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garik1379 [7]
3 years ago
15

Which of these strategies would eliminate a variable in the system of equations?

Mathematics
1 answer:
ahrayia [7]3 years ago
5 0

Graphing or elimination

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6a What is the Answer?
zavuch27 [327]

We have been provided a diagram which tells us that Patti drew vertical line segments from two points to the line in her scatter plot. The first point she selected was dwarf crocodile. The second point she selected was for an Indian Gharial crocodile.

We can see that dwarf crocodile's bite force is closer to line of best fit than Indian Gharial crocodile. Indian Gharial crocodile seems to be an outlier for our data set.

Therefore, Patti's line have resulted in a predicted bite force that was closer to actual bite force for the dwarf crocodile.

6 0
3 years ago
Test the claim that the proportion of men who own cats is smaller than 70% at the 0.05 significance level. The null and alternat
Ghella [55]

Answer:

the null hypothesis would be: p = 70%/0.7

The alternative hypothesis would be: p < 0.7

Step-by-step explanation:

The null hypothesis is most of the time always the default statement while the alternative hypothesis is tested against the null and is its opposite.

In this case study the null hypothesis would be: the proportion of men who own cats is 70%: p = 0.7

The alternative hypothesis would be: the proportion of men who own cats is smaller than 70% : p < 0.7

3 0
3 years ago
A consumer organization inspecting new cars found that many had appearance defects (dents, scratches, paint chips, etc.). While
Murljashka [212]

Answer:

The expected number of appearance defects in a new car  = 0.64

standard deviation = 0.93(approximately)

Step-by-step explanation:

Given -

7% had exactly three, 11% exactly two, and 21% only one defect in cars.

Let X be no of defects in a car

P(X=3) = .07 , P(X=2) = .11 , P(X=3) = .21

P(X=0 ) = 1 - .07 - .11 - .21 = 0.61

The expected number of appearance defects in a new car =

E(X) = \nu = = \sum X P(X) =3\times 0.07 + 2\times0.11 + 3\times0.21 + 0\times0.61 = 0.64

\sigma^{2}  = variation of E(X) = \sum (X - \nu) ^{2}P(X) = (3 - 0.64) ^{2}\times0.07 + (2 - 0.64) ^{2}\times0.11 + (1 - 0.64) ^{2}\times0.21 + (0 - 0.64) ^{2}\times0.61

 = (2.36) ^{2}\times0.07 + (1.36) ^{2}\times0.11 + (.36) ^{2}\times0.21 + ( 0.64) ^{2}\times0.61 = 0.8704

standard deviation  =  \sqrt{\sigma^{2}} = \sqrt{0.8704^{2}} = 0.93(approximately)

4 0
3 years ago
I NEED HELP DONT COMMENT IF YOU'RE DONT KNOW
stepan [7]
<span>12.6≤<span>g+17.4</span></span>  Flip the equation.<span><span>  g+17.4</span>≥12.6</span>  Subtract 17.4 from both sides.<span><span><span>  g+17.4</span>−17.4</span>≥<span>12.6−17.4</span></span><span>  g≥<span>−4.8</span></span>   Answer:  <span>g≥<span>−<span>4.8</span></span></span>
6 0
3 years ago
$32.98 with 25% off (SHOW WORK)
lisabon 2012 [21]

Answer:

$24.74

Step-by-step explanation:

32.98*0.75=24.735

7 0
3 years ago
Read 2 more answers
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