**Question 1**The chart below shows the correlation between altitude and pressure.| Altitude (thousand ft) | 0 | 5 | 10 | 15 | 20 | 25 | 30 ||------------------------|----|----|----|----|----|----|----|| Pressure (lb/in.²) | 14.7 | 12.2 | 10.1 | 8.3 | 6.8 | 5.4 | 4.4 |Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 50.*For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac)*---**Explanation of the Data Table:**The table represents the relationship between altitude (measured in thousands of feet) and atmospheric pressure (measured in pounds per square inch). As altitude increases, atmospheric pressure decreases. **Tasks:**- **Scatter Plot**: You'll need to plot these data points on a graph with altitude on the x-axis and pressure on the y-axis. This visual representation can help identify the type of correlation (linear, exponential, etc.) between the variables.- **Regression Equation**: This involves finding a mathematical equation that best fits the plotted data, typically achieved using statistical software or graphing calculators.- **Prediction**: Use the equation derived from the regression analysis to predict the pressure at an altitude of 50,000 feet. This exercise demonstrates the application of regression analysis in interpreting real-world scientific relationships.

Any point on the Cartesian coordinate system can be represented using the ordered pair: x, y. The…

Answered: The chart below shows the correlation…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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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 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
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Cheick is investigating how long his phone's battery lasts (in hours) for various brightness levels (on a scale of 0-100). His data is displayed in the table and graph below. Brightness Level (x) Hours (y) 23 6.7 27 5.9 30 7.3 36 7.2 71 3.8 72 3.6 85 3.1 94 1.9 (a) Use the Corr/Regression to find the equation for the line of best fit. Round your answers to two decimal places. ˆy = 8.74 + -0.07x (b) Interpret the slope in context. Cheick expects the battery life to go down by 0.07 hours for each increase of 1 in the brightness level. Cheick expects the brightness to decrease by 0.07 for every hour that goes by. Cheick expects his phone battery to last 0.07 hours if he keeps the brightness level at 0. Cheick expects his phone battery to last 8.74 hours if he keeps the brightness level at 0. Correct (c) What does the equation predict for the number of hours the phone will last at a brightness level of 36? 6.2 hours Round your answer to…
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