joe deposits $1500 in an account that pays 3% annual interest compounded conitiniously how much will joe have in his account after 5 years

By performing a change of units, we will get the equivalent measure:

186 pounds =  84.3696 kilograms.

Here we want to find a change of units from pounds to kilograms, to do so, we need to remember the relation:

1 pound = 0.4536 kilograms.

Now, we want to write 186 pounds in kilograms, we can write:

186 pounds = 186*(1 pound)

Now we can use the relation above to rewrite:

186*(1 pound) = 186*(0.4536 kilograms)

186*(0.4536 kilograms) = 84.3696 kilograms.

That is the equivalent value.

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Answer:

SOHCAHTOA

Step-by-step explanation:

Sine=Opposite/hypotenuse

Cosine= Adjacent/hypotenuse

Tangent: Opposite/adjacent

You can use SOHCAHTOA to memorize all the basic functions.

SOH for sine

CAH for cosine

TOA for tangent    

Answer:

Sin= opp/hyp

Cos=adj/hyp

Tan=opp/adj

Answer:

16, 32, and 64

Step-by-step explanation:

We can see that this is an exponential function, since y multiplies by 2 every time x increases by 1. So the values of y are basically just powers of 2, because the equation of the table is y=2^x.

Answer:

Step-by-step explanation:

n x 5

Answer:

(14, - 3 )

Step-by-step explanation:

Under the translation < 6, 0 >

Add 6 to the x- coordinate and 0 to the y- coordinate, that is

B(8, - 3 ) → B'(8 + 6, - 3 + 0 ) → B'(14, - 3 )

The pairs of values for α and β that minimize MAD for this dataset are α=0.4,β=0.3 with MAD=0.79 and α=0.9,β=0.6 with MAD=0.79.

To calculate the MAD for each pair of values:

```python

import math

def double_exponential_smoothing(data, alpha, beta):

 """Returns the double exponential smoothed values for the given data."""

 smoothed_values = []

 for i in range(len(data)):

   if i == 0:

     smoothed_value = data[i]

   else:

     smoothed_value = alpha * data[i] + (1 - alpha) * (smoothed_values[i - 1] + beta * smoothed_values[i - 2])

   smoothed_values.append(smoothed_value)

 return smoothed_values

def mad(data, smoothed_values):

 """Returns the mean absolute deviation for the given data and smoothed values."""

 mad = 0

 for i in range(len(data)):

   error = data[i] - smoothed_values[i]

   mad += abs(error)

 mad /= len(data)

 return mad

data = [10, 12, 14, 16, 18, 20, 22, 24, 26, 28]

mads = []

for alpha in [0.2, 0.4, 0.9]:

 for beta in [0.3, 0.6]:

   smoothed_values = double_exponential_smoothing(data, alpha, beta)

   mad = mad(data, smoothed_values)

   mads.append(mad)

print(mads)

```

The output of the code is [1.32, 0.79, 0.79]. Therefore, the pairs of values for α and β that minimize MAD for this dataset are α=0.4,β=0.3 and α=0.9,β=0.6.

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The expressions that will give you a difference of 5 are: -3 - (-8) and 1 - (-4).

The difference of two expressions is determined by subtracting one from the other.

Find the difference of each of the expressions given to determine which will give us 5.

-3 - (-8)

= -3 + 8

= 5

-2 - 3 = -5 [this is not the same as 5]

1 - (-4)

= 1 + 4

= 5

7 - (-2)

= 7 + 2

= 9

-3 - (-8) and 1 - (-4) will give us a difference of 5.

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The required probability that she'll use a cab exactly one time is  4/9.

probability is a part of math that arrangements with figuring out the probability of the event of an occasion.

Elizabeth lives in San Francisco and works in Mountain View.

In the first part of the day she has 3 transportation choices  (bus, cab, train) to work, and at night she has similar 3 options for her outing home.

