Q&A Hero

Q: 1+ When I want to make a prediction but don"t have the value of X on which to base that prediction, my best estimate is a) the value that I calculate with a regression equation. b) the smallest value of Y. c) the mean of Y. d) There is no good prediction.

Q: 66 Briefly describe the difference between the standardized beta coefficient and the unstandardized b

Q: 65 Given the following data, do you believe the regression equation would be a reliable way to predict values of Y. Explain your answer.

Q: 64 Given the data in the previous table: a) What is the slope of the regression line? b) What does the value of the slope mean here? c) Is the slope significantly different from 0?

Q: 63 Answer the following questions based on the regression data in the previous table.a) What percent of variability in behavior problems is accounted for by anger?b) What percent of variability in behavior problems independent of anger?

Q: 62 Write a sentence interpreting the regression data in the following table.Dependent variable: Child Behavior Problem Score

Q: 61 Given this regression equation, = .3 X + 25, estimate the values of X given the following values of Y.a) Y = 0b) Y = 25c) Y = -30

Q: 60 Calculate SSerror for the previous data. Explain how you did it.

Q: 59 Calculate the residuals for the previous data. Explain how you did it.

Q: 58 Given the following values, calculate the regression equation.Age of car (years) Mileage 1.00 40.00 1.00 25.00 2.00 37.00 2.00 35.00 3.00 36.00 3.00 35.00 4.00 32.00 5.00 30.00 6.00 25.00 10.00 20.00

Q: 57 Given this regression equation, = .75 X + 5, estimate Y for the following values of X.a) X = 0b) X = 1c) X = -3d) X = 75

Q: 56 Residual refers to the error of prediction.

Q: 55 Using a regression equation to predict a value will always lead to highly accurate predictions.

Q: 54 When there is only one predictor variable in a regression, beta (regression coefficient) = r (correlation coefficient).

Q: 53 In a regression using standardized data, to predict health symptoms from stress, the beta = .5. This means that for every 1 point increase in stress there is half a point increase in symptoms.

Q: 52 The regression equation can be used to estimate the value of the criterion variable based on knowing the value of the predictor variable.

Q: 51 Regression is typically used to test cause-effect relationships.

Q: 50 If the association between warm parenting practices and self-esteem is .50, then 75% of the variability in self-esteem is independent of warm parenting practices.

Q: 49 If the correlation between smoking and lung cancer is .50, smoking accounts for 50% of the variability in lung cancer.

Q: 48 Regression can be used to examine both linear and curvilinear relationships.

Q: 47 Regression is only appropriate for predicting a criterion variable from one predictor variable.

Q: 46 The intercept of a regression line is a) the value of when X=0. b) always greater than 0. c) significant when the correlation is significant. d) never informative.

Q: 45 A regression line is a) a line of covariance. b) a correlation matrix. c) the best fit straight line. d) the equal to a correlation line.

Q: 44 When one refers to the degree that variable A changes as variable B changes they are referring to a) variance. b) regression. c) covariance. d) habituation.

Q: 43 A regression analysis of hours spent exercising and ounces of weight loss had a slope of 3. We would predict that a) for every 1 hour of exercise, a person would lose 3 ounces of weight. b) for every ounce lost, a person has to exercise for 7 hours. c) every hour of exercise would have no effect on weight. d) The slope cannot be used to make predictions, you need the intercept.

Q: 42+ An example in the text hypothesized that 4% of the variability in life expectancy was accounted for by variability in smoking behavior. The values of r and r2, respectively, are equal to a) .20 and .04. b) .04 and .16. c) .04 and .20. d) More information is needed.

Q: 41 In a scatterplot, an outlier is one that a) is far to the left of the display. b) is in the center of the display. c) is far from the regression line. d) is the largest value of Y.

Q: 40 If you drop a pencil randomly on a scatterplot, what aspect are you changing as you rotate the pencil about the point where it crosses the Y axis? a) the slope. b) the intercept. c) the correlation. d) the residual.

Q: 39 If you drop a pencil randomly on a scatterplot, what aspect are you changing as you move the pencil vertically on the page without rotating it? a) the slope. b) the intercept. c) the correlation. d) the residual.

