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____ [38]
1 year ago
7

Stephanie put $80 in her bank account when she was five years old. The bank gave her a simple interest rate of 2.1%.

Mathematics
1 answer:
Brut [27]1 year ago
4 0

Answer:

2000

Step-by-step explanation:

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Olaf needs a total of 3 cups of sugar to make 4 cakes. Write and solve an equation to find the number of cups of sugar he needs
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3/4 cup

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Jorge is making 6 large salads and 4 small salads how many cherry tomatoes does he need?
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Answer:10

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(-45-24v^2+v^4-22v-6v^3)/(v-9)
Yuliya22 [10]

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If my 15 year old brain has functioned correctly, the answer is v^3+3v^2+3v+5

Step-by-step explanation:

7 0
1 year ago
Linda commutes a total of 54 miles to and from work every day. She needs a new car, and good gas mileage is important to her. Sh
Alchen [17]
The answer is 1 gallon.

Miles per gallon(mpg) is computed by dividing the distance traveled by the how many gallons used. So you can derive a formula for how many gallons you would use given the mpg. You will end up with:

gallon =  \frac{miles travelled}{miles per gallon}

The problem asks for how many gallons of gas she will safe in a five-day work work week. So first you need to compute how many miles that would be. 

54 miles/day x 5days =  270 miles

So in a five day work week, she will travel 270 miles.

Now to see how much gas she will save, compute how many gallons she will use up for each car, given the mpg of each and find the difference. 

First model:30 mpg

gallons = \frac{270miles}{30mpg}
gallons = 9g
 
This means that with the first model, she will have used up 9 gallons in a 5-day work week.

Second model: 27 mpg
g = \frac{270mi}{27mi/g}
g = 10g

This means that with the second model, she will have used up 10g in a 5-day work week. 

Now for the last bit. How much will she save? You can get that by getting the difference of how many gallons each car would have used up.

10gallons - 9gallons = 1g

So she would have saved 1 gallon of gas if she buys the first car instead of the second. 
 
8 0
1 year ago
Read 2 more answers
In the book Essentials of Marketing Research, William R. Dillon, Thomas J. Madden, and Neil H. Firtle discuss a research proposa
MakcuM [25]

Answer:

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

z=\frac{0.179-0.15}{\sqrt{0.17(1-0.17)(\frac{1}{140}+\frac{1}{60})}}=0.500  

p_v =2*P(Z>0.500)=0.617  

So the p value is a very low value and using any significance level for example \alpha=0.05, 0,1,0.15 always p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions NOT differs significantly.  

Step-by-step explanation:

Data given and notation  

X_{1}=25 represent the number of homeowners who would buy the security system

X_{2}=9 represent the number of renters who would buy the security system

n_{1}=140 sample 1

n_{2}=60 sample 2

p_{1}=\frac{25}{140}=0.179 represent the proportion of homeowners who would buy the security system

p_{2}=\frac{9}{60}= 0.15 represent the proportion of renters who would buy the security system

z would represent the statistic (variable of interest)  

p_v represent the value for the test (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the two proportions differs , the system of hypothesis would be:  

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

We need to apply a z test to compare proportions, and the statistic is given by:  

z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}   (1)  

Where \hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{25+9}{140+60}=0.17  

Calculate the statistic  

Replacing in formula (1) the values obtained we got this:  

z=\frac{0.179-0.15}{\sqrt{0.17(1-0.17)(\frac{1}{140}+\frac{1}{60})}}=0.500  

Statistical decision

For this case we don't have a significance level provided \alpha, but we can calculate the p value for this test.    

Since is a two sided test the p value would be:  

p_v =2*P(Z>0.500)=0.617  

So the p value is a very low value and using any significance level for example \alpha=0.05, 0,1,0.15 always p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions NOT differs significantly.  

6 0
2 years ago
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