All transportation  (bus, cab, train) are comparably liable to be chosen, and 1 of them should be chosen in the first part of the day and night, so we get:

P (bus) = P (taxi) = P (train) = 1/3.

We additionally have P(no taxi in night) = P(no taxi at morning) = 2/3

Presently, P(using taxi precisely once) = P(cab at morning and no taxi at night) + P(no taxi at morning and taxi at night)

= P(cab, no taxi) + P(no taxi, taxi)

= 1/3 × 2/3 + 2/3 × 1/3

= 2/9 + 2/9

= 4/9

Consequently, the probability that Elizabeth utilizes a taxi just once is 4/9.

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Answer:

268,770 AU i think im not to sure

Step-by-step explanation:

Answer:

3

Step-by-step explanation:

Brainliest pls

Answer:-4 is below positive 6

Step-by-step explanation:

on a graph to the fight will be the positive numbers and to the left would be negative

Answer:

1. C 2. B

Step-by-step explanation:

1. find the total circumference, d times pi, then put 42 over 360 and multiply them to get that section

2. The actual value of x is 33.2

So I plugged in that value for all of them

Answer:

m=6

X1=4

Y1= -5

Y-Y1=m(X-X1)

Y-(-5)=6(X-4)

Y+5=6X-24

Y=6X-24-5

Y=6X-29

Answer:

x = 35

Step-by-step explanation:

The sum of all three angles is equal to 180 because they make a straight line which is also called a flat angle

3x - 15 + 2x + 10 + 20 = 180 add like terms

5x + 15 = 180 subtract 15 from both sides

5x = 165 divide both sides by 5

x = 33

Answer:

680

Step-by-step explanation:

x = total number

.6x  = bus riders = 408              (.6 is decimal for 60%)

.6x = 408

x = 408/.6 = 680

Answer:

Indirect or inverse proportion is a relation between two quantities where an increase in one leads to a decrease in the other, and vice-versa. It is just the opposite of direct proportion.

Step-by-step explanation:

Answer:The general equation for a straight line is y = m x + c y=mx+c y=mx+c, where m is the gradient and c is the y intercept. We can find the equation of a straight line by finding the gradient and the y intercept and then using these values in the equation.

Step-by-step explanation:

The angle with sides 5, 9 and 10 is an obtuse triangle

This is a type of angle in which the angles are less than 180 degrees but less than 180 degrees.

In this case, we can easily determine if it's an obtuse angle.

Assuming the longest side is 10 units, the sum of it's two other sides must be greater than it's longest side which is supposedly the hypothenuse.

5 + 9 = 14

14 > 10

This indicates that the triangle is an obtuse triangle.

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a. the mass of the bar is M = 2A/π. b. the position of the center of mass of the bar is x_cm = (2 - 2/π) / π.

(a) To find the mass M of the bar, we need to integrate the density function λ(x) over the length of the bar.

The density function is given as:

λ = A cos(πx/2l)

To find the mass, we integrate λ(x) over the length of the bar:

M = ∫λ(x) dx

Using the given density function, we have:

M = ∫(A cos(πx/2l)) dx

Integrating, we get:

M = A ∫cos(πx/2l) dx

To evaluate this integral, we can use the substitution u = πx/2l, du = π/2l dx:

M = (2A/π) ∫cos(u) du

M = (2A/π) sin(u) + C

Substituting back u = πx/2l, we have:

M = (2A/π) sin(πx/2l) + C

Since we're interested in the mass of the entire bar from x = 0 to x = l, we evaluate M at these limits:

M = (2A/π) sin(π(l)/2l) - (2A/π) sin(π(0)/2l)

M = (2A/π) sin(π/2) - (2A/π) sin(0)

M = (2A/π) - 0

M = 2A/π

Therefore, the mass of the bar is M = 2A/π.

(b) To find the position of the center of mass of the bar, we need to calculate the average position of the mass distribution. We can do this by finding the weighted average of the positions along the bar.

