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pishuonlain [190]
3 years ago
10

Damian wrote the number eight and sixty-five thousandths as 8.65. Complete the description of his error and correct it. Damian d

id not include as a place holder in the place. He should have written .
Mathematics
1 answer:
trapecia [35]3 years ago
6 0

Answer:

8.065

Step-by-step explanation:

the zero holds the tenths place, the 6 is in the hundredths place, and the 5 is in the thousandths place.

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A genetic experiment involving peas yielded one sample of offspring consisting of 437437 green peas and 129129 yellow peas. Use
navik [9.2K]

Answer:

The null hypothesis: \mathbf{H_o: p=0.27}

The alternative hypothesis: \mathbf{H_1: p \neq 0.27}

Test statistics : z = −2.30

P-value:  = 0.02144

Decision Rule: Since the p-value is lesser than the level of significance; then we reject the null hypothesis.

Conclusion: We accept the alternative hypothesis and  conclude that under the same​ circumstances the proportion of offspring peas will be yellow is not equal to 0.27

Step-by-step explanation:

From the given information:

Let's state the null and the alternative hypothesis;

Since The claim is that 27%  of the offspring peas will be yellow.

The null hypothesis state that the proportion of offspring peas will be yellow is equal to 0.27.

i.e

\mathbf{H_o: p=0.27}

The alternative hypothesis  state that the proportion of offspring peas will be yellow is not equal to 0.27

\mathbf{H_1: p \neq 0.27}

<u>The test statistics:</u>

we are given 437 green peas and 129 yellow apples;

Hence;

\hat p = \dfrac{x}{n}

where ;

\hat p = sample proportion

x = number of success

n = total number of the sample size

\hat p = \dfrac{129}{437+129}

\hat p = \dfrac{129}{566}

\mathbf{\hat p = 0.2279}

Now; the test statistics can be computed as :

z = \dfrac { \hat p -p }{\sqrt {\dfrac{p(1-p)}{n}  } }

z = \dfrac {0.2279 -0.27 }{\sqrt {\dfrac{0.27(1-0.27)}{566}  } }

z = \dfrac {-0.043 }{\sqrt {\dfrac{0.27(0.73)}{566}  } }

z = \dfrac {-0.043 }{\sqrt {\dfrac{0.1971}{566}  } }

z = \dfrac {-0.043 }{\sqrt {3.48233216*10^{-4} } }

z = \dfrac {-0.043 }{0.01866} }

z = −2.30

C. P-value

P-value = P(Z < z)

P-value = P(Z< -2.30)

By using the ​ P-value method and the normal distribution as an approximation to the binomial distribution.

from the table of standard normal distribution

move left until the first column is reached. Note the value as –2.0

move upward until the top row is reached. Note the value as 0.30

find the probability value as 0.010724 by the intersection of the row and column values gives the area to the left of

z = -2.30

P- value = 2P(z ≤ -2.30)

P-value = 2 × 0.01072

P - value = 0.02144

Decision Rule: Since the p-value is lesser than the level of significance; then we reject the null hypothesis.

Conclusion: We accept the alternative hypothesis and  conclude that under the same​ circumstances the proportion of offspring peas will be yellow is not equal to 0.27

8 0
3 years ago
Which of the following prefixes is the best for measuring small quantities like the thickness of a dime A.milli B.kilo C.deci D.
never [62]
Milli is the best to measure the thickness of a dime. A is your answer.
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Which of the following terminating decimals is equivalent to -1 3/4<br> ?
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It would be - 1.75. Hope it helps! :)
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I promise this app called brainily is a life saver for algebra problems like this !! It’s not a scam trust me
8 0
3 years ago
A college job placement office collected data about students’ GPAs and the salaries they earned in their first jobs after gradua
frez [133]

Answer:

X is the GPA

Y is the Salary

Standard deviation of X is 0.4

Standard deviation of Y is 8500

E(X)=2.9

E(Y)=47200

We are given that The correlation between the two variables was r = 0.72

a)y = a+bx

b = \frac{\sum(x_i-\bar{x})(y_i-\bar{y})}{\sum(x_i-\bar{x})^2} = \frac{r \times \sqrt{var(X) \times Var(Y)}}{Var(X)} =  \frac{0.72 \times \sqrt{0.4^2 \times 8500^2}}{0.4^2} = 15300

a=y-bx = 47200-(15300 \times 29) = 2830

So, slope =  15300

Intercept =  2830

So, equation : y = 2830+15300x

b) Your brother just graduated from that college with a GPA of 3.30. He tells you that based on this model the residual for his pay is -$1880. What salary is he earning?

y = 2830+15300 \times 3.3 = 53320

Observed salary = Residual + predicted = -1860+53320 = 51440

c)) What proportion of the variation in salaries is explained by variation in GPA?

The proportion of the variation in salaries is explained by variation in GPA = r^2 = (0.72)^2 =0.5184

8 0
3 years ago
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