- 11The final score (Y ) of students in a course was correlated with score() in entrance test. The relevant data in coded units are as follows:Y:86.4X :16.3(a) Obtain the linear regression equation of Y on X.(b) Obtain the correlation coefficient and interpret it.(c) Predict Y when X = 4. If the predicted value is different fromthe observed value of 6. Explain the reasons for the difference.%3D

(a) Use EXCEL to determine the regression equation. EXCEL procedure: Go to EXCEL Go to…

Answered: 11 The final score (Y ) of students in…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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
c) Show that the coefficient of determination, R², can also be obtained as the squared correlation between actual Y values and the Y values estimated from the regression model where Y is the dependent variable. Note that the coefficient of correlation between Y and X is Eyixi r = And also that ỹ = ŷ (18.75)
It is known that the linear regression equation: y= -2.88+1.77x, with a coefficient of determination of 0.81. Based on the two information, the correlation coefficient is
The mortality rate of a sample of the population as a function of daily tobacco consumption can be seen below: Number of cigarettes "x": 3 5 6 15 20 Mortality rate "y" : 0.2 0.3 0.4 0.5 0.7 With these data, solve the following: a. Determine and interpret the correlation coefficient. b. Find the regression line of y on x. c. What will be the mortality rate for a consumer of 40 cigarettes per day?
The table below gives the number of weeks of gestation and the birth weight (in pounds) for a sample of five randomly selected babies. Using this data, consider the equation of the regression line, y = bo + b1x, for predicting the birth weight of a baby based on the number of weeks of gestation. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Weeks of Gestation 33 34 36 38 41 Weight (in pounds) 6 6.1 6.8 7.3 7.9 Table Copy Data Step 4 of 6: Find the estimated value of y when x = 36. Round your answer to three decimal places.
The following table shows students’ number of absences, x, and the student’s final grade,, y.# of absences x 6 2 15 9 12 5 8 Final grade y 82 86 43 74 58 90 78a) Calculate r, the correlation coefficient ________________b) Find the equation of the regression line __________________________________c) If a student is absent 4 times,, what grade does your regression line predict?__________________
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There is a dataset of size n = 51 and is for the 50 states and the District of Columbia in the United States. The dependent variable is year 2002 birth rate per 1000 females 18 to 19 years old and independent variable is the violent crime rate (per 1000 population). A simple linear regression model is run with the results given below. What is the Pearson correlation coefficient between x and y variables? The R squared of the model? What kind of relationship there is?
Calculate the co-efficient of correlation and the lines of regression for the following data: 1 2 3 4 5 7 8 9 X= y= 8 10 12 11 13 14 16 15. Obtain an estimate of y which should correspond on the average to x= 6. 2.
A linear regression analysis reveals a strong, negative linear relationship between x and y. Which of the following could possibly be the results from this analysis? (A) ŷ 13.1 27.4x, r = 0.85 (B) == 27.4+ 13.1x, r = -0.95 (D) == (C) ŷ 13.1+ 27.4x, r = 0.95 542 385x, r = -0.15 (E) 0.85 0.25x, r = -0.85

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