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sergejj [24]
2 years ago
6

-1. The table shows the annual consumption of cheese per person in the United States for selected years in the 20th century. Let

x = number of years since 1900, and y = pounds per person.
Year Pounds Consumed
1912 4.976
1932 8.717
1969 16.997
1979 21.705

What cubic model best fits this data?

-2. The table shows the annual consumption of cheese per person in the U.S. for selected years in the 20th century.

Year Pounds Consumed
1913 4.468
1926 5.56
1955 4.778
1990 10.905

Use a cubic model to estimate milk production in 1989.
a. 20.9
b. 10.5
c. 14.5
d. 6.5

-3. Use synthetic division to find P(-1) for P(x)=x^4+x^3+4x^2-10x+4
a. -1
b. -16
c. 18
d. 8
Mathematics
1 answer:
olga nikolaevna [1]2 years ago
5 0
<span>Using processing software (Excel) or even a decent scientific calculator. You input the values and generate the best fit cubic equation.
For number 1, the equation is
y = 8x10</span>⁻⁵ x³ - 0.0097 x² + 0.374 x + 1.083
where x is the number of years since 1900
y is the pounds cheese consumed

For number 2, the equation is
y = -3x10⁻⁵ x³ + 0.0028 x² + 0.2155 x + 1.7736

For number 3
P(-1) = 18
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Answer:

We need to conduct a hypothesis in order to test the claim that the true proportion of employess are late to work is 0.16, so we need to apply a one sample proportion test:  

Null hypothesis:p=0.16  

Alternative hypothesis:p \neq 0.16  

z=\frac{0.20 -0.16}{\sqrt{\frac{0.16(1-0.16)}{25}}}=0.546  

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Step-by-step explanation:

Data given and notation

n=25 represent the random sample taken

\hat p=0.2 estimated proportion  

p_o=0.16 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)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the true proportion of employess are late to work is 0.16, so we need to apply a one sample proportion test:  

Null hypothesis:p=0.16  

Alternative hypothesis:p \neq 0.16  

When we conduct a proportion test we need to use the z statistic, 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.

Calculate the statistic  

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

z=\frac{0.20 -0.16}{\sqrt{\frac{0.16(1-0.16)}{25}}}=0.546  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about 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 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>0.546)=0.585  

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