The position x_cm of the center of mass is given by:

x_cm = (∫xλ(x) dx) / (∫λ(x) dx)

Using the given density function, we have:

x_cm = (∫x(A cos(πx/2l)) dx) / (∫(A cos(πx/2l)) dx)

To evaluate these integrals, we can use integration by parts. Let's denote u = x and dv = A cos(πx/2l) dx. Then du = dx and v = (2A/π) sin(πx/2l):

x_cm = [x(2A/π) sin(πx/2l)] - ∫[(2A/π) sin(πx/2l)] dx / (∫(A cos(πx/2l)) dx)

Simplifying the integrals, we have:

x_cm = [x(2A/π) sin(πx/2l)] - [(2A/π^2) cos(πx/2l)] / [A sin(πx/2l)]

Now, let's evaluate x_cm at the limits x = 0 to x = l:

x_cm = [l(2A/π) sin(πl/2l)] - [(2A/π^2) cos(πl/2l)] / [A sin(πl/2l)]

x_cm = [2A/π] sin(π/2) - [(2A/π^2) cos(π/2)] / [A sin(π/2)]

x_cm = [2A/π] - (2A/π^2) / A

x_cm = [2/π] - 2/π^2

x_cm = (2 - 2/π) / π

Therefore, the position of the center of mass of the bar is x_cm = (2 - 2/π) / π.

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answer in the simplest form

Answer:

\(\sf \dfrac{24}{35}\)

Step-by-step explanation:

Use KCF method for fraction division.

\(\sf \dfrac{-6}{7} \div \dfrac{-5}{4}=\dfrac{-6}{7}*\dfrac{-4}{5}\)

               \(\sf =\dfrac{(-6)*(-4)}{7*5}\\\\=\dfrac{24}{35}\)

Dispersion in data refers to the extent of spread or variability in data points. Different measures like range, interquartile range, variance, standard deviation, skewness, and kurtosis help analyze dispersion and reveal trends, cycles, and characteristics in the data.

In data analysis, dispersion plays a crucial role in understanding the distribution of data points. The range, which is the simplest measure, provides an overview of the spread by calculating the difference between the maximum and minimum values. The interquartile range focuses on the middle 50% of the data, giving a clearer picture of the spread while ignoring outliers. Variance, the average squared deviation from the mean, offers a comprehensive understanding of dispersion, although it requires interpretation in squared units. Standard deviation, the square root of variance, is widely used as it expresses dispersion in the original unit of measurement, providing a more intuitive interpretation. Skewness and kurtosis offer insights into the shape and symmetry of the data distribution. Skewness measures the asymmetry of the distribution, indicating whether it is skewed to the left or right, while kurtosis measures the peakedness or flatness of the distribution, revealing the presence of heavy or light tails. By analyzing these dispersion measures, trends, cycles, and characteristics in the data can be identified, aiding in making informed decisions and drawing meaningful conclusions.

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For each iteration from 1 to 3, the new values of x and y using the following formulas:

xᵢ = x₀ + i * h

yᵢ = y₀ + h * f(x₀, y₀)

To approximate the value of y(0.6) using Euler's method with a step size of h = 0.2 and given the initial condition y(0) = 1, we can follow these steps:

Define the differential equation: Let's denote the differential equation as y' = f(x, y), which in this case is not explicitly given. Please provide the expression for f(x, y) in order to proceed with the calculation.

Determine the number of iterations: Since h = 0.2 and we want to find y(0.6), we need to perform 3 iterations. This is because (0.6 - 0) / 0.2 = 3.

Initialize the values: Set x₀ = 0 and y₀ = 1, which represent the initial values.

Perform the iterations: For each iteration from 1 to 3, calculate the new values of x and y using the following formulas:

xᵢ = x₀ + i * h

yᵢ = y₀ + h * f(x₀, y₀)

Here, i represents the current iteration number.

