We all know that when the temperature of a metal increases, it begins to expand. So,we experimented with exposing a metal rod to different temperatures and recorded itslength as follows:TempLength202530354045505560650.51.856.26.57.89.49.810.9Required:1. Implement and plot a simple linear regression for the above data, where thetemperature is "x", and the length is "y"2. Implement and plot a multiple linear regression "Polynomial regression" withdifferent degrees.For example, Degree of 3:Y = Wix' + w2x? + w3x? + W4Where wa represents bias.*you can use normal equation to calculate W' as follow:w = (X".X)4.(XT.Y)Then calculate Y, Where Y = X.WT3. Try degree of 2, 3, 5, and 8

In this experiment, the goal is to analyze the relationship between the temperature and length of a…

Answered: We all know that when the temperature…

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 following table contains data for the number of bacteria y (in millions) growing in a particular medium after x hours. Using a calculator or statistical software, find the linear regression line for the data in the table. Enter your answer in the form y=mx+b, with m and b both rounded to two decimal places. x y 0 3.67 1 5.24 2 7.04 3 10.31 4 9.83 5 11.04 6 14.68 7 15.02
The following data on x= maternal age in years of the young birth mothers and y weight of baby born in grams summarizes the result of a study. Assume that a simple linear regression model y = Bo + B1x + e is an appropriate model for the study. x-bar 17 (avg of y-bar 3004.1 x's) (avg of y's) SSXX = 20 SS= 4903 SSyw = 1539182.9 n- 10 Calculate the estimated for Bo and B correct to T WO decimal places. Using your results, predict the average weight of a baby born for a value of x = 18. Enter your answer correct to TWO DECIMAL PLACES.
Managers rate employees according to job performance and attitude. The results for several randomly selected employees are given below. Performance (x) / 10 / 5 / 6 / 6 / 9 / 3 / 3 / 4 / 5 / 9 Attitude (y) / 3 / 9 / 7 / 6 / 8 / 10 / 3 / 3 / 4 / 7 Use the given data to find the equation of the regression line. Enter the slope. (Round your answer to nearest thousandth.)
Consider the following population linear regression model of individual food expenditure: Y = 50 + 0.5X + u, where Y is weekly food expenditure in dollars, X is the individual’s age, and 50+0.5X is the population regression line. Suppose we generate artificial data for 3 individuals using this model. This artificial sample, which consists of 3 observations, is shown in the following table: Answer the following questions. Show your working. (a) What are the values of V1 and V4? (b) Suppose we know that in this artificial sample, the sample covariance between X and Y is 150, and the sample variance of X is 100. Compute the OLS regression line of the regression of Y on X. (Hint: Assume these summary statistics and the OLS regression line continue to hold in parts (c)-(e).) (c) What are the values of V5 and V7?
A group of scientists and engineers aim to create fuel-efficient and fuel-efficient cars. In order to study the problem, they randomly selected a sample of 20 cars and took information from X: weight (hundreds of pounds) and Y: vehicle performance (mill / gal). Once the information was collected and analyzed, using a scatterplot, they determined that a linear model can fit the data. Using R the following information is obtained from the linear regression model. Y = 40.15−0.513X According to the model, what would be the weight of a car with a performance of 14 mill / gal? Select one: a. -39.98 lbs b. 39.98 lb c. 77.82 lb d. -77.82 lb
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. Complete parts a and b below. Temperature (°C) 20 Demand 49 11 23 32 36 19 40 5 17 10 21 16 44 20 D 34 a. Calculate the slope and y-intercept for the linear regression equation for these data. ŷ=+* (Round to two decimal places as needed.)
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) (...)
Question 8 please
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.
Suppose the analyst constructs the simple linear regression model In(y) = a + Bx+e. She estimates it to be In() = -1- 1.3x. What is the residual in Excel output for the pair of observations x= 1.5 and y = 27 O a. 6. O b. 1.98 O c. -2. O d. 403.43 e. 4.29
For a week prior to their final exam, a group of friends collect data to see whether time spent studying (r) had a strong correlation with their marks on the exam (y). The collected data is summarized in the following table: Time Spent Studying (hours): 10 11 15 14 7 6. Exam Grade (%): 71 67 81 93 54 66 а) Plot the data (y versus æ). Produce a regression of y against r and report an r? value for this fit. Add the b) regression line to the plot in a). Do you think that the regression line captures the most important features of the data set reasonably well? c) At a 5% significance level, is there a significant linear relationship between the x and y? Does this result agree with the conclusion you made in b)? Testing at a 5% significance level, can you say that Bo is not zero? How does d) this conclusion agree with the plot in a)?
Consider the following regression equation representing the linear relationship between the Canada Child Benefit provided for a married couple with 3 children under the age of 6, based on their annual family net income: ŷ =121.09−0.57246xR2=0.894 where y = annual Canada Child Benefit paid (in $100s) x = net annual family income (in $1000s) Source: Canada Revenue Agency a. As the net annual family income increases, does the Canada Child Benefit paid increase or decrease? Based on this, is the correlation between the two variables positive or negative?The Canada Child Benefit paid .The correlation between the two variables is .b. Calculate the correlation coefficient and determine if the relationship between the two variables is strong, moderate or weak.r= , the relationship is . Round to 3 decimal places c. Interpret the value of the slope as it relates to this relationship. For every $1 increase in annual family net income, there is a $0.57246 decrease in…

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS