Radius (cm)Diameter (cm)Volume (cm?)14.1933.51113.104.8.268.0810523.609.12904.78141436.768.162144.66183053.6310204188.7911225575.28Now decide what variables to graph to so that your data points produce a linear line.X-axisY-axisMake a graph and draw the best fit line or curve on your graph. Calculate the slope of theor curve.SlopeEquation of the line2.009,

Concept: Slope: A line's slope is determined by how its y coordinate changes in relation to how its…

Answered: Radius (cm) 1 2 3 4 5 6 7 8 9 10 11…

Elementary Geometry For College Students, 7e

7th Edition

ISBN:9781337614085

Author:Alexander, Daniel C.; Koeberlein, Geralyn M.

Publisher:Alexander, Daniel C.; Koeberlein, Geralyn M.

ChapterP: Preliminary Concepts

SectionP.CT: Test

Problem 1CT

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Fit a linear regression model for the following data.
The temperature of a liquid during the first four minutes of an experiment has been recorded in the table below. Time (x) (minutes) 0 1 2 3 4 Temperature (y) (°C) 30 33 40 56 73 Determine if the relationship between temperature and time is linear by constructing a residual plot.
Please proper explaintion and excel file solution
Why this type of plot is used in analysing regression models
Breakfast cereals We saw in Chapter 7 that the calorie con-tent of a breakfast cereal is linearly associated with its sugar content. Is that the whole story? Here’s the output of aregression model that regresses Calories for each serving onits Protein(g), Fat(g), Fiber(g), Carbohydrate(g), andSugars(g) content.Dependent variable is CaloriesR-squared = 84.5, R-squared (adjusted) = 83.4,s = 7.947 with 77 - 6 = 71 degrees of freedomSource Sum ofSquares dfMeanSquare F-RatioRegression 24367.5 5 4873.50 77.2Residual 4484.45 71 63.1613Variable Coefficient SE(Coeff) t-Ratio P-ValueIntercept 20.2454 5.984 3.38 0.0012Protein 5.69540 1.072 5.32 60.0001Fat 8.35958 1.033 8.09 60.0001Fiber -1.02018 0.4835 -2.11 0.0384Carbo 2.93570 0.2601 11.3 60.0001Sugars 3.31849 0.2501 13.3 60.0001Assuming that the conditions for multiple regressionare met,a) What is the regression equation?b) Do you think this model would do a reasonably goodjob at predicting calories? Explain.c) To check the conditions, what…
TOPIC: Linear Regression please answer, will upvote your solutions.
statistic please answer
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…
Please show work on paper and circle answer
Please no written by hand solution Identify the residual plot that shows the linear regression model is a good fit for the data.

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