Consider the following dataset.S.No. Y50.00 12.0066.00 18.0061.00 16.231.002.003.004.0079.00 32.065.0052.00 17.00Determine the following:a. Make a scatter diagram between the variables Y and Xb. Find correlation coefficient between the variables Y and X. Show all calculations.c. Make linear model equation (regression equation) with Y as the output variable and X as the inputvariable. Show all calculation for slope and intercept.d. Using hypothesis testing do you have enough statistical evidence to show relationship between Xand Y?

Since you have asked multiple questions, we will solve first three subparts for you. To get…

Answered: Consider the following dataset. S.No. Y…

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

6.In simple linear regression, the sample correlation coefficient between the input variable and the output variable, and the estimated slope parameter : a.Must have the same sign (negative, zero, or positive) b.May have opposite signs c.Must have opposite signs d.Neither of the above
Question-6 Use the Table given below to find out: a. Correlation coefficient between Hydrocarbon levels and purity. b. Regression model. Observation number 1 2 3 4 5 6 7 8 9 10 11/ 12 Hydrocarbon Levels, % 0.99 1.02 1.15 1.29 1.46 1.36 0.87 1.23 1.55 1.4 1.19 1.15 Purity % 90.01 89.05 91.43 93.74 96.73 94.45 87.59 91.77 99.42 93.65 93.54 92.52 Pu
A departmental store has the following sales for a period of last one year of 8 salesmen, who have different years of education. Years of Education 8 10 10 12 14 16 Annual Sales (Thousand Tk.) 100 120 80 100 80 100 70 130 a. Determine the correlation coefficient r between the two variables. Answer rounded to at least 4 decimal places. b. Determine the slope coefficient B1 for the regression of annual sales on years of education. Answer rounded to at least 4 decimal places. c. Determine the y-intercept Bo for the regression of annual sales on years of education. Answer rounded to at least 4 decimal places. d. What will be the annual sales when the years of education is 11 (years)? Answer rounded to at least 4 decimal places. Thousand Tk.
A company wishes to estimate a regression line for the relationship between sales and advertising. а. To arrive at its decision regarding the best model to use, the company has calculated the following three correlation coefficients. i. ii. The sales in any month depend on that month's advertising with r = 0.28 The sales in any month depend on 50% of the previous month's advertising and 50% of that month's advertising with r= 0.68 The sales in any month depend on the previous month's advertising with r = 0.92 iii. Interpret each of the above correlation coefficients and state which of the suggested models you would choose as the basis for predicting sales. Justify your answer.
Given are 3 observations for two variables, x and y. 1 3 6. 9. 10 What is the estimated regression equation? Select one: a. ÿ = -2 + 6.5x O b. ý 10.89 – 0.87x с. у -0.87+ 10.89x d. ŷ 6.5 – 2x %3D
Consider the following scatter and residual plots: Discuss whether the scatter data are appropriately represented with a linear model. Include in your answer comments relating to the level of correlation between the two variables. Edit View Insert Format Tools Table 12pt Paragraph BI UAV T²:
1945 is paired with cancer rates for 1975. The cigarette consumption data is from 1945 to 1975 in 5-year increments. There is a strong positive linear association between annual cigarette consumption and lung cancer rates. The correlation is 0.81. If we use the line to make predictions of the number of lung cancer deaths per 100,000 people, which of the following is an example of extrapolation? a. Predict Y when cigarette consumption is 3,500 cigarettes per person. b. Predict Y when cigarette consumption is 3,800 cigarettes per person. c. Predict Y when cigarette consumption is 4,600 cigarettes per person.
Q3: From the following data: 2 5 y 5 4 6 3 1) Draw scatter plot. 2) Determine the regression line y = a + b x. 3) Predict the value of y for the value of x = 4.6. 4) Calculate the correlation coefficient. 4 8 3 5
Consider the following table of data. 2 3 4 y 1 1 1 1.1 (a) Calculate the correlation coefficient. (b) Sketch a graph of the data. (c) Based on how closely the data fits a straight line, is your answer to part (a) surprising? Discuss the extent to which the correlation coefficient describes how well the data fit a horizontal line.
For the following data: a. Find the regression equation for predicting Y from X. b. Calculate the Pearson correlation for these data. Use r2 and SS_Y to compute SSresidual and the standard error of estimate for the equation. Y 3 3 4 3 7 10 5 9.
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, ŷ = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.05 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperature (°F) Average Temperatures and Snow Accumulations 42 31 24 45 38 18 33 21 25 9 12 27 7 15 22 30 13 20 37 Snow Accumulation (in.) 8
The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression eqation, using the first variable (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140. Use a significance level of x Systolic Diastolic 116 82 124 88 112 72 144 95 138 96 112 76 145 88 124 76 130 90 129 94 1)Find the correlation coefficient. 2)State the appropriate critical r value to use to test the claim that the correlation between systolic blood pressure and diastolic blood pressure is significantly different from 0 3)The correlation between diastolic blood pressure and systolic blood pressure is: significant, not significant, weak, none 4)The best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140 is closest to 1pts

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS