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Masteriza [31]
2 years ago
11

Sanjeet paid $32.85 for 1 file and 3 identical pens. Leon paid $83.50 for 2 files and 8 identical pens. Find the cost of one suc

h pen
Mathematics
1 answer:
suter [353]2 years ago
3 0

The cost of the file is $6.15 and the cost of the pen is $8.9

<h3>Solving word problems with systems of linear equations.</h3>

The interpretation of the given word problem leads to a system of linear equations.

From the given information:

  • Let the file be denoted with f and the pen be denoted with p

f + 3p = 32.85 --- (1)

2f + 8p = 83.5 --- (2)

From equation (1)

f = - 3p+32.85

Replace the value of f in the above equation into equation (2)

2(-3p + 32.85) + 8p = 83.5

2p + 65.7 = 83.5

2p = 83.5 -65.7

2p = 17.8

p = 17.8/2

p = 8.9

Replacing the value of p = 8.9 into f = - 3p+32.85

f = -3(8.9)+32.85

f = 6.15

Therefore, we can conclude that the cost of the file is $6.15 and the cost of the pen is $8.9.

Learn more about solving a system of linear equations here:

brainly.com/question/13729904

#SPJ1

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Solve the equation a=m-n for the variable n
Bogdan [553]

Answer:

m-a = n

Step-by-step explanation:

a=m-n

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a-m = m-n-m

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3 years ago
Is education related to programming preference when watching TV? From a poll of 80 television viewers, the following data have b
Luda [366]

Answer:

a) H0:  There is no association between level of education and TV station preference (Independence)

H1: There is association between level of education and TV station preference (No independence)

b) \chi^2 = \frac{(15-10)^2}{10}+\frac{(15-20)^2}{20}+\frac{(10-10)^2}{10}+\frac{(5-10)^2}{10}+\frac{(25-10)^2}{10}+\frac{(10-20)^2}{20} =33.75

c) \chi^2_{crit}=5.991

d) Since the p value is lower than the significance level we enough evidence to reject the null hypothesis at 5% of significance, and we can conclude that we have dependence between the two variables analyzed.

Step-by-step explanation:

A chi-square goodness of fit test "determines if a sample data matches a population".

A chi-square test for independence "compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another".

Assume the following dataset:

                                  High school   Some College   Bachelor or higher  Total

Public Broadcasting       15                       15                          10                     40

Commercial stations      5                         25                         10                     40  

Total                                20                      40                          20                    80

We need to conduct a chi square test in order to check the following hypothesis:

Part a

H0:  There is no association between level of education and TV station preference (Independence)

H1: There is association between level of education and TV station preference (No independence)

The level os significance assumed for this case is \alpha=0.05

The statistic to check the hypothesis is given by:

\sum_{i=1}^n \frac{(O_i -E_i)^2}{E_i}

Part b

The table given represent the observed values, we just need to calculate the expected values with the following formula E_i = \frac{total col * total row}{grand total}

And the calculations are given by:

E_{1} =\frac{20*40}{80}=10

E_{2} =\frac{40*40}{80}=20

E_{3} =\frac{20*40}{80}=10

E_{4} =\frac{20*40}{80}=10

E_{5} =\frac{40*40}{80}=20

E_{6} =\frac{20*40}{80}=10

And the expected values are given by:

                                  High school   Some College   Bachelor or higher  Total

Public Broadcasting       10                       20                         10                     40

Commercial stations      10                        10                         20                     40  

Total                                20                      30                          30                    80

Part b

And now we can calculate the statistic:

\chi^2 = \frac{(15-10)^2}{10}+\frac{(15-20)^2}{20}+\frac{(10-10)^2}{10}+\frac{(5-10)^2}{10}+\frac{(25-10)^2}{10}+\frac{(10-20)^2}{20} =33.75

Now we can calculate the degrees of freedom for the statistic given by:

df=(rows-1)(cols-1)=(2-1)(3-1)=2

Part c

In order to find the critical value we need to look on the right tail of the chi square distribution with 2 degrees of freedom a value that accumulates 0.05 of the area. And this value is \chi^2_{crit}=5.991

Part d

And we can calculate the p value given by:

p_v = P(\chi^2_{3} >33.75)=2.23x10^{-7}

And we can find the p value using the following excel code:

"=1-CHISQ.DIST(33.75,2,TRUE)"

Since the p value is lower than the significance level we enough evidence to reject the null hypothesis at 5% of significance, and we can conclude that we have dependence between the two variables analyzed.

7 0
3 years ago
What percent is 93 out of 930?
joja [24]

Answer:

1/10

Step-by-step explanation:

93÷93 930÷93

=1/10

6 0
3 years ago
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