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german
4 years ago
7

Condensing Logarithmic Expressions In Exercise, use the properties of logarithms to rewrite the expression as the logarithm of a

single quantity.
4[In(x3 - 1) + 2 In x - In(x - 5)]
Mathematics
1 answer:
yKpoI14uk [10]4 years ago
8 0

Answer:

4ln [\frac{x^2 (x^3-1)}{x-5}]

Step-by-step explanation:

For this case we have the following expression:

4[ln(x^3-1) +2ln(x) -ln(x-5)]

For this case we can apply the following property:

a log_c (b) = log_c (b^a)

And we can rewrite the following expression like this:

2 ln(x) = ln(x^2)

And we can rewrite like this our expression:

4[ln(x^3-1) +ln(x^2) -ln(x-5)]

Now we can use the following property:

log_c (a) +log_c (b) = log_c (ab)

And we got this:

4[ln(x^3-1)(x^2) -ln(x-5)]

And now we can apply the following property:

log_c (a) -log_c (b) = log_c (\frac{a}{b})

And we got this:

4ln [\frac{x^2 (x^3-1)}{x-5}]

And that would be our final answer on this case.

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the first slope is 0 (horizontal line)

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3 years ago
Suppose you had d dollars in your bank account. You spent $22 but have at least $42 left. How much money did you have initially?
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1) What left

\boxed {d-22 \geq 42}

*Obs: remember that left at least 42 dollars. In other words, the left over is equal or more than 42 dollars.

2) At the beginning

 d-22 \geq 42 \\  \\ \boxed {d \geq 64}

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Find the area of the figure shown below and choose the appropriate result.
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Step-by-step explanation:

14

8 0
3 years ago
The least-squares regression model y =−3.4+5.2x and correlation coefficient r=−0.66 were calculated for a set of bivariate data
Makovka662 [10]

Answer:

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

For this case the value of r = -0.66

Now we can calculate the determination coeffcient:

r^2 = (-0.66)^2 = 0.4356

And then we can conclude that 43.56% of the variation in y can be explained by the explanatory variable

And then 100-43.56 = 56.44 % of the variation in y that cannot be explained by the explanatory variable

Step-by-step explanation:

For this case we need to calculate the slope with the following 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}

\bar x= \frac{\sum x_i}{n}

\bar y= \frac{\sum y_i}{n}

And we can find the intercept using this:

b=\bar y -m \bar x

And the model obtained for this case is:

y = -3.4 +5.2 x

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

And in order to calculate the correlation coefficient we can use this formula:  

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

For this case the value of r = -0.66

Now we can calculate the determination coeffcient:

r^2 = (-0.66)^2 = 0.4356

And then we can conclude that 43.56% of the variation in y can be explained by the explanatory variable

And then 100-43.56 = 56.44 % of the variation in y that cannot be explained by the explanatory variable

8 0
3 years ago
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