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3 years ago

Please answer question 11

Mathematics

2 answers:

storchak [24]3 years ago

4 0

Answer:

48 + 48 solve it and that is your answer

deff fn [24]3 years ago

4 0

Answer:

96 inches

Step-by-step explanation:

multiply 24 times 4 for all of the sides

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Suppose a 5x8 coefficient matrix for a system has pivot columns. Is the system consistent? Why and Why not?

Lyrx [107]

Step-by-step explanation:

All the 5 rows of the coefficient matrix (since it is of order 5×8) will have a pivot position. The augmented matrix obtained by adding a last column of constant terms to the 8 columns of the coefficient matrix will have nine columns and will not have a row of the form [0 0 0 0 0 0 0 0 1]. So the system is consistent.

7 0

3 years ago

The circle x2+y2=36 is translated 5 Units left and 4 units up where is the center of the new circle after the translation

Andrej [43]

The general equation of a circle is given by:
(x-a)^2+(x-b)^2=r^2
where:
(a,b) is the center
r is the radius

given the equation:
x^2+y^2=36
it means that the equation is centered at (0,0) with radius of 6 units. Thus a translation of 5 units to the left and 4 units up, will change the new center to
(-5,4)
thus the equation will be:
(x+5)^2+(y-4)^2=36

Answer: (x+5)^2+(y-4)^2=36

6 0

3 years ago

3. From the table below, find Prof. Xin expected value of lateness. (5 points) Lateness P(Lateness) On Time 4/5 1 Hour Late 1/10

wariber [46]

Answer:

The expected value of lateness $\frac{7}{20}$ hours.

Step-by-step explanation:

The probability distribution of lateness is as follows:

Lateness P (Lateness)

On Time 4/5

1 Hour Late 1/10

2 Hours Late 1/20

3 Hours Late 1/20

The formula of expected value of a random variable is:

$E(X)=\sum x\cdot P(X=x)$

Compute the expected value of lateness as follows:

$E(X)=\sum x\cdot P(X=x)$

$=(0\times \frac{4}{5})+(1\times \frac{1}{10})+(2\times \frac{1}{20})+(3\times \frac{1}{20})\\\\=0+\frac{1}{10}+\frac{1}{10}+\frac{3}{20}\\\\=\frac{2+2+3}{20}\\\\=\frac{7}{20}$

Thus, the expected value of lateness $\frac{7}{20}$ hours.

8 0

3 years ago

Let x be the average number of employees in a group health insurance plan, and let y be the average administrative cost as a per

Step2247 [10]

A scatter diagram has points that show the relationship between two sets of data.

We have the following data,

$\left\begin{array}{ccccccc}\mathrm{x}&3&7&15&32&74\\\mathrm{y}&40&35&30&25&17\end{array}\right$

where x is the average number of employees in a group health insurance plan and y is the average administrative cost as a percentage of claims.

To make a scatter diagram you must, draw a graph with the independent variable on the horizontal axis (in this case x) and the dependent variable on the vertical axis (in this case y). For each pair of data, put a dot or a symbol where the x-axis value intersects the y-axis value.

Linear regression is a way to describe a relationship between two variables through an equation of a straight line, called line of best fit, that most closely models this relationship.

To find the line of best fit for the points, follow these steps:

Step 1: Find $X\cdot Y$ and $X\cdot X$ as it was done in the below table.

Step 2: Find the sum of every column:

$\sum{X} = 131 ~,~ \sum{Y} = 147 ~,~ \sum{X \cdot Y} = 2873 ~,~ \sum{X^2} = 6783$

Step 3: Use the following equations to find intercept a and slope b:

$\begin{aligned} a &= \frac{\sum{Y} \cdot \sum{X^2} - \sum{X} \cdot \sum{XY} }{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 147 \cdot 6783 - 131 \cdot 2873}{ 5 \cdot 6783 - 131^2} \approx 37.05 \\ \\b &= \frac{ n \cdot \sum{XY} - \sum{X} \cdot \sum{Y}}{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 5 \cdot 2873 - 131 \cdot 147 }{ 5 \cdot 6783 - \left( 131 \right)^2} \approx -0.292\end{aligned}$

Step 4: Assemble the equation of a line

$\begin{aligned} y~&=~a ~+~ b \cdot x \\y~&=~37.05 ~-~ 0.292 \cdot x\end{aligned}$

6 0

3 years ago

The weights of a certain dog breed are approximately normally distributed with a mean of 49 pounds, and a standard deviation of

AlekseyPX

Answer:

a. 74.86%

b. 50%

c. 50%

Step-by-step explanation:

Normal Probability Distribution:

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

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Normally distributed with a mean of 49 pounds, and a standard deviation of 6 pounds.

This means that $\mu = 49, \sigma = 6$

a. Find the percentage of dogs of this breed that weigh less than 53 pounds.

The proportion is the p-value of Z when X = 53. So

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

$Z = \frac{53 - 49}{6}$

$Z = 0.67$

$Z = 0.67$ has a p-value of 0.7486.

0.7486*100% = 74.86%, which is percentage of dogs of this breed that weigh less than 53 pounds.

b. Find the percentage of dogs of this breed that weigh less than 49 pounds.

p-value of Z when X = 49, so:

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

$Z = \frac{49 - 49}{6}$

$Z = 0$

$Z = 0$ has a p-value of 0.5

0.5 = 50% of dogs of this breed that weigh less than 49 pounds.

c. Find the percentage of dogs of this breed that weigh more than 49 pounds.

1 subtracted by the p-value of Z when X = 49, so:

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

$Z = \frac{49 - 49}{6}$

$Z = 0$

$Z = 0$ has a p-value of 0.5.

1 - 0.5 = 0.5 = 50% of dogs of this breed that weigh more than 49 pounds.

8 0

3 years ago