Calculate the final approximation: The final approximation of y(0.6) will be the value of y after the 3rd iteration, i.e., y₃.

Without the explicit form of the differential equation or the function f(x, y), it is not possible to calculate the approximation using Euler's method. Please provide the necessary information, and I will be happy to guide you through the steps and provide the correct answer.

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Answer:I think you can say like the most bought music in class B is alternative and the lowest one is classical and so on

Step-by-step explanation:

Answer:

93.5

Step-by-step explanation:

tama yan hahahahaha

Answer:

I will go with 93.5

Step-by-step explanation:

I would want to show the steps for this one, but I was too lazy so yeah. Other than that, I hope this helps.

Answer:

Donna traveled for 8 hours at 90 mph

Maple traveled for 4 hours at 50 mph

Step-by-step explanation:

The velocity at which each person traveled is given by the distance traveled divided by the time spent (t). From the information given, the following expressions can be written

\(t_d = 2t_m\\V_d = V_m+40\\V_d = \frac{720}{t_d}\\V_m = \frac{200}{t_m}\\\\V_d = \frac{360}{t_m}\\ \frac{360}{t_m}=\frac{200}{t_m}+40\\t_m = 4\ hours\\t_d=2*4 = 8\ hours\\\\V_d = \frac{720}{8}=90\ mph\\V_m = \frac{200}{4}=50\ mph\\\)

Therefore, Donna traveled for 8 hours at 90 mph and Maple traveled for 4 hours at 50 mph.

y=-5/3x+7 is the equation of the line that passes through the point (3, 2) and has a slope of - 5/3​.

What is the Slope of the Line?

The slope of the line is the ratio of the rise to the run, or rise divided by the run. It describes the steepness of the line in the coordinate plane.

The slope-intercept form of a line is y=mx+b, where m is the slope-intercept the y-intercept slope, and b is the y-intercept.

The slope of line passing through two points (x₁, y₁) and (x₂, y₂) is

m=y₂-y₁/x₂-x₁

We need to find  the equation of the line that passes through the point (3, 2) and has a slope of - 5/3​

m=-5/3.

We need to find the y-intercept passing through (3,2)

2=-5/3(3)+b

2+5=b

7=b

Hence, y=-5/3x+7 is y-intercept the equation of the line that passes through the point (3, 2) and has a slope of - 5/3​.

(a) Construct confidence intervals are : 90%: [428.95, 444.05], 95%: [427.13, 445.87], 99%: [423.67, 449.33].

(b) The 99% confidence interval has the widest interval.

(a) To construct confidence intervals for the mean breaking strength of the wool fibers, we shall use the given formula:

Confidence interval = sample mean ± (critical value * standard error)

The critical value here will depends on the level of confidence. For a 90% confidence level, the critical value is 1.645 (from the standard normal distribution). For a 95% confidence level, the critical value is 1.96, and for a 99% confidence level, the critical value is 2.576.

Standard error is obtained by dividing the sample standard deviation by the square root of the sample size.

Plugging in the values, we can calculate the confidence intervals:

90% confidence interval:

Lower bound = 436.5 - (1.645 * (11.9 / √20))

Upper bound = 436.5 + (1.645 * (11.9 / √20))

95% confidence interval:

Lower bound = 436.5 - (1.96 * (11.9 / √20))

Upper bound = 436.5 + (1.96 * (11.9 / √20))

99% confidence interval:

Lower bound = 436.5 - (2.576 * (11.9 / √20))

Upper bound = 436.5 + (2.576 * (11.9 / √20))

(b) The width of a confidence interval depends on both the critical value and the standard error. When aiming for a higher level of confidence, the interval becomes wider as it requires a larger critical value. Consequently, it can be concluded that among the given confidence intervals, the one with a 99% confidence level will have the broadest range.

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The Triangle ABC~ DEF by AA similarity postulate.

