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1 year ago

The lunch bill for Eugene and Maggie totaled $20.20. Tax

Mathematics

1 answer:

LiRa [457]1 year ago

6 0

Correct answer is A. The cost of meal in the caffeteria is 24.39.

<h3>What percentage is it?</h3>

A percentage is a figure or ratio that represents a portion of 100. In addition to the percent symbol "%," the abbreviations "pct," "pct," and occasionally "pc" are also used to denote it. A% does not have any dimensions or a corresponding unit of measurement.

Your $20.20 bill is made up of the full amount (100%) plus the 15% tip, for a total of 115%. Decimal equivalent is 1.15.

Simply divide the entire charge by 1.15 to determine the price before the tip.

20.20/1.15 = 17.56

Consequently, the final amount due before the 15% tip was $17,56.

The total cost after tax and tip = 24.39

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Answer:

y = -0.85 + 0.09x; $49.82

Step-by-step explanation:

1. Calculate Σx, Σy, Σxy, and Σx²

The calculation is tedious but not difficult.

$\begin{array}{rrrr}\mathbf{x} & \mathbf{y} & \mathbf{xy} & \mathbf{x^{2}}\\526 & 52.08 & 27394.08 & 276676\\625& 59.00 & 36875.00 &390625\\589 & 56.12 & 33054.68 & 346921\\409 & 25.72 & 10519.48 & 167281\\489 & 34.12& 16684.68 & 293121\\500 & 53.00 & 26500.00 &250000\\906 & 76.48 & 71102.88 & 820836\\251 &26.08 & 6546.08 & 63001\\595 & 50.60 & 30107.00 & 354025\\719 & 68.52 & 49265.88 & 516961\\\mathbf{5609} & \mathbf{503.72} &\mathbf{308049.76} & \mathbf{3425447}\\\end{array}$

2. Calculate the coefficients in the regression equation

$a = \dfrac{\sum y \sum x^{2} - \sum x \sum xy}{n\sum x^{2}- \left (\sum x\right )^{2}} = \dfrac{503.7 \times 3425447 - 5609 \times 308049.76}{10 \times 3425447- 5609^{2}}\\\\= \dfrac{1725466163 - 1727851103.84}{34254470 - 31460881} = -\dfrac{2384941}{2793589}= \mathbf{-0.8537}$

$b = \dfrac{n\sumx y - \sum x \sumxy}{n\sum x^{2}- \left (\sum x\right )^{2}} = \dfrac{3080498 - 2825365.48}{2793589} = \dfrac{255132}{2793589} = \mathbf{0.09133}$

To two decimal places, the regression equation is

y = -0.85 + 0.09x

3. Prediction

If x = 563,

y = -0.85 + 0.09x = -0.85 + 0.09 × 563 = -0.85 + 50.67 = $49.82

(If we don't round the regression equation to two decimal places, the predicted value is $50.56.)

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