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2 years ago

There are 4 consecutive integers that have a sum of 54. What is the greatest of the 4 integers?

Mathematics

2 answers:

Maslowich2 years ago

8 0

Answer:

Step-by-step explanation:

Let the consecutive numbers be x, x + 1, x + 2, x + 3

==========

x + x + 1 + x + 2 + x + 3 = 54

4(x) + 6 = 54

4(x) = 54 - 6

4(x) = 48

x = 12

Greatest of the 4 integers:

x + 3

12 + 3

Tanya [424]2 years ago

3 0

Answer:

x + x-1 + x-2 + x-3 =54.

x-1

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An automobile dealer wants to see if there is a relationship between monthly sales and the interest rate. A random sample of 4 m

SVETLANKA909090 [29]

Answer:

a) $y=-6.254 x +75.064$

b) r =-0.932

The % of variation is given by the determination coefficient given by $r^2$ and on this case $-0.932^2 =0.8687$ , so then the % of variation explained by the linear model is 86.87%.

Step-by-step explanation:

Assuming the following dataset:

Monthly Sales (Y) Interest Rate (X)

22 9.2

20 7.6

10 10.4

45 5.3

Part a

And we want a linear model on this way y=mx+b, where m represent the slope and b the intercept. In order to find the slope we have this formula:

$m=\frac{S_{xy}}{S_{xx}}$

Where:

$S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}$

$S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}$

With these we can find the sums:

$S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=278.65-\frac{32.5^2}{4}=14.5875$

$S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i){n}}=696.9-\frac{32.5*97}{4}=-91.225$

And the slope would be:

$m=\frac{-91.225}{14.5875}=-6.254$

Nowe we can find the means for x and y like this:

$\bar x= \frac{\sum x_i}{n}=\frac{32.5}{4}=8.125$

$\bar y= \frac{\sum y_i}{n}=\frac{97}{4}=24.25$

And we can find the intercept using this:

$b=\bar y -m \bar x=24.25-(-6.254*8.125)=75.064$

So the line would be given by:

$y=-6.254 x +75.064$

Part b

For this case we need to calculate the correlation coefficient given by:

$r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}$

$r=\frac{4(696.9)-(32.5)(97)}{\sqrt{[4(278.65) -(32.5)^2][4(3009) -(97)^2]}}=-0.937$

So then the correlation coefficient would be r =-0.932

The % of variation is given by the determination coefficient given by $r^2$ and on this case $-0.932^2 =0.8687$ , so then the % of variation explained by the linear model is 86.87%.

6 0

3 years ago

Which number makes this sentence true? 7.8×3.6×1=7.8×? 1,3.6,4.6,7.8

marin [14]

In the left hand side, you're multiplying 7.8 by $3.6\times 1$

In the right hand side, you're multiplying again 7.8 by a mysterious number.

So, the unknown number must be $3.6\times 1$

Every number remains unchanged when multiplied by 1, so the answer is 3.6

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3 years ago

Ft=50,000(0.47)^t expontional growth

jonny [76]

Answer:

Step-by-step explanation:

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3 years ago

The probability of flu symptoms for a person not receiving any treatment is 0.038. In a clinical trial of a common drug used to

alexgriva [62]

Answer:

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Step-by-step explanation:

I am going to use the normal approximation to the binomial to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

Problems of normally distributed samples can be 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.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .

In this problem, we have that:

$n = 1164, p = 0.038$

$\mu = E(X) = np = 1164*0.038 = 44.232$

$\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = 6.5231$

Estimate the probability that at least 47 people experience flu symptoms.

Using continuity correction, this is $P(X \geq 47 - 0.5) = P(X \geq 46.5)$ , which is 1 subtracted by the pvalue of Z when X = 46.5.

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

$Z = \frac{46.5 - 44.232}{6.5231}$

$Z = 0.35$

$Z = 0.35$ has a 0.6368

1 - 0.6368 = 0.3632

36.32% probability that at least 47 people experience flu symptoms. This is not an unlikely event, so this suggests that flu symptoms are not an adverse reaction to the drug.

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