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kicyunya [14]
3 years ago
10

My last function question. Please break this down for me. Brainliest answer will be given

Mathematics
1 answer:
cupoosta [38]3 years ago
7 0
Remember these two combinations: logab=loga+logb, log(a/b)=loga-logb
3logx=logx^3
(1/2)log(x+2)=log(x+2)^(1/2)
2log(z-4)=log(z-4)^2
so the given expression can be combined into log{[(x^3)(z-4)^2]/(x+2)^(1/2)}
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A number cube is rolled two times. What is the probability that the sum of two numbers will be 9?
harina [27]
Total number of possible outcomes = 36
Total number of outcomes with sum 9 = 4
{3, 6} (4, 5) {5, 4} (6, 3}

P(Sum = 9) = 4/36 = 1/9

Answer: 1/9
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X-3=4 with work to provide
TEA [102]

Answer:

7

Step-by-step explanation:

x-3=4

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x=7

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1. Vertical
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4. 72
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weqwewe [10]

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An automobile dealer wants to see if there is a relationship between monthly sales and the interest rate. A random sample of 4 m
SVETLANKA909090 [29]

Answer:

a) y=-6.254 x +75.064  

b) r =-0.932

The % of variation is given by the determination coefficient given by r^2 and on this case -0.932^2 =0.8687, so then the % of variation explained by the linear model is 86.87%.

Step-by-step explanation:

Assuming the following dataset:

Monthly Sales (Y)     Interest Rate (X)

       22                               9.2

       20                               7.6

       10                                10.4

       45                                5.3

Part a

And we want a linear model on this way y=mx+b, where m represent the slope and b the intercept. In order to find the slope we have this 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}  

With these we can find the sums:  

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=278.65-\frac{32.5^2}{4}=14.5875  

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i){n}}=696.9-\frac{32.5*97}{4}=-91.225  

And the slope would be:  

m=\frac{-91.225}{14.5875}=-6.254  

Nowe we can find the means for x and y like this:  

\bar x= \frac{\sum x_i}{n}=\frac{32.5}{4}=8.125  

\bar y= \frac{\sum y_i}{n}=\frac{97}{4}=24.25  

And we can find the intercept using this:  

b=\bar y -m \bar x=24.25-(-6.254*8.125)=75.064  

So the line would be given by:  

y=-6.254 x +75.064  

Part b

For this case we need to calculate the correlation coefficient given by:

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

r=\frac{4(696.9)-(32.5)(97)}{\sqrt{[4(278.65) -(32.5)^2][4(3009) -(97)^2]}}=-0.937  

So then the correlation coefficient would be r =-0.932

The % of variation is given by the determination coefficient given by r^2 and on this case -0.932^2 =0.8687, so then the % of variation explained by the linear model is 86.87%.

6 0
3 years ago
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