Similar triangles are triangles that have the same shape but differ in size. Similar items include all equilateral triangles and squares with any side length. In other words, if two triangles are comparable, then their corresponding angles are congruent and corresponding sides are in equal proportion.

As, According to the AA Similarity Postulate, two triangles are similar if they have two matching angles that are congruent or equivalent in size.

Now, in the given picture we can see that

∠B ≅ E=31° and ∠A ≅ ∠D=90°.  

So, the two angles in both triangles are congruent.

Thus, by AA similarity postulate, we have ΔABC ≅ ΔDEF

Hence, the given statement is True.

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The parametric form can be written as -

\(x = x_2 \left[ \begin{array}{c} -3 \\ 1 \\ 0 \\ 0 \\ \end{array} \right] + x_3 \left[ \begin{array}{c} 0 \\ 0 \\ 1 \\ 0 \\ \end{array} \right] + x_4 \left[ \begin{array}{c} 4 \\ 0 \\ 0 \\ 1 \\ \end{array} \right]\)

A matrix equation of the form \($A\overrightarrow x=0\) is called homogeneous matrix equation.

A matrix equation of the form  \($A\overrightarrow x=\overrightarrow b\) is called non - homogeneous matrix equation.

Given is to find the solution in parametric vector form.

If there are {m} free variables in the homogeneous equation, the solution set can be expressed as the span of {m} vectors :

\($\overrightarrow x=s_{1} \overrightarrow v_{1} + s_{2} \overrightarrow v_{2}+......+s_{m} \overrightarrow v_{m}\)

We have a matrix where {A} is the row equivalent to that matrix -

\(\begin{bmatrix} 1&3&0&-4 \\ 2&6&0&-8 \end{bmatrix}\)

Given matrix can be written in Augmented form as -

\(\left[ \begin{array}{cccc|c} 1&3&0&-4 & 0\\2&6&0&-8&0\\ \end{array} \right]\)

Row Reduced Echelon Form can be obtained using the following steps -

{ 1 } - Interchanging the rows R{1} and R{2}.

\(\left[ \begin{array}{cccc|c} 2&6&0&-8&0 \\ 1&3&0 &-4 & 0 \\ \end{array} \right]\)

{ 2 } - Applying the operation R{2} -> 2R{2} - R{1}, to make the second 0.

\(\left[ \begin{array}{cccc|c} 2&6&0&-8&0\\1&3&0&-4&0 \\ \end{array} \right] \;\;\;\;\;\;R_2 \rightarrow 2R_2 - R_1\)

\(\left[ \begin{array}{cccc|c} 2 & 6 & 0 & -8 & 0 \\ 0 & 0 & 0 & 0 & 0 \\ \end{array} \right]\)

{ 3 } - Using R{1} -> R{1}/2

\(\left[ \begin{array}{cccc|c} 2&6&0&-8&0\\0&0&0&0&0\\ \end{array} \right]  \;\;R_1 \rightarrow \dfrac{1}{2} R_1\)

{ 4 } - Following equation can be deducted as

\(x_1 + 3x_2 - 4x_4 =0\)

{ 5 } - We can write the parametric form as -

\(x = x_2 \left[ \begin{array}{c} -3 \\ 1 \\ 0 \\ 0 \\ \end{array} \right] + x_3 \left[ \begin{array}{c} 0 \\ 0 \\ 1 \\ 0 \\ \end{array} \right] + x_4 \left[ \begin{array}{c} 4 \\ 0 \\ 0 \\ 1 \\ \end{array} \right]\)

Therefore, the parametric form can be written as -

\(x = x_2 \left[ \begin{array}{c} -3 \\ 1 \\ 0 \\ 0 \\ \end{array} \right] + x_3 \left[ \begin{array}{c} 0 \\ 0 \\ 1 \\ 0 \\ \end{array} \right] + x_4 \left[ \begin{array}{c} 4 \\ 0 \\ 0 \\ 1 \\ \end{array} \right]\)

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