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3 years ago

F(j) = 6j + 5. Find f(⅓)

Mathematics

1 answer:

galben [10]3 years ago

4 0

Answer:

f(j) = 6j + 5 if f(1/3)

f(j) = 6(1/3) + 5

f(j) = 2 + 5

f(j) = 7

Step-by-step explanation:

replace j by 1/3
distribute 6(1/3)
do addition

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Rectangle ABCDABCDA, B, C, D is graphed in the coordinate plane. The following are the vertices of the rectangle: A(-7, -5), B(-

sergey [27]

The length of side CD is equal to 11 units.

Given coordinates of rectangle are A(-7,-5), B(-7,6),C(-4,6) ,D(-4,-5)

We are require to find the length of side CD.

Rectangle is a two dimensional figure whose two opposite sides are equal to each other. Distance between two coordinates is the equal to length of a side.

We know that the distance means how far two points are located.

Coordinates of A(-7,-5), B(-7,6),C(-4,6) ,D(-4,-5).

Distance= $\sqrt{(x_{2} -x_{1} )^{2} +(y_{2} -y_{1} )^{2} }$ where ( $x_{1} ,y_{2} )(x_{2} ,y_{2} )$ are the coordinates of two ends of a line.

CD= $\sqrt{(-5-6)^{2} +(-4+4)^{2} }$

= $\sqrt{11^{2}+0^{2} }$

= $\sqrt{121}$

=11 units.

Hence the length of side CD is 11 units.

Learn more about distance at brainly.com/question/17273444

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Question is wrong as it should be :

Coordinates of rectangle A(-7,-5), B(-7,6),C(-4,6) ,D(-4,-5) and find the length of CD.

8 0

2 years ago

The distribution of weights of potato chip bags filled off a production line is unknown. However, the mean is m=13.35 OZs and th

Nikitich [7]

Answer:

a) $\mu_{\bar X} =13.35$

e.none of the above

b) $\sigma_{\bar X}= \frac{0.12}{\sqrt{36}}= 0.02$

a.0.0200

c) $z = \frac{13.32-13.35}{\frac{0.12}{\sqrt{36}}}= -1.5$

$P(\bar X< 13.32)= P(z$

a.0.0668

d) $z = \frac{13.30-13.35}{\frac{0.12}{\sqrt{36}}}= -2.5$

$z = \frac{13.36-13.35}{\frac{0.12}{\sqrt{36}}}= 0.5$

$P(13.30$

c.0.6853

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".

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Solution to the problem

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

$X \sim N(13.35,0.12)$