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notsponge [240]
3 years ago
14

Name the possible rational roots for the function using the Rational Root Theorem.

Mathematics
1 answer:
blondinia [14]3 years ago
6 0

Answer:

\pm 1,\pm 3,\pm 5,\pm 15,\pm \frac{1}{3},\pm \frac{5}{3}

Step-by-step explanation:

Given:

The function is given as:

f(x)= 3x^{3}-19x^{2} +23x-15

The possible rational roots for a function f(x) = a_{n}x^{n}-a_{n-1}x^{n-1} +a_{n-2}x^{n-2}+....a_{1}x+a_{0} using the Rational Root Theorem is given as:

\pm (\frac{\textrm{Factors of }a_{0}}{\textrm{Factors of } a_{n}}})

Here, a_{0}=-15,a_{n}=3

Factors of -15 = \pm1,\pm3,\pm5,\pm15

Factors of 3 = \pm1,\pm3

Now, possible roots are given as:

\pm (\frac{\textrm{Factors of }a_{0}}{\textrm{Factors of } a_{n}}})\\\\=\pm(\frac{\pm1,\pm3,\pm5,\pm15}{\pm1,\pm3})\\\\=\pm\frac{1}{1},\pm\frac{1}{3},\pm\frac{3}{1},\pm\frac{3}{3},\pm\frac{5}{1},\pm\frac{5}{3},\pm\frac{15}{1},\pm\frac{15}{3}\\\\=\pm1,\pm\frac{1}{3},\pm3,\pm1,\pm5,\pm\frac{5}{3},\pm15,\pm5\\\\=\pm1,\pm \frac{1}{3},\pm3, \pm 5, \pm \frac{5}{3},\pm15

Therefore, option 1 is correct.

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Many high school students take the AP tests in different subject areas. In 2007, of the 144,796 students who took the biology ex
Nataly [62]

Answer:

(0.582-0.485) - 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.0942  

(0.582-0.485) + 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.09978  

And the 90% confidence interval would be given (0.0942;0.09978).  

We are confident at 90% that the difference between the two proportions is between 0.0942 \leq p_A -p_B \leq 0.09978

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".  

The margin of error is the range of values below and above the sample statistic in a confidence interval.  

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".  

p_A represent the real population proportion female for Biology

\hat p_A =\frac{84199}{144796}=0.582 represent the estimated proportion female for biology

n_A=144796 is the sample size for A

p_B represent the real population proportion female for calculus AB

\hat p_B =\frac{102598}{211693}=0.485 represent the estimated proportion female for Calculus AB

n_B=211693 is the sample size required for B

z represent the critical value for the margin of error  

The population proportion have the following distribution  

p \sim N(p,\sqrt{\frac{p(1-p)}{n}})  

The confidence interval for the difference of two proportions would be given by this formula  

(\hat p_A -\hat p_B) \pm z_{\alpha/2} \sqrt{\frac{\hat p_A(1-\hat p_A)}{n_A} +\frac{\hat p_B (1-\hat p_B)}{n_B}}  

For the 90% confidence interval the value of \alpha=1-0.90=0.1 and \alpha/2=0.05, with that value we can find the quantile required for the interval in the normal standard distribution.  

z_{\alpha/2}=1.64  

And replacing into the confidence interval formula we got:  

(0.582-0.485) - 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.0942  

(0.582-0.485) + 1.64 \sqrt{\frac{0.582(1-0.582)}{144796} +\frac{0.485(1-0.485)}{211693}}=0.09978  

And the 90% confidence interval would be given (0.0942;0.09978).  

We are confident at 90% that the difference between the two proportions is between 0.0942 \leq p_A -p_B \leq 0.09978

5 0
4 years ago
Is negative 5 a rational number
katen-ka-za [31]
Yes and rational numbers are numbers that can be written as a ratio of two integers
8 0
3 years ago
A measurement template with a historcal value of 25.500 is measured 27 times and a mean value of 25.301 is recorded. What is the
QveST [7]

Complete Question

A measurement template with a historical value of 25.500 mm is measured 27 times and a mean value of 25.301 mm is recorded. What is the percent bias when the tolerance is +/- 0.3?

Answer:

The percent bias is  B = 33.167 \%  

Step-by-step explanation:

From the question we are told that

   The historical value  is  S = 25.00 \ mm

   The number of times it is measured is  n  =  7  

    The mean value is  \= x = \frac{\sum x_i }{n} = 25.301 \ mm

    The tolerance is  t =\pm 0.3 = 0.3 - (-0.3) = 0.6

Generally the percent bias is mathematically represented as

      B = 100 * \frac{\= x - \tau }{ t}

=>  B = 100 * \frac{25.301 - 25.5000 }{0.6}

=>  B = 33.167 \%  

3 0
3 years ago
0.0176165803 is estimated to what
bezimeni [28]
It most common to round to the hundredths place, this is two spaces after the decimal. 

So look two spaces right - 0.17. If the third digit (in this case 6) is higher than 5 you round the number up if its not, keep it the same. 

"6" is greater than five, so round it to about (or approximately) 0.18.
5 0
4 years ago
The distribution of resistance for resistors of a certain type is known to be normal, with 10% of all resistors having a resista
baherus [9]

Answer:

The mean is 9.65 ohms and the standard deviation is 0.2742 ohms.

Step-by-step explanation:

Problems of normally distributed samples are 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.

10% of all resistors having a resistance exceeding 10.634 ohms

This means that when X = 10.634, Z has a pvalue of 1-0.1 = 0.9. So when X = 10.634, Z = 1.28.

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

1.28 = \frac{10.634 - \mu}{\sigma}

10.634 - \mu = 1.28\sigma

\mu = 10.634 - 1.28\sigma

5% having a resistance smaller than 9.7565 ohms.

This means that when X = 9.7565, Z has a pvalue of 0.05. So when X = 9.7565, Z = -1.96.

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

-1.96 = \frac{9.7565 - \mu}{\sigma}

9.7565 - \mu = -1.96\sigma

\mu = 9.7565 + 1.96\sigma

We also have that:

\mu = 10.634 - 1.28\sigma

So

10.634 - 1.28\sigma = 9.7565 + 1.96\sigma

1.96\sigma + 1.28\sigma = 10.645 - 9.7565

3.24\sigma = 0.8885

\sigma = \frac{0.8885}{3.24}

\sigma = 0.2742

The mean is

\mu = 10.634 - 1.28\sigma = 10 - 1.28*0.2742 = 9.65

The mean is 9.65 ohms and the standard deviation is 0.2742 ohms.

8 0
4 years ago
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