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stepan [7]
2 years ago
9

9. a. Maurice says that 1079 ÷ 62 is 16 with a remainder of 87. a. Without seeing his work, how can you tell Maurice divided inc

orrectly? *
9. b. Maurice is correct about this fact: 16 × 62 + 87 = 1079. Explain how you can use that fact to find the correct quotient and remainder for 1079 ÷ 62 without actually dividing. Then find the quotient. *
Mathematics
1 answer:
mamaluj [8]2 years ago
8 0

Answer:

a.  We can tell that Maurice divided incorrectly because if the dividend is 62, you can't have a remainder of 87, because 62 goes into 87 once, so the answer would be 17 with a remainder of 25.  B. YOu can use that fact to find the correct quotient, because 87/62 is 1, with a remainder of 25, so 16+1=17, so the answer is 17 with a remainder of 25.   Please vote the brainliest.

Step-by-step explanation:

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Answer:1/12

Step-by-step explanation: if the loop 11/12 of a mile and she rode for 1/2 of a mile then 1/3 , subtract what she rode from 11/12 then you get 1/12

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4. The reference angle for 190 is<br> A. 10°<br> B. 180°<br> C. -10°<br> D. 90°
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Answer: A

Step-by-step explanation:  A reference angle is smallest possible angles that  terminal side makes with the x- axis. Since 190 degrees is located i the 3rd quadrant we use the formula 190-180 to find the possible answer and in this case it is A, 10.

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2 years ago
Poor Milhouse is hopelessly in love with Lisa. Unfortunately for Milhouse, Lisa does not feel the same way. However, Milhouse re
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Answer:

15.6%

Step-by-step explanation:

Since each day there is a 6% chance that Lisa smiles at him then that means that each day there is a 94% chance that Lisa does not smile at him. To find the probability of Milhouse going longer than a month (30 days) without a smile from Lisa we need to multiply this percentage in decimal form for every day of the month. This can be solved easily by putting 94% to the 30th power which would be the same, but first, we need to turn it into a decimal...

94% / 100 = 0.94

0.94^{30} = 0.156

Now we can turn this decimal into a percentage by multiplying by 100

0.156 * 100 = 15.6%

Finally, we can see that the probability that Milhouse goes longer than a month without a smile from Lisa is 15.6%

6 0
3 years ago
During the 2000 season, the home team won 138 out of 240 regular season National Football League games. (15 points) a) Construct
jeka94

Answer:

Step-by-step explanation:

A) Confidence interval is written as

Sample proportion ± margin of error

Margin of error = z × √pq/n

Where

z represents the z score corresponding to the confidence level

p = sample proportion. It also means probability of success

q = probability of failure

q = 1 - p

p = x/n

Where

n represents the number of samples

x represents the number of success

From the information given,

n = 240

x = 138

p = 138/240 = 0.58

q = 1 - 0.58 = 0.42

To determine the z score, we subtract the confidence level from 100% to get α

α = 1 - 0.95 = 0.05

α/2 = 0.05/2 = 0.025

This is the area in each tail. Since we want the area in the middle, it becomes

1 - 0.025 = 0.975

The z score corresponding to the area on the z table is 1.96. Thus, the z score for a confidence level of 95% is 1.96

Therefore, the 95% confidence interval is

0.58 ± 1.96√(0.58)(0.42)/240

Confidence interval is

0.58 ± 0.062

B) winning more than halve of the games would be winning 120 games and above.

p = 120/240 = 0.5

We would set up the hypothesis test.

For the null hypothesis,

P ≥ 0.5

For the alternative hypothesis,

P < 0.5

Considering the population proportion, probability of success, p = 0.5

q = probability of failure = 1 - p

q = 1 - 0.5 = 0.5

Considering the sample,

Sample proportion, P = x/n

Where

x = number of success = 138

n = number of samples = 240

P = 138/240 = 0.58

We would determine the test statistic which is the z score

z = (P - p)/√pq/n

z = (0.58 - 0.5)/√(0.5 × 0.5)/240 = 2.48

Recall that this is a left tailed test. We would determine the probability value of the area to the right of the z score from the normal distribution table.

P value = 1 - 0.9934 = 0.0066

Since alpha, 0.01 > the p value, 0.0066, then we would reject the null hypothesis.

Therefore, At the 0.01 significance level, there is no strong evidence of a home field advantage (they win more than half of the games) in professional football.

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