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kicyunya [14]
3 years ago
5

784,926 rounded by the 4

Mathematics
1 answer:
Gnesinka [82]3 years ago
8 0
785,000
Or
780,000
Either im pretty sure should work.
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A fruit-drinking company tester a new flavor. In a taste test, 34% of the people taking part liked the new flavor. If 51 people
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Answer:

C. 150

Step-by-step explanation:

The number of people who took the test is unknown, so call it x.

34% of x liked the flavor.

51 people liked the flavor.

That means that 34% of x is equal to 51.

34% of x = 51

0.34x = 51

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x = 150

Answer: C. 150

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**URGENT<br>033.012 divided by <br>6.3​
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3 years ago
3x + 9 &gt; -18
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Answer:

The written form would be "Nine more than three times a number is greater than -18.

Step-by-step explanation:

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3x > -27

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3 years ago
Charles and his brother are sharing the cost of a video game. The video game costs $30.70. If Charles saved $20 to buy the game
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3 years ago
Gibbs Baby Food Company wishes to compare the weight gain of infants using its brand versus its competitor’s. A sample of 40 bab
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Answer:

z=\frac{(7.6-8.1)-0}{\sqrt{\frac{2.3^2}{40}+\frac{2.9^2}{55}}}}=-0.936  

The p value can be founded with this formula:

p_v =P(z  

Since the p value is higher than the significance level provided of 0.05 we have enough evidence to FAIL to reject the null hypothesis and we can't conclude that the true mean for the Gibbs brand is significantly lower than the true mean for the competitor

Step-by-step explanation:

Information given

\bar X_{1}=7.6 represent the mean for Gibbs products

\bar X_{2}=8.1 represent the mean for the competitor

\sigma_{1}=2.3 represent the population standard deviation for Gibbs

\sigma_{2}=2.9 represent the sample standard deviation for the competitor

n_{1}=40 sample size for the group Gibbs

n_{2}=55 sample size for the group competitor

\alpha=0.05 Significance level provided

z would represent the statistic

Hypothesis to verify

We want to check if babies using the Gibbs brand gained less weight, the system of hypothesis would be:  

Null hypothesis:\mu_{1}-\mu_{2}=0  

Alternative hypothesis:\mu_{1} - \mu_{2}< 0  

The statistic would be given by:

z=\frac{(\bar X_{1}-\bar X_{2})-\Delta}{\sqrt{\frac{\sigma^2_{1}}{n_{1}}+\frac{\sigma^2_{2}}{n_{2}}}} (1)  

Replacing the info given we got:

z=\frac{(7.6-8.1)-0}{\sqrt{\frac{2.3^2}{40}+\frac{2.9^2}{55}}}}=-0.936  

The p value can be founded with this formula:

p_v =P(z  

Since the p value is higher than the significance level provided of 0.05 we have enough evidence to FAIL to reject the null hypothesis and we can't conclude that the true mean for the Gibbs brand is significantly lower than the true mean for the competitor

5 0
3 years ago
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