A researcher calculates the coefficient of determination r2 = 0.41. Which is the BEST statement following the finding? a. There are 41% variation in y is explained by the variable x b. The strength of the relationship between variable x and variable y is modest and positive at 41%. c. 41% of y is not accounted for by the variation of x. d. The relationship between variable x and variable y is positive at 41%.

A researcher calculates the coefficient of determination r2 = 0.41. Which is the BEST statement following the finding? a. There are 41% variation in y is explained by the variable x b. The strength of the relationship between variable x and variable y is modest and positive at 41%. c. 41% of y is not accounted for by the variation of x. d. The relationship between variable x and variable y is positive at 41%.

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

See similar textbooks

Similar questions

aChen -. M Gmail YouTube Maps oscar - Google D... Translate New Tab ece Gler 2/6 100% SID: 2. A researcher is studying the relationship between various properties of wine and their taste characteristics. The histogram below shows the amount of residual sugar (sugar left after fermentation) in a collection of wines. However, one of the bars, between 3 and 5 grams per liter, is missing. 50 (47.9) (38.7) 30 10 (0.1) (0.92) (0.1) 2 10 15 Residual sugar (grams/liter) Calculate the height of the missing bar and draw it in. (Show your work below, and indicate the numerical value in parentheses above the bar.) % per gramlter
Assume the correlation coefficient between advertising dollars spent and sales is .78. How much of the variability in sales is explained by the relationship between sales and advertising dollars? a. 39.16% b. 60.84% c. 78% d. 22%
The correlation between hours of sleep and hours of study is r = 0.14. (a) Calculate r². (Round your answer to four decimal places.) ,2 = = (b) Choose a sentence that interprets value r². 1.96% of the variation in hours of sleep is not explained by hours of study. Variation in hours of study explains about 1.96% of the observed variation in hours of sleep. 1.96% of the variation in hours of sleep is not explained by the variation in hours of study. Hours of study explains about 1.96% of the observed variation in hours of sleep.
Explain in words and in percentages what it would mean if you found that for variables x and y, the coefficient of determination r squared = 0.832
Listed below are amounts (in millions of dollars) collected from parking meters by Brinks. Find coefficient of variation The data were provided by the attorney for New York City, and they are listed on the DASL Web site. Use s= 2.137 Collection contractor was Brinks: 71 66 72 69 68 69 Group of answer choices 3.1% 11.5% 1.5% 4.1%
Use the Women's Earnings scatterplot below to answer the questions. Women's Earnings as a Percentage of Men's Earnings 90 80 70 60 50 y = 0.617x - 1156.3 40 R² = 0.9302 à 30 20 10 1979 1984 1989 1994 1999 2004 2009 Year What is the independent variable and what does it represent? Year Percentage Income in dollars CO2 Percentage
Calculate the coefficient of variation between X and Y from the following data: 3 4. 6. Y 9. 10 12 11 13 14 16 重5
Use the following to answer the question: ˆy=−4x+10.3 with R2=35%. Which best describes the correlation? Weak negative linear relationship Weak positive linear relationship Moderate negative linear relationship No linear relationship Moderate positive linear relationship
A fire insurance company wants to relate the amount of fire damage in major residential fires to the distance between the residence and the nearest fire station. The study was conducted in a large suburb of a major city; a sample of fifteen recent fires in the suburb was selected. The amount of damage, y (£000), and the distance, r (km), between the fire and the nearest fire station are given in the following table. 3.4 1.8 4.6 2.3 3.1 5.5 0.7 3.0 y 26.2 17.8 31.3 23.1 27.5 36.0 2.1 y 19.6 31.3 24.0 17.3 43.2 36.4 26.1 14.1 22.3 2.6 4.3 1.1 6.1 4.8 3.8 (a) Fit a simple linear regression model to these data. Check if the residual plots give any reason to doubt the usual assumptions of the model. (b) Write a short report giving your conclusions. You do not need to upload the output from R. Include a possible interpretation of the intercept and slope parameters.
Q1. A study was conducted to investigate the relationship between premature birth and mental development at 12 months. The infant's birth weight was used as an index of prematurity. At age 12 months, the child's mental development was recorded. The results are shown below (the weights are in pounds): Birth 4 6 7 8 Weight(x) Developmental 85 Quotients(y) 88 87 94 96 Summary: n = 5, £x=30, £x² = 190, Ey= 450, Ey² = 40590, Exy = 2728 . a. Find the least square prediction equation, y on x. b. Obtain a 95% confidence interval for the average value of y when x 6.5 (i.e., a C.I. for E(y|x= 6.5)). c. Obtain the coefficient of correlation (r) and interpret the result. d. Test the hypothesis that H, :p= 0 vs. H, : p0. Use a =0.05.
Solve.
Use the following to answer the question: ŷ : = −3x + 13.9 with R² = 34%. Which best describes the correlation? No linear relationship Weak positive linear relationship O Moderate negative linear relationship O Moderate positive linear relationship Weak negative linear relationship