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3 years ago

Use long division to find the quotient and remainder when 2x^3 + 6x^2 - x + 5 divided by 2x^2 - 1.

Mathematics

2 answers:

andrew11 [14]3 years ago

4 0

Answer:

Qoutient=x+3

Remainder=8

STatiana [176]3 years ago

3 0

Answer:

Quotient ---> x + 3

Reminder ---> 8

Step-by-step explanation:

See the attached image, I have included all the necessary steps!

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If log2 5 = k, determine an expression for log32 5 in terms of k.

lukranit [14]

Answer:

$log_3_2(5)=\frac{1}{5} k$

Step-by-step explanation:

Let's start by using change of base property:

$log_b(x)=\frac{log_a(x)}{log_a(b)}$

So, for $log_2(5)$

$log_2(5)=k=\frac{log(5)}{log(2)}\hspace{10}(1)$

Now, using change of base for $log_3_2(5)$

$log_3_2(5)=\frac{log(5)}{log(32)}$

You can express $32$ as:

$2^5$

Using reduction of power property:

$log_z(x^y)=ylog_z(x)$

$log(32)=log(2^5)=5log(2)$

Therefore:

$log_3_2(5)=\frac{log(5)}{5*log(2)}=\frac{1}{5} \frac{log(5)}{log(2)}\hspace{10}(2)$

As you can see the only difference between (1) and (2) is the coefficient $\frac{1}{5}$ :

So:

$\frac{log(5)}{log(2)} =k\\$

$log_3_2(5)=\frac{1}{5} \frac{log(5)}{log(2)} =\frac{1}{5} k$

6 0

3 years ago

What do you notice about the ratios of the lengths for each transversal? How do they compare?

lesya [120]

Answer:

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4 0

3 years ago

Read 2 more answers

Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construc

Anarel [89]

Answer and Step-by-step explanation: Scaterplot is a type of graphic which shows the relationship between to variables. In this question, you want to determine if there is a linear relationship between overhead widths of seals and the weights. So, the hypothesis are:

H₀: no linear correlation;

H₁: there is linear correlation;

In this hypothesis test, to reject H₀, the correlation coefficient r of the data set has to be bigger than the critical value from the table.

With α = 0.05 and n = 6, the critical value is 0.811.

The linear correlation is calculated as:

r = n∑xy - ∑x.∑y / √[n∑x² - (∑x)²] [n∑y² - (∑y)²]

r = $\frac{6.9632 - 51.1108}{\sqrt{6.439 - (51^{2} )}.6.14482 - (1108^{2} ) }$

r = 0.9485

Since r is bigger than the critical value, H₀ is rejected, which means there is enough evidence to conclude that there is linear correlation between overhead widths and the weights.

In the attachments is the scaterplot of the measurements, also showing the relationship.