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Andreyy89
3 years ago
15

Which of the following is a true statement?

Mathematics
1 answer:
Nikolay [14]3 years ago
3 0

Answer:

The last choice: 68/5 - 22/5 = 9 1/5

Step-by-step explanation:

Solve each problem:

9 3/7 = 10 3/7

The fractions are the same so look at the whole numbers.

Does 9 equal 10? No, it doesn't so this is a false statement.

332/4 = 1/83

Simplify 332/4:

332/4 = 83/1

83 does not equal 1/83 so this is a false statement.

37/5 = 5 2/5

Convert the improper fraction into a mixed number:

7 2/5 = 5 2/5

These numbers do not equal each other so this is a false.

68/5 - 22/5 = 9 1/5

Subtract the numerators on the left side of the equation:

46/5 = 9 1/5

Convert the improper fraction into a mixed number:

9 1/5 = 9 1/5

These numbers equal each other so this is a true statement!

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Answer:

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Step-by-step explanation:


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3 years ago
Amy wants to estimate 11% of $9.11. what is a good estimate of the answer
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In a simple regression analysis for a given data set, if the null hypothesis β = 0 is rejected, then the null hypothesis ρ = 0 i
kati45 [8]

Answer:

Null hypothesis: \rho =0

Alternative hypothesis: \rho \neq 0

The statistic to check the hypothesis is given by:

t=\frac{r \sqrt{n-2}}{\sqrt{1-r^2}}

And is distributed with n-2 degrees of freedom

And the statistic to check the significance of a coeffcient in a regression is given by:

t_1 = \frac{\hat{\beta_1} -0}{S.E (\hat{\beta_1})}

For this case is importantto remember that t1 and p value for test of slope coefficient is the same test statistic and p value for the correlation test so then the answer would be:

Always

Step-by-step explanation:

In order to test the hypothesis if the correlation coefficient it's significant we have the following hypothesis:

Null hypothesis: \rho =0

Alternative hypothesis: \rho \neq 0

The statistic to check the hypothesis is given by:

t=\frac{r \sqrt{n-2}}{\sqrt{1-r^2}}

And is distributed with n-2 degrees of freedom

And the statistic to check the significance of a coeffcient in a regression is given by:

t_1 = \frac{\hat{\beta_1} -0}{S.E (\hat{\beta_1})}

For this case is importantto remember that t1 and p value for test of slope coefficient is the same test statistic and p value for the correlation test so then the answer would be:

Always

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attached is a file/ picture i made in google images of a graph of it, i explain the steps as well.
id appreciate a brainliest since the drawing took a good 15 minutes but its up to you! Hope i helped.</span></span>

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