A 95 percent confidence interval for the slope of the regression line relating the number of grams of carbohydrates and the number of kilocalories per 100-gram sample of various raw foods is given by (2.505, 6.696). Theconfidence interval is based on a random sample of n raw foods. A check of the conditions for inference on the slope shows they are reasonably met.Which of the following is a correct interpretation of the interval?Ninety-five percent of all such samples of size n will produce a sample slope between 2.505 and 6.696 for the regression line relating grams of carbohydrates and kilocalories per 100-gram sample ofvarious raw foods.The probability is 0.95 that the true slope of the regression line relating grams of carbohydrates and kilocalories per 100-gram sample of various raw foods is between 2.505 and 6.696.CWe are 95 percent confident that the slope of the regression line for the random sample of n raw foods is between 2.505 and 6.696.We are 95 percent confident that the predicted number of kilocalories per 100-gram sample will be between 2.505 and 6.696.We are 95 percent confident that the true slope of the regression line relating grams of carbohydrates and kilocalories per 100-gram sample of various raw foods is between 2.505 and 6.696.

A 95 percent confidence interval for the slope of the regression line relating the number of grams of carbohydrates and the number of kilocalories per 100-gram sample of various raw foods is given by (2.505, 6.696). The confidence interval is based on a random sample of n raw foods. A check of the conditions for inference on the slope shows they are reasonably met. Which of the following is a correct interpretation of the interval? Ninety-five percent of all such samples of size n will produce a sample slope between 2.505 and 6.696 for the regression line relating grams of carbohydrates and kilocalories per 100-gram sample of various raw foods.

A 95 percent confidence interval for the slope of the regression line relating the number of grams of carbohydrates and the number of kilocalories per 100-gram sample of various raw foods is given by (2.505, 6.696). The confidence interval is based on a random sample of n raw foods. A check of the conditions for inference on the slope shows they are reasonably met. Which of the following is a correct interpretation of the interval? Ninety-five percent of all such samples of size n will produce a sample slope between 2.505 and 6.696 for the regression line relating grams of carbohydrates and kilocalories per 100-gram sample of various raw foods.

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

please answer correctly and give me the right answer
Data on 12 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were measured in minutes and a regression analysis was performed. ski 85 2.5. treadmill = Coefficients Estimate (Intercept) Treadmill 85 - 2.5 Std. Error What is the test statistic? -2.5 0.45 1 Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance? Round your answers to three decimal places. Using your answer from the previous question, find the p-value. Part 2 o
The ANOVA summary table to the right is for a multiple regression model with six independent variables. Complete parts (a) through (e). Draw a conclusion. Choose the correct answer below. (3) Degrees of Source Freedom Regression Error Total 6 26 32 Sum of Squares 240 190 430 A. There is insufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is less than the critical value. O B. There is sufficient evidence of a significant linear relationship with at least one of the independent variables because the p-value is less than the level of significance. C. There is sufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is greater than the level of significance. D. There is insufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is greater than the critical value.
The average midterm score in a large statistics class was 60 with an SD of 5. The average final score in the same class was 80 with an SD of 15. The correlation coefficient between midterm and final scores was r=0.6. Using the regression line, we predict the final score of a student with a midterm score of 70 to be but this prediction is likely to be off by about Fill in the blanks, rounding each answer to one decimal point.
3) For a sample of 306 students in a basic business communications course, the sample regression line y = 58.813 + 0.2875x was obtained. Here y = final student score at the end of the course x = score on a diagnostic writing skills test given at the beginning of the course The coefficient of determination was 0.1158 and the estimated standard deviation of the estimator of the slope of population regression line was 0.04566. a) Define and interpret the estimates of the regression equation. b) Interpret the coefficient of determination. c) What will happen to the final student score if his diagnostic writing test score increases by 2? d) How can you inmprove this model?
After you estimate a simple linear regression you obtain the following sample regression function: Y₁ = 8.8 +0.7091 Xį With an r² of 0.784. The observed dependent variable used for the regression is: Y 9 675 40 40 40 6 5 5 5 5 1 1 Compute the sample variance of X? 8.45 10.79 9.17 7.19 Cannot be computed with the provided information.
The following sample contains the scores of 6 students selected at random in Mathematics and English. Use the scores in English as the dependent variable Y. Mathematics score (X) 70 92 80 74 65 83 English score (Y) 74 84 63 87 78 90 ∑x=464, ∑y=476,∑x^2=36354,∑y^2=38254, ∑xy=36926. Estimate the regression parameters and also write the prediction equation.
Suppose that a researcher, using data on 150 randomly selected bicycles, estimates the OLS regression: Price=672.65-2.12x Weight, (185.8) (0.42) where Price measures the price of the th bike in dollars and Weight measures the weight of the th bike in kilograms. The 99% confidence interval for the intercept, ßo, will be (, ). (Round your answers to two decimal places.)
To investigate the relationship between the selling price of a house, yy, in dollars, and the size of the house xx, in square feet, a local builder collected data on a random sample of 120 houses from a certain region. Assume that the conditions for inference for the slope of a regression line are met. The resulting 95 percent confidence interval for the population slope of the regression line relating price and size is given by (62,99). The local builder claims that the selling price of houses from the region increases by $104 for every extra square foot of space in the house. Which of the following best describes the conclusion that can be reached about this claim based on the confidence interval? A)The claim is supported by the interval, since the interval does not contain the value 0. B)The claim is supported by the interval, since all values in the interval are positive. C)The claim is supported by the interval, since the interval does not contain the…
П. 2. What is the degrees of freedom in a multiple regression model( with n values in each variable) with 14 independent variables when doing a t-test for the individual regression coefficients determined?
Below is the output for regression equation for a realtor with 2 independent variables of square footage and number of bedrooms. 30 homes were included. Standard Coefficients Error t Stat P-value Intercept 99.217.87 111.681.14 0.89 0.39 Sq Ft 107.69 54.04 1.99 0.07 Bedrooms 120.130.59 36.467.30 3.29 0.01 What is the 90% confidence interval for the slope of square footage? 107.69 + 1.703 - 54.04 107.69 + 1.701 - 54.04 54.04 107.69 + 1.703- O 107.69 + 1.701 - 54.04
i)Test individually whether the slope coefficients are significant at 10% significance level. ii)Test the overall significance of the estimated regression at 1% significance level.