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julsineya [31]
4 years ago
7

for the graph, complete the following (a) write a table of ordered pairs from the graph. (b) write an equation from the table. (

c) state which variable is the independent variable and which is the dependent variable. (1,3) (2,6) (3,9) (4,12) (5,15) (6,18)
Mathematics
1 answer:
Allisa [31]4 years ago
8 0

Answer:

(a) The table of the ordered pairs is given as:

x-values          1            2            3            4            5             6

y-values           3            6            9           12           15            18

(b)

We find the equation from the table using the slope intercept form.

Let y=mx+c

on using the first column i.e x=1 and y=3 we have equation as:

3=m+c-------(1)

on using the second column i.e. x=2 and y=6

we have 6=2m+c---------(2)

on subtracting equation (1) from equation (2) we get:

m=3

and finally on putting value of m in equation (1) we get c=0

Hence, the equation of the line is y=3x.

This equation holds for all the points.

(c)

<em>x is the independent variable</em> and <em>y is the dependent variable </em>since it depends on the value of 'x'. it is thrice the value of x at each point.




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a)

The null hypothesis is H_0: p = 0.91.

The alternate hypothesis is H_1: p < 0.91.

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b)

The p-value for this test is 0.0367. Since this p-value is less than the significance level of \alpha = 0.05, we reject the null hypothesis and accept the alternate hypothesis that that percentage of athletes who graduate is less than for the student population at large.

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Question a:

Perform the appropriate hypothesis test to determine whether this is significant evidence that the percentage of athletes who graduate is less than for the student population at large:

At the null hypothesis, we test if the proportion is the same as the student population, of 91%. Thus:

H_0: p = 0.91

At the alternate hypothesis, we test that the proportion for athletes is less than 91%, that is:

H_1: p < 0.91

The test statistic is:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

In which X is the sample mean, \mu is the value tested at the null hypothesis, \sigma is the standard deviation and n is the size of the sample.

Test if the proportion is less at the 0.05 level:

The critical value is z with a p-value of 0.05, that is, z = -1.645. Thus, the decision rule is: accept the null hypothesis for z > -1.645, reject the null hypothesis for z < -1.645.

0.91 is tested at the null hypothesis:

This means that \mu = 0.91, \sigma = \sqrt{0.91*0.09}

A sports reporter contacted 152 athletes randomly sampled from that same university and time period and found that 132 of them had graduated within 6 years.

This means that n = 152, X = \frac{132}{152} = 0.8684

Value of the test statistic:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

z = \frac{0.8684 - 0.91}{\frac{\sqrt{0.91*0.09}}{\sqrt{152}}}

z = -1.79

Since z = -1.79 < -1.645, we reject the null hypothesis and accept the alternate hypothesis that that percentage of athletes who graduate is less than for the student population at large.

(b) (3 points) Calculate the P-value for this test. Explain how this P-value can be use to test the hypotheses in part (a).

The p-value of the test is the probability of finding a sample proportion of 0.8684 or below. This is the p-value of z = -1.79.

Looking a the z-table, z = -1.79 has a p-value of 0.0367.

The p-value for this test is 0.0367. Since this p-value is less than the significance level of \alpha = 0.05, we reject the null hypothesis and accept the alternate hypothesis that that percentage of athletes who graduate is less than for the student population at large.

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