---### Regression Analysis: Predicting Subway Fare Based on Pizza Cost#### Objective:Determine the regression equation using the pizza cost and the subway fare from the table below. Here, the pizza cost is the predictor (x) variable. Both pizza cost (measured in dollars per slice) and subway fare (measured in dollars) are given. We aim to predict the subway fare when the pizza cost is $4.01 per slice.#### Data Table:| Year | Pizza Cost | Subway Fare | CPI ||------|------------|-------------|-------|| 1960 | 0.152 | 0.148 | 29.6 || 1973 | 0.354 | 0.352 | 44.4 || 1986 | 0.996 | 0.999 | 109.6 || 1995 | 1.246 | 1.350 | 152.4 || 2002 | 1.754 | 1.502 | 180.0 || 2009 | 1.999 | 1.998 | 184.0 || 2013 | 2.247 | 2.247 | 214.5 || 2015 | 2.299 | 2.547 | 233.0 || 2019 | 3.003 | 2.748 | 252.2 |#### Instructions:1. **Find the regression equation**: Use the given data to calculate the regression equation, where `y` represents the subway fare, and `x` represents the pizza cost.2. **Equation format**: The regression equation will be in the form: \[ \hat{y} = \beta_0 + (\beta_1)(x) \] - Round the y-intercept ($\beta_0$) to four decimal places. - Round the slope ($\beta_1$) to three decimal places.3. **Prediction**: Use the regression equation to predict the subway fare when the pizza cost is $4.01 per slice.#### Solution Setup:- **Regression Equation Calculation Placeholder**: \[ \hat{y} = \square + (\square) x \]#### Example: If after calculations the regression

The provided information is Pizza cost (x) Subway Fare (y) xy x2 0.152 0.148 0.022496 0.023104…

Answered: Use the pizza cost and the subway fare…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
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A simple regression model for 10 pair of data resulted in a standard error of 3.95 (i.e., Se = 3.95), and the. The sum of squares of error (SSE) is ______. a. 187.23 b. 171.63 c. 156.03 d. 140.42 e. 124.82
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.98 per slice? Year Pizza Cost Subway Fare CPI 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 0.152 0.353 1.000 1.251 1.753 2.003 2.254 2.300 2.747 2.997 0.151 0.346 1.000 1.347 1.497 2.004 2.253 2.551 2.747 2.750 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 The regression equation is y=+x. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) The best predicted subway fare when pizza costs $3.98 per slice is $ (Round to the nearest cent as needed.)
Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.3 mm. How does the result compare to the actual height of 1776 mm? Foot Length 281.9 278.3 253.2 258.7 278.7 257.8 274.2 262.2 Height 1784.8 1771.0 1675.6 1645.9 1858.7 1710.1 1789.2 1737.4 the regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) The best predicted height of a male with a foot length of 273.3 mm is enter your response here mm. (Round to the nearest integer as needed.)

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