Q: 38 If the slope is significant we know that a) the intercept is not significant. b) the intercept is significant. c) there is a strong relationship between the two variables. d) none of the above

Q: 37 A significant slope means that a) the slope is positive. b) there is a significant relationship between X and Y in the population. c) the slope is not equal to 0 in the population. d) both b and c

Q: 36+ If the correlation between X and Y is significant, that tells us a) that the slope is significant. b) that the intercept is significant. c) that X causes Y. d) nothing about the regression equation.

Q: 35+ Which of the following does NOT belong with the rest? a) variance attributable to b) variance associated with c) variance predictable from d) variance caused by

Q: 34+ An important thing about r2 is that it represents a measure of a) causal relationships. b) accountable variability. c) the correlation. d) statistical significance.

Q: 33 If we want to specify the percentage of the overall variability in life expectancy attributable to variability in smoking behavior, the statistic we want to look at is

Q: 32 The notation SS stands for a) simply sensational. b) statistical significance. c) squared sums. d) sum of squares.

Q: 31+ If the correlation between a body image measure and an eating disorders measure is .50, we can conclude that a) body image has very little to do with eating disorders. b) 50% of the variability in the eating disorders scales is associated with variability in body image. c) one quarter of the variability in the eating disorders scores is associated with variability in body image. d) overweight people eat too much.

Q: 30 When we use a regression equation to make a prediction, the errors that we make are often referred to as a) residuals. b) predictions. c) . d) standard errors.

Q: 29 We can think of the standard error of estimate as a) the standard deviation of the errors that we make when using the regression equation. b) the standard deviation of Y. c) the variance of the errors that we would make when using the regression equation. d) the variance of X.

Q: 28 The standard error of estimate is denoted by a) b) c) d) none of the above

Q: 27+ The standard error of estimate is given by a) b) c) d) none of the above

Q: 26 If we do know X, our measure of error isa) the standard deviation of Y.b) the standard deviation of X.c) the standard error of estimate.d) the standardized residual.

Q: 25 If we do not know X, our measure of error in predicting Y is a) the standard deviation of Y. b) the standard deviation of X. c) the standard error of estimate. d) the standardized residual.

Q: 24 The notation Y - is referred to as a) error. b) deviation. c) residual. d) all of the above

Q: 23 The regression line always passes through the point a) 0, 0 b) , c) , 0 d) a, b

Q: 22+ If you want to plot the regression line, after having found the regression equation, you need to calculate for _______ value(s) of X. a) all possible b) one c) a minimum of two d) at least five

Q: 21 If data with only one predictor variable were standardized, the slope would equal a) r b) b c) a d)

Q: 71 Give an example of a: a) positive relationship b) negative relationship c) curvilinear relationship

Q: 70 Calculate and interpret the correlation between the following variables. X Y5.00 2.005.00 1.005.00 2.004.00 2.004.00 3.003.00 4.003.00 4.002.00 3.002.00 2.00

Q: 69 Give an example of a relationship that is effected by restricted range. Explain your example clearly.

Q: 68 Give an example of a relationship that may be effected by the heterogeneity of a sample. Explain your example clearly.

Q: 67 Describe the following graph.

Q: 66 Calculate the correlation coefficient for the previous data. Is it significant? Write a brief statement to explain the results.

Q: 65 Make a scatterplot of the following data and draw a line of best fit.Self-esteem Grades10.00 83.009.00 97.008.00 92.007.00 83.007.00 93.006.00 97.006.00 75.006.00 68.005.00 59.004.00 65.00

Q: 64 Write a brief paragraph to summarize the data displayed in the following table. 1 2 3 41. Wives' marital aggression - -.25* .45** -.35*2. Wives' marital satisfaction - -.30* .63***3. Husbands' marital aggression - -.30*4. Husbands' marital satisfaction -N = 100; * p < .05; ** p < .01; *** p < .001

Q: 63 Given the following pairs of data for mothers' and fathers' ratings of their child's behavior problems, what type of correlation would you expect? Explain your answer. Child Behavior Problem Score Mother's Rating Father's RatingFamily 1 60 70Family 2 55 50Family 3 30 30Family 4 45 40Family 5 95 100Family 6 75 75Family 7 50 55Family 8 100 90Family 9 25 30

Q: 62 Indicate the types of relationships illustrated in the following graphs. (e.g., positive, negative, no relationship, curvilinear).

