Annual high temperatures in a certain location have been tracked for several years. Let X represent thenumber of years after 2000 and Y the high temperature. Based on the data shown below, calculate thelinear regression equation using technology (each number to three decimal places).ŷXClick Download CSV to download csv file of data or copy/paste the data into Excel. After downloading thefile, you may want to save it as an Excel Workbook.The fitted regression equation is-y031.6132.232 33.563 31.99431.925 34.556 33.88736.518 35.54936.4710361136.93Interpret the y-intercept of the equation:O In 2000, the temperature was about 31.5.O In 2000, the temperature was about 0.503.O In 2000, the temperature was about 31.5.O In 2011, the temperature was about 36.93.

The data related to the number of years after 2000 and the high temperature is given.The independent…

Answered: Annual high temperatures in a certain…

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

help ASAP
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). X y 3 35.01 4 37.78 5 37.35 6 36.72 7 40.09 8 40.36 9 40.83 10 41.3 11 40.57 12 42.64 13 44.21 14 42.58 15 46.05 16 45.12 The equation is ĝ ŷ = X + Interpret the slope O For each additional 33.75 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 33.75 degrees on average. For each additional year, the annual high temperature will increase by 0.74 degrees on average. O For each additional 0.74 years, the annual high temperature will increase by 1 degree on average. Interpret the y-intercept O In 2000, the temperature was about 33.75. O In 2003, the temperature was about 33.75. O In 2003, the temperature was about…
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.)
Annual high temperatures in a certain location have been tracked for several years. Let x represent the number of years after 2000 and y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to three decimal places). X y 3 37.64 4 37.02 5 39.4 6 40.78 7 40.76 8 44.54 9 44.42 10 46.2 11 45.58 12 46.66 13 49.54 The equation is ŷ
An instructor asked a random sample of eight students to record their study times at the beginning of a course. She then made a table for total hours studied (x) over 2 weeks and test score (y) at the end of the 2 weeks. The table is given below. Complete parts (a) through (f). x 10 13 10 18 6 15 16 21 y 93 79 81 74 85 81 85 80 a. Find the regression equation for the data points. b. Graph the regresson equation c. Describe the apparent relationship between the two variables. d. Identify the predictor and response variables. e. Identify outliers and potential influential observations. f.Predict the score for a student that studies for 17 hours.
Annual high temperatures in a certain location have been tracked for several years. Let X represent the year and Y the high temperature. Assume that temperature is independent each year. Based on the data shown below, calculate the regression line (each value to two decimal places). First the slope and then the y-intercept. Y X 3 4 5 67 8 00 a 9 y 10.14 10.85 11.86 11.17 7.58 9.79 7.5 x+
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable, Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? 1220 1075 986 88 5 843 821 849 697 758 1170 867 939 D Chirps in 1 min Temperature ("F) What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000 chirps per minute is F (Round to one decimal place as needed.) What is wrong with this predicted value? Choose the correct answer below O A. The first variable should have been the dependent variable O B. It is unrealistically high. The value 3000 is…
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). x y 4 36.68 5 35.85 6 35.52 7 35.99 8 38.46 9 38.93 10 38 11 38.07 12 39.54 13 40.11 14 41.58 The equation is y^ = x + Interpret the slope For each additional 33.38 years, the annual high temperature will increase by 1 degree on average. For each additional 0.52 years, the annual high temperature will increase by 1 degree on average. For each additional year, the annual high temperature will increase by 0.52 degrees on average. For each additional year, the annual high temperature will increase by 33.38 degrees on average. Interpret the y-intercept In 2000, the temperature was about 33.38. It does not make sense to interpret the intercept in this scenario. In 2004, the…
Perform a linear regression analysis on the following data and determine the "a" coefficient (i.e., slope): Y 4.99 22.19 1.96 9.89 2.98 11 9 40.46 4.04 18.93 6.06 25 0.88 0.19 8.02 34.02 6.97 28.03
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1118 796 1161 918 1103 1219 Temperature (F) 82 72.2 92.2 73 87.5 94.4
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to one decimal place). X 1 2 3 4 5 6 7 8 9 10 11 y 33.99 37.78 37.27 37.16 37.65 40.54 41.13 42.52 40.11 41.9 45.69 The equation in y-ax+b form is Interpret the y-intercept of the equation: O For each additional 0.9 years, the annual high temperature will increase by 1 degree on average. For each additional 34.3 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 0.9 degrees on average. O For each additional year, the annual high temperature will increase by 34.3 degrees on average.

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