Which one of the following statements is true?The correlation coefficient is not affected by outliers.O In the context of correlation and regression, as long as the correlation is strong, it's okay to infer that theexplanatory variable causes the response variable.O The "P" in P-value stands for "practical."O The slope in a regression equation tells us what we predict y to be if x is equal to 0O It is not necessary to know the population size in order to compute the standard deviation of the samplingdistribution.

Here we want to know true statement.

Answered: Which one of the following statements…

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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In a scatterplot of two variables x and y, the correlation is positive. A particular point has an x value that is greater than the median but less than the 60th percentile. The regression effect means that we can immediately eliminate which of the following values as possible answers for the predicted percentile rank for y we get using the regression line? Check all that apply. Group of answer choices 60 50 65 45 55
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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.
Fill in the blanks. a. If predictor variable x1 has VIF equal to 5, then_______percent of the variation in the observed values of x1 is explained by the other predictor variables in the regression equation. b. If x1 and x2 are the only predictor variables in a regression equation and if the observed values of x1 and x2 have linear correlation coefficient equal to 0.7, then the VIF of x1 equals_______ c. A VIF of 10 indicates_______multicollinearity.
F 30
Measles and Mumps The data show the number of cases of measles and mumps for a recent -year period. + Measles Cases 48 145 64 57 217 Mumps Cases S07 432 1957 2553 379 Send data to Excel The correlation coefficient for the data is 7=-0.688 and a = 0.05. Should regression analysis be done? The regression analysis should not be done. O The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places. y =a= bx a = Given a year with 171 cases of measles, predict the expected number of cases of mumps for that year. Round your answer to at least one decimal place. The number of cases of mumps for that year is
Fill in the blanks. a. If predictor variable x1 has VIF equal to 5, then _______ percent of the variation in the observed values of x1 is explained by the other predictor variables in the regression equation. b. If x1 and x2 are the only predictor variables in a regression equation and if the observed values of x1 and x2 have linear correlation coefficient equal to 0.7, then the VIF of x1 equals ________. c. A VIF of 10 indicates _______. multicollinearity.
J 1 The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response why variable is city fuel consumption in miles/gallons. The predictor X variables are weight weight in pounds, DISP engine displacement leaders NHW Y Highway fuel consumption in miles/gallons. It's only one predictor X variable is used to predict the city fuel consumption, which single variable is best? Why? The best variable is (WT/HWY/DISP) because it has the best combination of (large/small) p-value, (answer) and (large/small) adjusted R^2 (answer) (type integers are decimals. Do not round)
Which one of the following statements is true? When predicting one quantitative variable based on another, the variable you are trying to predict should always go on the x-axis of the scatterplot. The intercept in a regression equation can never negative. The correlation coefficient has no units. A very strong relationship between variables can result in a value of r that is larger than 1. A correlation coefficient can only range in value from 0 to 1.
Chapter 11 Worksheet on Regression Name Consider an experiment designed to estimate the linear relationship between the percentage of a certain drug in the bloodstream of a subject and the length of time it takes the subject to react to a stimulus. In particular, the researchers want to predict reaction time based on the amount of drug in the bloodstream. Give a practical interpretation of the slope. Give a practical interpretation of the coefficient of correlation. What percentage of the sample variation in y can be explained by x in the simple linear model? REACTIO PERCENT N TIME 4.5 XOF IN 4 DRUG SECONDS 3.5 y=0.7x-0.1 R = 0.8167/ 2 2.5 3 4 1.5 1 0.5 r^2=.8167 From Excel
Direction: Answer the problem below. Show your solution. Mr. David runs to keep himself physically fit. He wants to know if there is a relationship between the time elapsed and the kilometers he ran. Kilometers ran Time (in minutes) (X) (Y) 1 10 90 2 10 60 3 16 150 4 16 90 5 21 160 21 180 a. Calculate the Pearson correlation coefficient and regression line based on the data below, b. Draw a scatter plot. Activate Windows N Go to PC settings to activate Windows.
Forest Fires and Acres Burned Numbers (in thousands) of forest fires over the year and the number (in hundred thousands) of acres burned for 7 recent years are shown. Number of fires x 58 47 84 62 57 72 69 Number of acres burned y 54 43 80 58 53 68 65 The correlation coefficient for the data is =r1 and =α0.05 . Should regression analysis be done? The regression analysis should not be done. The regression analysis should be done. Find the equation of the regression line. =y′+abx =a =b Find y′ when =x50 . =y′

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