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wolverine [178]
3 years ago
12

Use algebraic methods to prove that the given function has an x-intercept that is equal to its y-intercept. In your final answer

, include all of your calculations.
y = x/x^2 - 1
Mathematics
2 answers:
Llana [10]3 years ago
5 0

Given the function, y = x/( x^2 – 1)

Add x and subtract x from (x^2 – 1) to make it a complete square

y = x/(x^2 + x – x – 1)

 y = x/[x(x + 1) – 1(x + 1)]

y = x/[(x – 1)(x + 1)]

 

 

In order to find the y -intercept, we set x = 0

When x = 0

y = 0/[(0 – 1)(0 + 1)]

y = 0.

Therefore, the y-intercept is zero.

 

In order to find the x -intercept, we set y = 0

When y = 0

0 = x/[(x – 1)(x + 1)]

The only way the product of a division will be zero is if the numerator is zero

So, if x/[(x – 1)(x + 1)] = 0

x = 0

Therefore, the x-intercept is also zero.

 

Since both x- intercept and y- intercept equal zero,

Then, the given function has an x-intercept that is equal to its y-intercept

scoundrel [369]3 years ago
4 0
We have that y= \frac{x}{x^{2}-1 }, so we can factor the denominator to get:
y= \frac{x}{(x-1)(x+1)}
Now, when x=0 y= \frac{0}{(0-1)(0+1)}, y=0; therefore the y-intercept is zero.
And, when y=0 0= \frac{x}{(x-1)(x+1)} = x=[0[(x-1)(x+1)]], x=0; therefore the x-intercept is also zero.

We can conclude that both the y-intercept and the x-intercept are equal zero.
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A random sample of 850 births included 434 boys. Use a 0.10 significance level to test the claim that 51.5​% of newborn babies a
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Answer:

A

Null hypothesis: H0: p = 0.515

Alternative hypothesis: Ha ≠ 0.515

z = -0.257

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Rule

If;

P-value > significance level --- accept Null hypothesis

P-value < significance level --- reject Null hypothesis

Z score > Z(at 90% confidence interval) ---- reject Null hypothesis

Z score < Z(at 90% confidence interval) ------ accept Null hypothesis

Step-by-step explanation:

The null hypothesis (H0) tries to show that no significant variation exists between variables or that a single variable is no different than its mean. While an alternative Hypothesis (Ha) attempt to prove that a new theory is true rather than the old one. That a variable is significantly different from the mean.

For the case above;

Null hypothesis: H0: p = 0.515

Alternative hypothesis: Ha ≠ 0.515

Given;

n=850 represent the random sample taken

Test statistic z score can be calculated with the formula below;

z = (p^−po)/√{po(1−po)/n}

Where,

z= Test statistics

n = Sample size = 850

po = Null hypothesized value = 0.515

p^ = Observed proportion = 434/850 = 0.5106

Substituting the values we have

z = (0.5106-0.515)/√(0.515(1-0.515)/850)

z = −0.256677

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P value = P(Z<-0.257) = 0.797

Since z at 0.10 significance level is between -1.645 and +1.645 and the z score for the test (z = -0.257) which falls with the region bounded by Z at 0.10 significance level. And also the one-tailed hypothesis P-value is 0.797 which is greater than 0.10. Then we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say that at 10% significance level the null hypothesis is valid.

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