An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 20 155.4 21.5 172.2 23 178.7 24.5 190.4 26 208.2 27.5 220.2 29 232.2 A) Write the linear regression equation for the data in the chart. Volume = where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 18, using your un-rounded regression equation find its predicted volume. Round your answer to 1 decimal place. mL

An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 20 155.4 21.5 172.2 23 178.7 24.5 190.4 26 208.2 27.5 220.2 29 232.2 A) Write the linear regression equation for the data in the chart. Volume = where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 18, using your un-rounded regression equation find its predicted volume. Round your answer to 1 decimal place. mL

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

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.)
Fit a linear regression model for the following data.
(a) Write a note on the Skewness and Kurtosis consisting of their types and geometrical presentations. (b) Compute the Kurtosis for the following data using any appropriate formula and interpret the data with the help of its obtained numeric value.Classes Frequency100-109 5110-119 10120-129 15130-139 15140-149 10
For the data in the table, find the regression equation. Round the slope and y-intercept two decimals. y 3 12 13 16 10 29 12 32 15 35 18 37 19 39 20 40 Use your equation to predict y when x = 21 y = Submit Question 467 O258098
The following table shows the hot dogs bought from a street vendor over the course of eight days ("Demand"). Also shown is the temperature for each day in degrees Celsius. Temperature (°C) 19 Demand 45 10 30 23 34 17 42 a. Calculate the SST. SST = (Round to two decimal places as needed.) 6 19 19 O 13 16 22 42 32 A linear regression on the data gives the equation below. Complete parts a through d below. Predicted Demand = 15.58+1.15(Temperature) (...)
The ages (in years) of five men and their systolic pressures. (You can use technology) Age, x 16 25 39 45 49 Systolic blood pressure, y 109 122 143 132 199 a. calculate the correlation coefficient, r b. calculate the critical r c. Is there a significant linear relationship between x and y? d. find the equation of regression line e Interpret the slope and the y-intercept f. Predict the systolic blood pressure for a man who is 40 years old.
An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 17 174.8 19.5 208.6 22 230.8 24.5 257 27 280.4 29.5 312.5 32 329 A) Write the linear regression equation for the data in the chart. Volume x + where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 15, using your un-rounded regression equation find its predicted volume. Round your answer to 1 decimal place. mL
The table below shows how far a person driving in their car was able to go over different intervals of time. Perform a regression to model the data, using the form y = ka + h. What is your value for k? (Round your answer to the nearest tenth.) Time (hours) Distance (miles) 1.2 26 2.5 57 3.1 63 4.8 114
A physician wishes to know whether there is a relationship between a father’s weight (in pounds) and his new born sons’ weight (in pounds). The data are given here Fathers Weight 176 145 187 210 196 142 205 215 152 145 Sons Weight 6.6 8.2 9.2 7.1 8.8 9.3 7.1 8.6 7.8 6.0 Develop the regression equation for the sample Predict the sons weight based on the father’s weight of 300, 250 and 400.
Use the data in the table below to complete parts (a) through (d). 39 33 40 47 42 50 59 56 51 24 22 27 32 30 31 31 27 29 Click the icon to view details on how to construct and interpret residual plots. (a) Find the equation of the regression line. (Round to three decimal places as needed.) (b) Construct a scatter plot of the data and draw the regression line. Plot the x-values on the horizontal axis and the y-values on the vertical axis. Choose the correct graph below. OA. В. Oc. OD. 34 70, (c) Construct a residual plot. Plot the x-values on the horizontal axis and the residuals on the vertical axis. Choose the correct graph below. O A. Ов. Oc. OD. (d) Determine if there are any patterns in the residual plot and explain what they suggest about the relationship between the variables. The residual plot a pattern because the residuals about 0. This implies the regression line a good representation of the relationship between the variables.
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the valuo of v for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 762 621 508 480 (b) x = 641 feet (d) x = 726 feet 515 491 (a) x= 498 feet (c) x = 810 feet 51 46 44 42 38 37 Find the regression equation. ý=x+ (D (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. OA. OB O B. Oc. OD. 60- 604 60+ 800 B00 G 800 Height (feet) 800 Height (feet) 800 Height (feet) Height (feet) (a) Predict the value of y for x = 498. Choose the correct answer below. OA 40 ОВ. 50 O C. 47 O D. not meaningful (b) Predict the value of y for x 641. Choose the correct answer…
An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 15 205.9 16.5 224.3 18 244.7 19.5 267.7 21 279.7 22.5 312 24 326.2 A) Write the linear regression equation for the data in the chart. Volume where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 13, using your un-rounded regression equation find its predicted mL volume. Round your answer to 1 decimal place.