.9 person per household of all households in the city = parameter

The $65,000 median family income of all the households in the city = Parameter

Step-by-step explanation:

The population refers to all the entire elements, observations or subject which fits into a particular study. In the scenario above, the entire household in the city of study. That is, the 75,342 households.

The sample is the subset of the population which is a smaller set of observation meant to be representative of the larger population. The sample here is the 400 randomly selected households.

Parameter differs from statistics in that numerical estimates or calculations obtained from the population is called the parameter while the numerical characteristics derived from the sample is called statistic.

In this exercise we have to use the knowledge of probability to calculate the chances of choosing a TV approved by the quality control, so:

400  randomly selected households

So, based on the information given in the statement, we have:

Some parameters for this equation are:

The inhabitants of a place refers to all the complete essential feature, attention or subject that fits into the study. In the sequence of events above, the complete household fashionable the city of study. That is, the 75,342 households.

The sample exist the subset of the inhabitants of a place that exist a tinier set of comment on something scrutinized intend expected representative of the best inhabitants of a place. The sample in this place happen the 400 carelessly picked households.

See more about statistics at brainly.com/question/10951564

Answer:

They have the same domain and range (0,∞)

Step-by-step explanation:

Answer:

1/12

Step-by-step explanation:

Multiply across

Hope this helps

Answer:

B,30

Step-by-step explanation:

Answer:

B,30°

Step-by-step explanation:

Answer:

9.91

Step-by-step explanation:

Answer:

answer is 0

Step-by-step explanation:

Answer:

The number of people who like winter season is 1000.

Step-by-step explanation:

Event event correspond to a set in the Venn diagram, and we use it to find the percentages.

I am going to say that:

Event A: Like summer season

Event B: Like winter season.

55% like summer season

This means that [tex]P(A) = 0.55[/tex]

20% like winter season

This means that [tex]P(B) = 0.2[/tex]

40% don't like both seasons

This means that 100% - 40% = 60% like at least one, which means that [tex]P(A \cup B) = 0.6[/tex]

Proportion who like both:

This is [tex]P(A \cap B)[/tex]. The measures are related by the following equation:

[tex]P(A \cup B) = P(A) + P(B) - P(A \cap B)[/tex]

[tex]P(A \cap B) = P(A) + P(B) - P(A \cup B)[/tex]

Using what we have

[tex]P(A \cap B) = 0.55 + 0.2 - 0.6 = 0.15[/tex]

750 like both seasons.

This is 15% of the sample. So the total number of people is t, for which:

[tex]0.15t = 750[/tex]

[tex]t = \frac{750}{0.15}[/tex]

[tex]t = 5000[/tex]

20% like winter season

Out of 5000. So

0.2*5000 = 1000

The number of people who like winter season is 1000.