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3 years ago

PLEASE help i only have 2 more questions on the same concept! and i still cant get it right :(

Mathematics

1 answer:

Law Incorporation [45]3 years ago

4 0

Answer:

343 gallons, So Sarah dumped water in the pool each minute consists of 7 gallons so if she did it for 49 minutes, thats 7 gallons each for each minute. So you do 7 times 49 which gives you how many gallons in those total minutes.

-10 Fish because they re removing fish they removed 60 for 6 days so you have to figure out how many fish they have removed each day so 60 fish divided by how many days equals how many fish they have taken out each day.

Im sorry i forgot the negative again lol

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Which best describes the strength of the model? a weak positive correlation a strong positive correlation a weak negative correl

Akimi4 [234]

Correlation coefficient helps us to know how strong is the relation between two variables. The strength of the model is a strong positive correlation.

<h3>What is the correlation coefficient?</h3>

The correlation coefficient helps us to know how strong is the relation between two variables. Its value is always between +1 to -1, where, the numerical value shows how strong is the relation between them and, the '+' or '-' sign shows whether the relationship is positive or negative.

1 indicates a strong positive relationship.
-1 indicates a strong negative relationship.
A result of zero indicates no relationship at all, therefore, independent variable.

Hence, the strength of the model is a strong positive correlation.

Learn more about Correlation Coefficients:

brainly.com/question/15353989

3 0

2 years ago

Intravenous fluid bags are filled by an automated filling machine. Assume that the fill volumes of the bags are independent, nor

iren2701 [21]

Answer:

Let X the random variable that represent the heights of a population, and for this case we know the distribution for X is given by:

$X \sim N(\mu,0.08)$

Where $\mu$ and $\sigma=0.08$

Since the distribution for X is normal then the we know that the distribution for the sample mean $\bar X$ is given by:

$\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})$

And the standard error is given by:

$SE= \frac{0.08}{\sqrt{24}}= 0.0163$

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".

Solution to the problem

Let X the random variable that represent the heights of a population, and for this case we know the distribution for X is given by:

$X \sim N(\mu,0.08)$

Where $\mu$ and $\sigma=0.08$

Since the distribution for X is normal then the we know that the distribution for the sample mean $\bar X$ is given by:

$\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})$

And the standard error is given by:

$SE= \frac{0.08}{\sqrt{24}}= 0.0163$

8 0

3 years ago

Which is the union of the two sets D= {0, 10, 12, 18, 19} and E= {18, 19}

Cloud [144]

Answer:

DUE= {0,10,12,18,19}

Step-by-step explanation:

The union of two sets is a set which contains all the elements of both the sets. thus DUE= {0,10,12,18,19}

5 0

3 years ago

Which tables shows a proportional relationship between X and Y.

Alexxandr [17]

Answer:

the secound option :)

3 0

3 years ago

A random sample of 1500 self-employed individuals was chosen and asked about the number of hours they work per week. When the da

bija089 [108]

Answer:

1. Approximately 68% work between 39 and 55 hours; 2. Approximately 47.5%; 3. 16% of self-employed individuals work less than 39 hours per week.

Step-by-step explanation:

We can solve this question using the <em>68-95-99.7 rule</em> which states that, in a normal distribution, approximately 68% (more exactly, 68.27%) of the data are about <em>one standard deviation</em> <em>above</em> and <em>below</em> the population mean, 95% (or more exactly, 95.45%) are<em> two standard deviations</em> <em>above</em> and <em>below</em> the population mean, and finally 99.7% (or more exactly, 99.73%) of the data are <em>three standard deviations above</em> and <em>below</em> the population mean.

We can convert or transform any value given in the question to the equivalent <em>z-score</em> so that we can determine how many standard deviations from the mean are any of these values. For this, we can use the z-score formula:

$\\ z = \frac{x - \mu}{\sigma}$

Where

<em>x</em> is the value given to determine how far is from the population mean.

