The following results were obtained in the amalysis of data on yield of dry barkIn ounces Y and in vears X of 200 cinchona plants.ageYAverage9.216.5Standard Deviation0i - A. mi 2.1Y 4.2and correlation coefficient •84Fnd the two lines of regression and estimate the yield of dry bark of a plantof age 8 years.

Answered: Image /qna-images/answer/56cd9d2b-44a2-4221-938f-bd2fcf03e788.jpg

Answered: merollowing results were obtained 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

See similar textbooks

Similar questions

A paper† gave data on x = change in Body Mass Index (BMI in kilograms/meter2) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. JMP output for these data is shown below. A scatterplot titled "Bivariate Fit of Depression Score Schange by BMI Change" has 12 points and a line plotted on it. The horizontal axis is labeled "BMI change" and ranges from about −0.8 to about 1.8. The vertical axis is labeled "Depression score change" and ranges from about −2 to 20. The points are plotted from left to right in an upward, diagonal direction starting from the middle left of the diagram. The points are very scattered and are between approximately −0.5 to 1.5 on the horizontal axis and between approximately −1 to 18 on the vertical axis. A line with positive slope titled "Linear Fit" is drawn across the plot to approximate the trend of the points. The line enters the viewing window at about (−0.8, 3) and exits at…
Simple linear regression results: Dependent Variable: Heart. DiseaseIndependent Variable: BikingHeart. Disease = 18.115809 - 0.20845321 BikingSample size: 68R (correlation coefficient) = -0.94616452R-sq = 0.8952273Estimate of error standard deviation: 1.5273175 Correlation between Biking and Heart. Disease is: -0.94616452. Correlation between Smoking and Heart. Disease is: 0.32421. 1) State r 2 (i.e., the coefficient of determination) for “Biking” and “Heart.Disease” and explain what this value means in context of the data set.
Explain the concept of Asymptotic Distribution of the OLS Estimatorand t-Statistic in the multi regression model?
2 Please fast
Simple regression was employed to establish the effects of childhood exposure to lead. The effective sample size was about 122 subjects. The independent variable was the level of dentin lead (parts per million). Below are regressions using various dependent variables. (a) Calculate the t statistic for each slope, at significance level = 0.01. (Round your answers to 2 decimal places. Negative values should be indicated by a minus sign.) Dependent Variable R^2 Estimated Slope Standard Error t calculated p-value Highest grade achieved 0.028 -0.030 0.002 0.000 Reading grade equivalent 0.159 -0.033 0.034 0.334 Class Standing 0.052 -0.010 0.018 0.580 Absence from school 0.063 5.200 1.890 0.007 Grammatical reasoning 0.090 0.128 0.073 0.082 Vocabulary 0.149 -0.107 0.057 0.063 Hand-eye coordination 0.055 0.096 0.034 0.006 Reaction time 0.029 10.200 6.340 0.110 Minor antisocial behavior 0.025 -0.567 0.317 0.076
Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the neorest fire station. This information will be used in setting rates for insurance coverage. For o somple of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire domage, in thousands of dollars (y). ANOVA table Source Regression Residual SS df MS F 1,870.5782 1,870.5782 41.39 1,265.4934 3,136.0716 28 45.1962 Total 29 Regression output Standard Variables Coefficients Error t(df-28) Intercept Distance-X 13.76815 3.106 2.914 3.77es e. 5861 6.43 Click here for the Excel Data File a-1. Determine the regression equation. (Round your answers to 3 decimal places.) y3D X. a-2 Is there a direct or indirect relotionship between the distance from the fire station and the amount of fire damage? The relationship between distance and damage is b. How much domage would…
At the Thanksgiving break, I measured the correlation between the pre-class quiz grade and the average grade in the class for all 33 students in my stats classes. Below is the output from those results. Correlation Pearson correlation of PreClass and Grade = 0.705630 P-Value = < 0.0001 Regression Equation Grade = 0.24333 + 0.006369 PreClass (a) What is the slope of the regression equation line? (b) What does the slope of the line represent in this context? (c) What is the y-intercept of the regression equation line? (d) What does the y-intercept of the line represent in this context?
The amounts of 6 restaurant bills and the corresponding amounts of the tips are given in the below. Assume that bill amount is the explanatory variable and tip amount the response variable. Bill 32.98 49.72 52.44 64.30 97.34 88.01 Tip 4.50 5.28 7.00 7.70 16.00 10.00 (a) Find the correlation: r= (c) The regression equation is y^= . (d) If the amount of the bill is $90, the best prediction for the amount of the tip is $ .Note: Enter your answer as a number xx.xx (e) According to the regression equation, for every $5 increase in the bill, the tip should INCREASE or DECREASE) by $ .
Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model: SALES=a+BAGE+YMIL+SENG Where SALES= amount that a vehicle is sold for($000's), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained:
The attached results are for a multiple regression study of smartphone addiction (SSA-SV) proneness in relation to 1) Gender 2)Age 3) Anxiety (GAD-7). I just want to clarify that age is statistically significant with p = 0.006; is this correct? What's throwing me off is the notation "< .001" on the top line under the p category. I was under the impression that the p-value would need to be less than 0.001.
Do the following plots show 1. Constant variability 2. Nearly normal residuals 3. Independent observations for SLR (conditions for linear regression)
Please help me to interpret the attached chats. This is the ourput results of Regression (Scatter plots and Histograms) for Austria and United Kingdom

SEE MORE QUESTIONS

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