Q: 61 Point biseral correlation is used when one of the variables is dichotomous.

Q: 60 Correlations are typically used to examine mean differences between groups.

Q: 59 A scatterplot can be used to visualize the degree of association between 2 variables.

Q: 58 A correlation of .65 between depression and anxiety suggests that people who are highly depressed are reasonably likely to be highly anxious.

Q: 57 Restricted range has no effect on correlation coefficients.

Q: 56 A researcher is predicting exam scores based on the amount of time spent studying. The criterion variable is exam scores.

Q: 55 The following is an example of a negative correlation. As height increase, so does foot size.

Q: 54 Correlation coefficients closer to 0 reflect strong relationships.

Q: 53 Correlation coefficients can range from -1 to 1.

Q: 52 Correlation cannot be used to test associations between two dichotomous variables.

Q: 51 We look at a number of states and record the number of auto fatalities last year and the state's maximum speed limit, trying to show that high speed limits are dangerous. This is an example of a) a correlational study. b) an experiment. c) a longitudinal study. d) naturalistic observation.

Q: 50 A significant correlation is one which a) has a great deal of meaning. b) means that the variables are not linearly independent. c) is very hard to find. d) is most likely to occur when the true correlation is near 0.

Q: 49 Which of the following pairs is most likely to be negatively correlated? a) height of husband and height of wife b) depression and stress c) intelligence and sociability d) volatile temper and success as an arbitrator

Q: 48 We want to demonstrate that a relationship exists between optimism and happiness. We are not concerned with trying to demonstrate that one variable causes the other. What type of statistical test can be use to see if a relationship exists between the variables? a) correlation b) independent samples t-test c) power analysis d) one way ANOVA

Q: 47 A correlation was computed between amount of exercise people do and people's overall happiness. A significant correlation was found, such that the more people exercise, the happier they are. What is the best conclusion to draw from this finding? a) Exercise leads people to be happy. b) We have proved that people should exercise more. c) A positive relationship exists between exercise and happiness. d) A negative relationship exists between exercise and happiness.

Q: 46 Professor Falls wants to determine if there is a relationship between frequent hearing of a startle stimulus and hearing loss. He ran a regression and obtained an r value of .60. Which of the following best summarizes what this result means? a) 60% of hearing loss is accounted for by frequency of hearing startle stimuli. b) 36% of the variability in hearing loss can be accounted for by variability in the hearing of startle stimuli. c) 36% of startle stimuli cause hearing loss. d) 60% of hearing loss is caused by startle stimuli.

Q: 45 Which of the following is the most accurate statement? a) Correlation shows causation. b) R squared or regression shows causation. c) Correlation and R squared or regression show causation. d) Neither correlation nor R squared nor regression show causation.

Q: 44 If the R squared between brain size and IQ is .09 then a) 9% of your IQ is accounted for by variability in brain size. b) 91% of your IQ is accounted for by variability in brain size. c) 9% of the variability in IQ is accounted for by variability in brain size. d) 91% of the variability in IQ is accounted for by variability in brain size.

Q: 43 The covariance measure is a) the probability of obtaining a significant result. b) the degree to which observations predict each other. c) the degree to which observations vary together. d) the probability of finding variance.

Q: 42 The correlation between amount of caffeine consumed and nervous behavior was found to be .30. What conclusion can be drawn from this finding? a) 30% of the of the variability in nervous behavior can be accounted for by variability in amount of caffeine consumed. b) 9% of the of the variability in nervous behavior can be accounted for by variability in amount of caffeine consumed. c) The correlation between nervous behavior and caffeine consumption is not significant d) Consuming caffeine causes nervousness.

Q: 41 Which r-value represents the strongest correlation? a) +.50 b) -.50 c) -.75 d) 1.65

Q: 40 A _______ refers to the degree of the relationship between two or more variables. a) regression b) correlation c) relative frequency d) matched sample

Q: 39 The covariance between height and running speed on the State College track team was equal to "28.21. This tells us that the a) relationship between height and speed is significant. b) relationship between height and speed is negative. c) the correlation is equal to the square root of "28.21. d) the correlation is equal to "28.21.