$\\ \mu$ is the <em>population mean</em>, and

$\\ \sigma$ is the <em>population standard deviation</em>.

In this case

$\\ \mu = 47\;hours$

$\\ \sigma = 8\;hours$

We need to remember that we can use the <em>standard normal table</em> that has all the probabilities for any <em>z-score</em>, that is, <em>standardized values</em> for any normal distribution.

<h3>Solutions</h3><h3>1. Percent of 68% of the self-employed individuals work</h3>

We need to convert any value given to the equivalent z-score and proceed as we described before. So, for any range of values, we have:

For P(x>55 hours) and P(x<39 hours)

$\\ z = \frac{x - \mu}{\sigma}$

x = 55:

$\\ z = \frac{55 - 47}{8} = 1$ (a value <em>above</em> the mean).

x = 39:

$\\ z = \frac{39 - 47}{8} = -1$ (a value <em>below</em> the mean).

As we can see, from the 68-95-99.7 rule, values between x = 39 and x= 47 represent approximately 68% (or more exactly, 68.27%) of the data because they are one standard deviation above (z = 1) and one standard deviation below the mean (z = -1).

Mathematically, P(39<x<55) = 68.27% (approximately 68%). And, this seems to be the answer to the question, since the sum of P(x>55) and P(x<39) represent the complement probability for P(39<x<55), that is, 1 - 0.6827 = 0.3173 (or 31.73%), and because they are at the extremes of the normal distribution at symmetrically both sides, then, the probability for P(x<39) = (0.3173/2 = 0.1586) and P(x>55) = (0.3173/2 = 0.1586).

For the rest of the values, we have:

P(31<x<63)

For x = 31:

$\\ z = \frac{31 - 47}{8} = -2$ (below the mean)

For x = 63:

$\\ z = \frac{63 - 47}{8} = 2$ (above the mean)

Thus, P(31<x<63) (or equivalently, P(-2<z<2)) are between <em>two standard deviations</em> above and below the population mean, so this represents, according to the 68-95-99.7 rule, approximately 95% of the cases.

P(23<x<71)

For x = 23:

$\\ z = \frac{23 - 47}{8} = -3$ (below the mean)

For x = 71:

$\\ z = \frac{71 - 47}{8} = 3$ (above the mean)

Thus, P(23<x<71) are between three standard deviations above and below the population mean, and this represents, according to the 68-95-99.7 rule, approximately 99.7% of the cases.

P(39<x<55)

We already confirm that these values are between one standard deviation above and below the mean, so this represents, approximately, 68% of the cases, according to the 68-95-99.7 rule.

P(x>47)

We know that the population's mean is 47 hours, and for any normal distribution, values above and below the mean are 50% of the cases. So, P(x>47) = 50% of the cases.

Therefore, "based on the collected data we can say that approximately 68% of the self-employed work" between 39 and 55 hours.

<h3>2. Percent of self-employed individuals that work between 47 and 63 hours</h3>

Using the 68-95-99.7 rule, we can use the following reasoning: because the value for x = 63 is two standard deviations above the mean and for values of two standard deviations above and below the mean this represents 95%, and we already know that the mean = 47, the values above the mean are only the half of 95% (95/2 = 47.5%).

Then, the percent of self-employed individuals that work between 47 and 63 hours per week is 47.5%.

<h3>3. 16% of self-employed individuals work less than how many hours per week</h3>

We know from the 68-95-99.7 rule that approximately 68% of the cases are between one standard deviation below and above the mean. The complement of the values at both extremes of the normal distribution are one half of the complement below and above the mean. So, the complement of 68% is 1 - 0.68 = 0.32. Then, one half (0.32/2 = 0.16) must be below the mean and the other above the mean, at the extreme sides of the normal distribution. Then, those values for P(z<-1) represents a probability of 16%.

Using the formula for z-scores:

$\\ z = \frac{x - \mu}{\sigma}$

$\\ -1 = \frac{x - 47}{8}$