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Vesna [10]
3 years ago
12

Troy has a price chart below for various ingredients he needs to order for his sandwich bar. Sandwich Ingredients Item Cost (per

pound) Onions $0.79 Tomatoes $0.93 Cheese $1.85 Ham $3.15 Turkey $3.40 Troy has to order 8 pounds of ham, 15 pounds of cheese, and 12 pounds of turkey. What is the total cost of Troy's order? $93.75 $110.25 $204.23 $293.66
Mathematics
1 answer:
shepuryov [24]3 years ago
4 0

Answer:

$93.75

Step-by-step explanation:

The computation of the total cost of order is shown below:

The Cost of 8 pounds of Pepperoni is

=  8 × $3.15

= 25.2

The Cost of 15 pounds of cheese is

= 15 × $1.85

= $27.75

The Cost of 12 pounds of sausage is

= 12 × $3.40

= $40.8

So, The total cost is

= $25.2 + 27.75 + $40.80

= $93.75

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Answer:

z= -0.968

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Step-by-step explanation:

1) Data given and notation n  

n=106 represent the random sample taken

X=48 represent the people who says that  they would watch one of the television shows.

\hat p=\frac{48}{106}=0.453 estimated proportion of people who says that  they would watch one of the television shows.

p_o=0.5 is the value that we want to test

\alpha represent the significance level  

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that 50% of people who says that  they would watch one of the television shows.:  

Null hypothesis:p=0.5  

Alternative hypothesis:p \neq 0.5  

When we conduct a proportion test we need to use the z statisitc, and the is given by:  

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

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

3) Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.453 -0.5}{\sqrt{\frac{0.5(1-0.5)}{106}}}=-0.968  

4) Statistical decision  

P value method or p value approach . "This method consists on determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level is not provided, but we can assume \alpha=0.05. The next step would be calculate the p value for this test.  

Since is a bilateral test the p value would be:  

p_v =2*P(z  

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