A researcher determines that the correlation between number of siblings X and parental satisfaction measured on a 10 point scale Y is +0.53 The regression model was determined to be Y=4.6 +1.2X. For every additional sibling that a person has their parental satisfaction rating will increase by ——-points How many points?

A researcher determines that the correlation between number of siblings X and parental satisfaction measured on a 10 point scale Y is +0.53 The regression model was determined to be Y=4.6 +1.2X. For every additional sibling that a person has their parental satisfaction rating will increase by ——-points How many points?

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 tab = The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, bo + bx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. 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. Answer How to enter your answer (opens in new window) esc Step 3 of 6: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable . Google Play Store alt 1…
From a regression equation r2= 0.39 and the slope = -2.8 What is the linear correlation coefficient r?
The equation of a regression line, unlike the correlation, depends on the units we use to measure the explanatory and response variables. Here is the data on percent body fat and preferred amount of salt. Preferred amountof salt x 0.2 0.3 0.4 0.5 0.6 0.8 1.1 Percent body fat y 21 30 23 30 39 24 31 In calculating the preferred amount of salt, the weight of the salt was in milligrams. (a) Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in milligrams. (Round your answers to one decimal place.) ŷ = + x (b) A mad scientist decides to measure weight in tenths of milligrams. The same data in these units are as follows. Preferred amountof salt x 2 3 4 5 6 8 11 Percent body fat y 21 30 23 30 39 24 31 Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in tenths of milligrams. (Round your intercept to one decimal place and your slope to two…
A regression modrel examining the amount of distance a long-ddistance runner runs (in miles) to predict the amount of fluid the runner drinks (ounces0 has a slope of 4.6. Which interpretation is appropiate? The correlation is needed to interpret this value. Arunner drinks minimum of 4.6 oz. We predict 4.6 miles for every ounce that drunk. We predict for every mile run, the runner drinks 4.6 more ounces. Each mile adds 4.6 more ounces.
Solve attached photo.
The coefficient of correlation in a simple regression analysis is = -0.6. The coefficient of determination for this regression would be 0.36 - 0.36 0.6 0.13 O 0.6 or + 0.6
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.271 b=39.101 ²-0.407044 r=-0.638 Assume the correlation is significant, and use this to predict the number of situps a person who watches 14 hours of TV can do (to one decimal place) Aft
A pediatrician wants to determine the relation that exists between a child's height (x) and head circumference (y). She randomly selects 11 children from her practice and measures their height and head circumference in inches. She finds that the correlation is 0.477 and the regression equation is y = 0.149x + 8.15 What proportion of the variation in head circumference can be explained by the variation in the values of height? % Report answer as a percentage accurate to one decimal place.
For a two-variable linear regression, if the sample correlation between the depen- dent and independent variables is –0.7, then the independent variable explains 49% of the variation in the dependent variable. Is this statement true? Explain your answer.
I’m taking a statistics and probability class. Please get this correct because I want to learn. I have gotten wrong answers on here before
I was wondering specifically about part D and how to interpret my findings.
A regression analysis was performed to predict weight (y, in kg) using height (x, in cm) among 150 children. The coefficient of determination was . Which of the following is a valid interpretation? a. For each 1-cm increase in height, weight tends to increase by about 0.32 kg b. There is no association between weight and height c. Height accounts for about 32% of the total variability in weight d. The correlation between weight and height is about 0.32