### Transcription and Explanation**10. You are given the following data and scatterplot:**#### Data Table:- **x** | **y**- 0 | 2- 1 | 6- 5 | 8- 6 | 7- 8 | 10- 10 | 15#### Scatterplot:A graph is provided with the data points plotted, showing the distribution of the values of x and y. The horizontal axis represents the value of x ranging from 0 to 12, and the vertical axis represents y ranging from 0 to 16.---#### Questions:**a) Perform a linear regression. Give the equation as well as the value for \( r^2 \).****b) What proportion of the total variation of y is explained by the linear model?****c) What is the value of the linear correlation coefficient?**---### Diagram Explanation:The scatterplot shows a positive correlation between x and y values. Points are distributed in a way that suggests a linear relationship, with a general upward trend as x increases.The tasks involve finding the linear regression equation for the set of data points, which can be used to predict y from x. Additionally, calculating \( r^2 \) will show how well the regression line fits the data, indicating the proportion of variance in y explained by this linear model. The correlation coefficient will provide insight into the strength and direction of the linear relationship between x and y.

The independent variable is x. The dependent variable is y. This is simple linear regression model.…

Answered: 10. You are given the following data…

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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(New Question) Which of the following is true about panel data regression? In panel data, there is a possibility of autocorrelation because of the correlation between u and u, where ujt and u are error terms for entity i and j. O Fixed effect model imposes the same intercept across the entities but allows for different slopes in estimation. O Panel data can be more useful than cross-sectional data because with panel data it is possible to estimate the regression coefficients even if X is fixed over time within entities. O The time-demeaned OLS regression transforms the data by deviating X and Y by the average across entities at each time t.
Data were gathered and displayed on the scatter plot. 15 y 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Which of the following is the best equation to model the data? ŷ = 11.5(0.81)* Oŷ = 8.1(0.115)* Oŷ= -0.115x+8.1 Oŷ=-0.81x+11.5
X 33 46 72 105 114 Y 209 228 170 127 109 1) What is slope of the regression line predicting Y from X,rounded to 2 decimal places? 2) What is the intercept of the regression line predicting Y from X, rounded to 2 decimal places? 3) What is the correlation between X and Y, rounded to 2 decimal places?
You are given below the following information about advertising and sales. Adv. Exp. (X) (S Lakhs) Sales (Y) Lakhs) Мean 10 90 S.D. 3 12 Correlation Coefficient 0.8 (a) Calculate the two regression lines. (b) Find the likely sales when advertisement expenditure is (c) What should be the advertisement expenditure if the company wants to attain a sales target of 15 lakhs. 120 lakhs ?
Need help answering A, B and C. B) Perform the linear regression calculation and provide the linear regression equation that describes the relationship between Y (number of air conditioning units sold) and X (outside temperature in degrees Fahrenheit. Calculate: Coefficient of determination (r2) and the coefficient of correlation (r).  SST, SSE and SSR for this linear regression.  Estimate for the variance (σ2) and the standard deviation for the linear regression model you have developed. C) Using the linear regression equation that you developed in topic (b), calculate the estimated sales for a day that will reach 72 degrees F and for a day that will reach 94 F and for both temperature levels calculate the error “e” when comparing the estimated value against the actual data provided. At which of the two temperatures, is your model more accurate? Justify.
Hello tutor, please help me to understand this 2 part MCQ question. Thank you. Part A) Based on Image 1, A researcher examined the relationship between weight (y axis) and height (x axis) among 475 male subjects. He graphed the relationship in the scatter diagram below. Weight is measured in pounds, and height in inches. The equation of the regression line is y = 3.86*x – 110.42. Is it reasonable to presume that if a male is 107 inches tall, his weight will be 302.6 pounds? a) Yesb) No Part B) Based on Image 2, A researcher examined the relationship between Variables X and Y among 150 male subjects, and he graphed a scatter plot as seen below. The correlation coefficient for all the 150 data points is about 0.5. Let K be the correlation coefficient for the data points with X values lying between 130 to 150. Which of the following statements is correct?a) K is less than 0.50.b) K is more than 0.50.c) None of the other options.
The following table contains ACT scores and the GPA for eight college students. Estimate the relationship between GPA (yi) and ACT (x;) using OLS regression by hand. Report the intercept and slope estimates: Student 1 2 3 4 5 6 7 8 GPA 2.8 3.4 3.0 3.5 3.6 3.0 2.7 3.7 ŷ₁ =B₁ + B₁x₁ ACT 21 24 26 27 29 25 25 30 y X ŷ₁
A teacher has found that his class performed particularly well on a quiz when the material was related to pop culture (M= 77) compared with normal quiz performance (u= 69, 0 =20 ). What is the effect size for this effect? Select one: • a. 0.40 e b. 1.57 • c. 0.94 • d. -0.94 e e. All of the above
a) Determine the correlation coefficient, r, and interpret this value in the context of the problem. (Round 4 decimal places)b) Find the equation of the regression line for the given data. (Round the slope and y-intercept 4 decimal places).c) Give a practical interpretation of the slope of the regression line.
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?

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