4. In a statistical investigation the grade point average (y) and study hour (x) of a group ofstudents are observed as follows:Study hour (x)Grade point (v)12 17 16 14 11 13 153.0 3.2 3.5 4.0 3.8 2.7 3.4i) Fit a line of y on x and test the significance of regression.ii) Estimate y if x = 17.

We have given the following data Study hour (x) Grade point (y) 12 3 17 3.2 16 3.5 14 4…

Answered: 4. In a statistical investigation the…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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True/false (please explain). Suppose that a regression of Y on X₁ is unbiased, and the true slope coefficient is 2. Another variable X2 is correlated with Y, but it is uncorrelated with X₁. In expectation, the default t-statistic on B₁ will be larger in the multivariate regression that includes X₂ than in the bivariate regression that omits X₂.
Zagat restaurant guides publish ratings of restaurants for many large cities around the world. The restaurants are rated on a 0 to 30 point scale based on quality of food, decor, service, and cost. Suppose that someone wants to predict the cost of dinner at a restaurant in a city based on the Zagat food quality ratings. If 10 restaurants in a city are sampled and the regression output is given below, what can we conclude about the slope of food quality? Since we are not given the dataset, we do not have enough information to determine if the slope differs from 0. 2) The slope is 2.521 and therefore differs from 0. 3) The slope significantly differs from 0. 4) Not enough evidence was found to conclude the slope differs significantly from 0. 5) The slope is equal to 0.
In a sample of cars reviewed by Motor Trend magazine, the mean horsepower (hp) was 150 hp with a standard deviation of 36 hp. The mean weight (lbs) was 2500 lbs with a standard deviation of 720 lbs. Assume the relationship between weight and horsepower is linear and has a correlation of r = +0.55. What is the slope of the linear regression model predicting weight (y-variable) from horsepower (x-variable)? 9 13 15 11
A researcher records age in years (x) and systolic blood pressure (y) for volunteers. They perform a regression analysis was performed, and a portion of the computer output is as follows: ŷ = 4.5+ 14.4x Coefficients (Intercept) x Estimate 4.5 Ho: B₁ = 0 H₁: B₁ > 0 Ho: B₁ = 0 Ha: B₁ <0 14.4 Ho: B₁ = 0 Ha: B₁ #0 Std. Error Test statistic 2.9 4.7 1.55 3.06 P-value Specify the null and the alternative hypotheses that you would use in order to test whether a linear relationship exists between x and y. 0.07 0
It is evaluated that there is a relationship between working experience in the business (X) and the number of daily errors (Y). Data are given below. What is the Regression Mean Square of Departure (RAKO) in the validity of the regression model?
e) Perform the F Test making sure to state the null and alternative hypothesis.
True or False and explain if false: 1. The slope estimate from a regression model is an example of descriptive statistic. 2. if a p-value is 0.9, then we may appropriately conclude that no relationship between X and Y exists 3. Assuming that X variable is controlled, one way to decrease standard errors in a sample linear regression analysis is to assign value of X variable that are further apart.
19
21. Which of the following statements is true regarding the sources of variation present in an analysis of regression? SSy is partitioned into variation explained by the regression model and residual variation. If most of the variability in Y is associated with residual variation, then X predicts Y. There are three sources of variation in an analysis of regression: regression variance, residual variance, and error variance. Regression variation measures variability in X, whereas residual variation measures variability in Y.
Consider the following data,Study Hours (Y): 2, 4 ,6 ,8 ,10 ,13, 7Sleeping Hours (X): 10, 9, 8, 7,6 ,7, 5 i) Calculate and analyze the fitted regression line between the number of study hours and the number of sleeping hours of different intakes of CSE students.ii) Find the coefficient of determination and interpret your data.iii) Predict study hour when he/she sleeps 11 hours.
I need correct only handwritten otherwise skip pls
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.

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4. In a statistical investigation the grade point average (y) and study hour (x) of a group of students are observed as follows: Study hour (x) Grade point (v) 12 17 16 14 11 13 15 3.0 3.2 3.5 4.0 3.8 2.7 3.4 i) Fit a line of y on x and test the significance of regression. ii) Estimate y if x = 17.