If the coefficient of determination (R2) value is 0.99, it means the 99% of ____________ of the observed y-values of are explained by the __________ of the predicted y-values, and only 1% remains unexplained.
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If the coefficient of determination (R2) value is 0.99, it means the 99% of ____________ of the observed y-values of are explained by the __________ of the predicted y-values, and only 1% remains unexplained.
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- (a) A researcher reports that there is no consistent relationship between grade point average and the number of hours spent studying for college students. The correlation between grade point average and the number of hours studying is an example of a) a positive correlation.b) a negative correlation. c) a correlation near zero.d) a correlation near one. (b) A positive value for a correlation indicates _____. a) increases in X tend to be accompanied by increases in Yb) increases in X tend to be accompanied by decreases in Y c) a much stronger relationship than if the correlation were negatived) a much weaker relationship than if the correlation were negativeWhich of the following is true of the correlation r? It measures the strength of the straight-line relationship between two quantitative variables. It cannot be greater than 1 or less than 1. A correlation of +1 or –1 can only happen if there is a perfect straight-line relationship between two quantitative variables. Correlation is 0 only when there is no association between the variables. Correlation changes when the explanatory and response variables are switched.Which of the following statements is true? a. None of the suggested answers are correct b. If the coefficient of determination is 0.64, the correlation coefficient must be 0.80. c. An indication of a nonlinear relationship between two variables would be a coefficient of correlation equal to zero. d. The strength of the correlation between two variables depends on the sign of the coefficient of correlation. e. The t-test for the true slope ?1=0 is identical to the t-test for the true correlation ?=0 only for large samples.
- Which of the following is not one of the uses of a scatter plot and regression line a. to estimate the average y at a specific value of x. b. All three are uses of the scatterplot and regression line c. to determine if a change in x causes a change in y d. to predict y at a specific value of x.8.6 Cherry Trees: Timber yield is approximately equal to the volume of a tree, however, this value is difficult to measure without first cutting the tree down. Instead, other variables, such as height and diameter, may be used to predict a tree's volume and yield. Researchers wanting to understand the relationship between these variables for black cherry trees collected data from 31 such trees in the Allegheny National Forest, Pennsylvania. Height is measured in feet, diameter in inches (at 54 inches above ground), and volume in cubic feet. (Hand, 1994) Estimate Std. Error t value P(>|t|) (Intercept) -57.99 8.64 -6.71 0.00 height 0.34 0.13 2.61 0.01 diameter 4.71 0.26 17.82 0.00What is indicated by a Pearson correlation of r = +1.00 between X and Y? Question 1 options: Each time X increases, there is a perfectly predictable increase in Y Every change in X causes a change in Y Every increase in X causes an increase in Y All of the other 3 choices occur with a correlation of +1.00.
- The Transylvania hypothesis claims that the full moon has an effect on health-related behavior. A study investigating this effect found a significant relationship between the phase of the moon and the (x-4) + 100 where y is the number of consultations as a percentage of the daily mean and x is the days since the last full 15.12 number of general practice consultations nationwide, given by y = 1.9 cos moon. a. What is the period of this function? What is the significance of this period? The period is days. (Round to two decimal places as needed.) Choose the correct meaning of the period p in the context of the problem. The x-distance between the maximum and the minimum of the graph is p. Every p days there is a full moon. There were p% more consultations when there was a full moon. The average number of daily consultations is p. b. If there was a full moon on April 7, on what day in April does this formula predict the maximum number of consultations? What percent increase would be…Which of the following statements concerning the linear correlation coefficient are always true? I: The value of the linear correlation coefficient always lies between−1 and 1. II: If the linear correlation coefficient for two variables is zero, then there is a strong linear relationship between the variables. III: If the slope of the regression line is negative, then the linear correlation coefficient could be either negative or positive. IV: A linear correlation coefficient of −0.82 suggests a stronger linear relationship than a linear correlation coefficient of 0.62.Question 7.2.9 A chemist has a 5-gallon sample of river water taken downstream from the outflow of a chemical plant. He is concerned about the concentration, c (in parts per million), of a certain toxic substance in the water. He wants to take several measurements, find the mean concentration of the toxic substance for this sample, and have a 95% chance of being within 5 parts per million of the true mean value of c. If the concentration of the toxic substance in all measurements is normally distributed with o = 12.50 parts per million, what is the minimum integer number nof measurements needed to achieve this goal?
- 21. Which of the following statements is true regarding the sources of variation present in an analysis of regression? SSy is partitioned into variation explained by the regression model and residual variation. If most of the variability in Y is associated with residual variation, then X predicts Y. There are three sources of variation in an analysis of regression: regression variance, residual variance, and error variance. Regression variation measures variability in X, whereas residual variation measures variability in Y.Example3. Calculate Pearson's coefficient of skewness for the following data: X: 2 3 4 6. 7 f:1 3 13 8. 3n 19 As a general rule it can be stated that: A. Association and causation are two terms that mean the same thing as regression-correlation analysis. B. Correlation shows association but does not prove causation. C. Regression analysis shows causation and correlation analysis proves causation. D. All of the above are correct.
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