Using least square method, find the regression line model. Interprete your result. Calculate the coefficient of correlation and explain. Calculate the coefficient of determination and explain your answer.

Using least square method, find the regression line model. Interprete your result. Calculate the coefficient of correlation and explain. Calculate the coefficient of determination and explain your answer.

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

You generate a scatter plot using Minitab. You then have Minitab plot the regression line and report the equation and the r2 value. The regression equation is reported as y=43.41x+77.98 and the r2=0.2025.What is the correlation coefficient for this data set? r =
Explain how the coefficient of multiple determination, R2, is used as a descriptive measure in multiple linear regression.
Can you please tell also the test statistics and if the weight is close to 518 pounds?
Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y=-59.97x+67.54 and the r=-0.31 What percentage of the variation in y can be explained by the variation in the values of x? r² = % (Report exact answer, and do not enter the % sign) .
Need some help
The values of advertisement expense (X) and sales (Y) are shown in the table below. Find the regression line. Estimate the value of sales when advertisement expense is 20.
Define Multiple Regression?
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years, construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $888 the equation of the regression line is y= 1.453x-47.386. Wages(state), X | 739|760|784|822|898|921|937|954|965| Wages (federal), Y |1,036|1,054|1,105|1,136|1,192|1,253|1,266|1,327|1,400|
Save 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 776 1173 1034 951 975 1214 D Temperature (°F) 70.1 89 77.4 76.2 77 92.6 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) Incorrec ary ns
answer both please and explain well. Anna company sells coffee products to various customers. In recent years, profits have been declining. The CFO of the company investigated the reasons for the profit decline and performed regression analysis for sales and costs. The CFO determined that sales depend on product price, delivery speed, customer services, and marketing expenses. She also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales. Questions 1. Define the coefficient of determination and explain what it means in this scenario. 2. Express the relationship between total costs and variable costs for Anna Company using a regression equation. Explain each element of the equation.
help asap please. I will upvote.
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 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)