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Define x:
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Let the tie be x
Tie = x
Shirt = x - 4.02
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Construct equation :
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The sum of the shirt and tie is $75.62
x + x -4.02 = 75.62
2x - 4.02 = 75.62
2x = 79.64
x = $39.82
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Find the cost of tie and shirt :
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Tie = x = $39.82
Shirt = x - $4.02 = $39.82 - $4.02 = $35.80
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Answer: The price of the short is $35.80
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Answer:
The conditional statement "∀x, If x is an insect, then x has six legs" is derived from the statement "All insects have six legs" using "a. existential" generalization
Step-by-step explanation:
In predicate logic, existential generalization is a valid rule of inference that allows one to move from a specific statement, or one instance, to a quantified generalized statement, or existential proposition. In first-order logic, it is often used as a rule for the existential quantifier in formal proofs.
Answer:
36
Step-by-step explanation:
36 is greater than 3.6
Answer:
6xy - 8x + 5y - 4z
Step-by-step explanation:
6xy - 20y + 7z - 8x + 25y - 11z
Group the ones with the variable first to make an equation:
6xy - 8x - 20y + 25y + 7z - 11z
Solve the equation
6xy - 8x +5y - 4z
Answer:
The correlation coeffcient for this case was provided:
r =0.934
And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .
We can also find the 
who represent the determination coefficient and we got:
And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables
Step-by-step explanation:
Previous concepts
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
And in order to calculate the correlation coefficient we can use this formula:
![r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}](https://tex.z-dn.net/?f=r%3D%5Cfrac%7Bn%28%5Csum%20xy%29-%28%5Csum%20x%29%28%5Csum%20y%29%7D%7B%5Csqrt%7B%5Bn%5Csum%20x%5E2%20-%28%5Csum%20x%29%5E2%5D%5Bn%5Csum%20y%5E2%20-%28%5Csum%20y%29%5E2%5D%7D%7D)
The correlation coeffcient for this case was provided:
r =0.934
And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .
We can also find the who represent the determination coefficient and we got:
And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables
