Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. μ The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \text { R-Sq }=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ Suppose we wish use the ANOVA F test to test the following hypotheses: H0: β1 = β2 = β3 = 0 Hα: At least one of β1 or β2 or β3 is not 0 What is the value of the F statistic for these hypotheses?

A) 2.14 B) 3.55 C) 4.58 D) 5.42 A) 2.14 B) 3.55 C) 4.58 D) 5.42 B

Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall }{ }^{*} \text { stress } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \text { R-Sq }=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ The interaction term in this model is statistically significant at the 0.05 level. Given this and the scatterplot provided, what should you conclude?

A) The effect of the number of pictures recalled on brainwave relative amplitude is substantially different when subjects are exposed to a stressful stimulus versus a neutral stimulus. B) The effect of the number of pictures recalled on brainwave relative amplitude is essentially the same when subjects are exposed to a stressful stimulus or a neutral stimulus. C) The number of pictures recalled does not affect brainwave relative amplitude at all. D) The type of stimulus received does not affect brainwave relative amplitude at all. A) The effect of the number of pictures recalled on brainwave relative amplitude is substantially different when subjects are exposed to a stressful stimulus versus a neutral stimulus. B) The effect of the number of pictures recalled on brainwave relative amplitude is essentially the same when subjects are exposed to a stressful stimulus or a neutral stimulus. C) The number of pictures recalled does not affect brainwave relative amplitude at all. D) The type of stimulus received does not affect brainwave relative amplitude at all. A

Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall }^{*} \text { stress } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \text { R-Sq }=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ Based on the software output provided, what is the equation of the regression model when a stressful stimulus is received (indicator variable stress = 1)?

A) amplitude = 0.533 - 0.114 recall B) amplitude = 0.533 + 0.320 recall C) amplitude = 4.795 - 0.114 recall D) amplitude = 4.795 + 0.320 recall A) amplitude = 0.533 - 0.114 recall B) amplitude = 0.533 + 0.320 recall C) amplitude = 4.795 - 0.114 recall D) amplitude = 4.795 + 0.320 recall B

Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall }{ }^{*} \text { stress } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \text { R-Sq }=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ What is a 95% confidence interval for β2, the coefficient of the indicator variable stress in this model?

A) -4.26 ± 2.21 B) -4.26 ± 4.47 C) 2.21 ± 1.93 D) 2.21 ± 4.47 A) -4.26 ± 2.21 B) -4.26 ± 4.47 C) 2.21 ± 1.93 D) 2.21 ± 4.47

Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. μ The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall* } \text { stress } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \text { R-Sq }=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ Based on the software output provided, what is the equation for the multiple regression model?

A) amplitude = 4.795 - 0.114 recall - 4.262 stress + 0.434 recall*stress B) amplitude = 1.329 + 0.107 recall + 2.205 stress + 0.168 recall*stress C) amplitude = 4.795 recall - 0.114 stress - 4.262 recall*stress + 0.434 D) amplitude = 1.329 recall + 0.107 stress + 2.205 recall*stress + 0.168 A) amplitude = 4.795 - 0.114 recall - 4.262 stress + 0.434 recall*stress B) amplitude = 1.329 + 0.107 recall + 2.205 stress + 0.168 recall*stress C) amplitude = 4.795 recall - 0.114 stress - 4.262 recall*stress + 0.434 D) amplitude = 1.329 recall + 0.107 stress + 2.205 recall*stress + 0.168

Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. μ The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall }{ }^{*} \text { stress } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \text { R-Sq }=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ Here are the residual plots for this regression model: Based on the study description, the scatterplot, and the residual plots, what should you conclude?

A) The assumption of Normality is not met but the other assumptions are met. B) The assumption of constant variance is not met but the other assumptions are met. C) The assumption of independence is not met but the other assumptions are met. D) All of the assumptions for regression inference are met. A) The assumption of Normality is not met but the other assumptions are met. B) The assumption of constant variance is not met but the other assumptions are met. C) The assumption of independence is not met but the other assumptions are met. D) All of the assumptions for regression inference are met.

Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. μ The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall } \text { stress } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \mathrm{R}-\mathrm{Sq}=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ What is the percent of variation in brainwave relative amplitude that can be explained by the regression model?

A) 23% B) 48% C) 77% D) 95% A) 23% B) 48% C) 77% D) 95%

Researchers investigated the effects of acute stress on emotional picture processing and recall by randomly assigning 40 adult males to receive either a stressful cold stimulus or a neutral warm stimulus before viewing pictures. The researchers computed the relative brainwave amplitude (in microvolts, μV) for each subject viewing unpleasant versus neutral pictures. They also recorded how many pictures the subjects were able to recall 24 hours later. The data are displayed in the following scatterplot. μ The following model is proposed for predicting the brainwave relative amplitude ("amplitude") from the number of images recalled ("recall"), the indicator variable reflecting the nature of the stimulus ("stress"), and an interaction term ("recall*stress"): Amplitudei = β0 + β1 (recalli) + β2 (stressi) + β3 (recall*stressi) + εi Where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the sample of 40 adult males. The following results summarize the least-squares regression fit of this model: $\begin{array}{lrr} \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 4.795 & 1.329 \\ \text { recall } & -0.1139 & 0.1069 \\ \text { stress } & -4.262 & 2.205 \\ \text { recall }{ }^{\star} \text { stress } & 0.4337 & 0.1677 \\ \mathrm{~S}=2.13946 & \text { R-Sq }=22.8 \% & \end{array}$ $\begin{array}{l} \text { Analysis of Variance }\\ \begin{array}{lrrr} \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regression } & 3 & 48.788 & 16.263 \\ \text { Residual Error } & 36 & 164.783 & 4.577 \\ \text { Total } & 39 & 213.571 & \end{array} \end{array}$ Suppose we wish use the ANOVA F test to test the following hypotheses: H0: β1 = β2 = β3 = 0 Hα: At least one of β1 or β2 or β3 is not 0 What is the P-value of the test?

A) Greater than 0.10 B) Between 0.05 and 0.10 C) Between 0.01 and 0.05 D) Less than 0.01 A) Greater than 0.10 B) Between 0.05 and 0.10 C) Between 0.01 and 0.05 D) Less than 0.01

A study examined the effect of body weight and origin (aviary or wild) on the length of the R1 central tail feather in male finches. The following model is proposed for predicting the length of the R1 feather from the bird's weight (in grams) and origin (aviary = 0, wild = 1): R1Lengthi = β0 + β1 (BodyWeighti) + β2 (Aviary0Wild1i) + εi Where the deviations εi were assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to a sample of 25 male finches. Using software, we obtained the following output: $\begin{array} { l r r } \text { Predictor } & \text { Coef } & \text { SE Coef } \\ \text { Constant } & 35.79 & 16.95 \\ \text { BodyWeight } & 2.826 & 1.030 \\ \text { Aviary0Wild1 } & - 10.453 & 4.996 \end{array}$ Predicted Values for New Observations $\begin{array} { r r r c c } \text { NewObs } & \text { Fit } & \text { SE Fit } & 95 \% \text { CI } & 95 \% \text { PI } \\ 1 & 76.22 & 4.32 & ( 67.26,85.17 ) & ( 54.35,98.09 ) \\ 2 & 86.67 & 2.75 & ( 80.96,92.38 ) & ( 65.91,107.43 ) \end{array}$ Values of Predictors for New Observations $\begin{array} { c r r } \text { NewObs } & \text { BodyWeight } & \text { Aviary0Wild1 } \\ 1 & 18.0 & 1.0 \\ 2 & 18.0 & 0.0 \end{array}$ What is the best description of the interval (65.91, 107.43)?

A) A confidence interval for the mean tail-feather length of all male finches that weigh 18 g and are raised in an aviary B) A confidence interval for the mean tail-feather length of all male finches that weigh 18 g and are caught in the wild C) A prediction interval for the tail-feather length of one male finch that weighs 18 g and was raised in an aviary D) A prediction interval for the tail-feather length of one male finch that weighs 18 g and was caught in the wild A) A confidence interval for the mean tail-feather length of all male finches that weigh 18 g and are raised in an aviary B) A confidence interval for the mean tail-feather length of all male finches that weigh 18 g and are caught in the wild C) A prediction interval for the tail-feather length of one male finch that weighs 18 g and was raised in an aviary D) A prediction interval for the tail-feather length of one male finch that weighs 18 g and was caught in the wild