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AlladinOne [14]
3 years ago
5

I need help with how to find 2 equations for thy problem

Mathematics
1 answer:
Mrrafil [7]3 years ago
4 0
To know how to find the answer you these two equations you figure out what the line is solid or dash.
Then you find the slope y-int form for the first equation and repeat for the second.
For your equation it would be y > 2x+2 and the second equation would be y> or equal to -1x+0
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Jamiah bought two 125 ounce bags of flour for baking. He used up 32 ounces of flour to bake a batch of brownies. How much flour
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Answer: its 218

Step-by-step explanation: you just have to subtract 250 minus 32

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2 years ago
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A researcher compares the effectiveness of two different instructional methods for teaching electronics. A sample of 138 student
yan [13]

Answer:

The 98% confidence interval for the true difference between testing averages for students using Method 1 and students using Method 2 is (-8.04, 0.84).

Step-by-step explanation:

The (1 - <em>α</em>)% confidence interval for the difference between population means is:

CI=(\bar x_{1}-\bar x_{2})\pm z_{\alpha/2}\times \sqrt{\frac{\sigma^{2}_{1}}{n_{1}}+\frac{\sigma^{2}_{2}}{n_{2}}}

The information provided is as follows:

n_{1}= 138\\n_{2}=156\\\bar x_{1}=61\\\bar x_{2}=64.6\\\sigma_{1}=18.53\\\sigma_{2}=13.43

The critical value of <em>z</em> for 98% confidence level is,

z_{\alpha/2}=z_{0.02/2}=2.326

Compute the 98% confidence interval for the true difference between testing averages for students using Method 1 and students using Method 2 as follows:

CI=(\bar x_{1}-\bar x_{2})\pm z_{\alpha/2}\times \sqrt{\frac{\sigma^{2}_{1}}{n_{1}}+\frac{\sigma^{2}_{2}}{n_{2}}}

     =(61-64.6)\pm 2.326\times\sqrt{\frac{(18.53)^{2}}{138}+\frac{(13.43)^{2}}{156}}\\\\=-3.6\pm 4.4404\\\\=(-8.0404, 0.8404)\\\\\approx (-8.04, 0.84)

Thus, the 98% confidence interval for the true difference between testing averages for students using Method 1 and students using Method 2 is (-8.04, 0.84).

5 0
3 years ago
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lapo4ka [179]

Answer:

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3 years ago
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What is the value of x to the nearest tenth
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