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= A psychologist was interested in whether the amount of news people watch (minutes per day) predicts how depressed they

Posted: Mon Nov 15, 2021 10:54 am
by answerhappygod
A Psychologist Was Interested In Whether The Amount Of News People Watch Minutes Per Day Predicts How Depressed They 1
A Psychologist Was Interested In Whether The Amount Of News People Watch Minutes Per Day Predicts How Depressed They 1 (249.1 KiB) Viewed 147 times
= A psychologist was interested in whether the amount of news people watch (minutes per day) predicts how depressed they are (from 0 = not depressed to 7 = very depressed). What does the standardized beta tell us in the output? Coefficients Standardized Coefficients Beta Collinearity Statistics Tolerance Unstandardized Coefficients Model B Std. Error 1 (Constant) 7.241 .784 News Exposure -.026 .012 a. Dependent Variable: Depression VIF 95.0% Confidence Interval for B Lower Bound Upper Bound 5.681 8.801 -.050 -.001 t 9.230 -2.099 Sig. .000 .039 -.224 1.000 1.000 Bootstrap for Coefficients Bootstrap Sig. (2- 95% Confidence Interval Model B Bias Std. Error tailed) Lower Upper 1 (Constant) 7.241 -.023 .873 .001 5.652 9.077 News Exposure -.026 .000 .014 .098 -.055 .000 a. Unless otherwise noted, bootstrap results are based on 1000 bootstrap samples a. As news exposure decreases by 0.224 standard deviations, depression increases by 1 standard deviation. b. As news exposure increases by 1 standard deviation, depression decreases by 0.224 of a standard deviation. As news exposure increases by 1 minute, depression decreases by 0.224 units.d. Your fourth answer Oc. option goes here. d. As news exposure decreases by 0.224 minutes, depression increases by 1 unit.

A consumer researcher was interested in what factors influence people's fear responses to horror films. She measured gender and how much a person is prone to believe in things that are not real (fantasy proneness). Fear responses were measured too. In this table, what does the value 847.685 represent? ANOVA F 9.419 Sig. .003" 7.475 .001 Sum of Model Squares df Mean Square 1 Regression 103.457 1 103.457 Residual 900.675 82 10.984 Total 1004.132 83 2 Regression 156.448 2 78.224 Residual 847.685 81 10.465 Total 1004.132 83 a. Dependent Variable: Fear after Horror Film b. Predictors: (Constant), Gender c. Predictors: (Constant), Gender, Fantasy Proneness a. The improvement in prediction of fear resulting from including both gender and fantasy proneness as predictors in the model b. The improvement in prediction of fear resulting from adding fantasy proneness to the model The total error in predicting fear scores when both gender and fantasy proneness are included as predictors in the model C d. The reduction in the error in predicting fear scores when fantasy proneness is added to the model

A psychologist was interested in whether the amount of news people watch predicts how depressed they are. In this table, what does the value 3.030 represent? ANOVA Sum of Model Squares df Mean Square F Sig. 1 Regression 3.030 1 3.030 4.404 .0396 Residual 57.115 83 .688 Total 60.145 84 a. Dependent Variable: Depression b. Predictors: (Constant), News Exposure a. The improvement in the prediction of depression by fitting the model The ratio of how much the prediction of depression has improved by fitting the model, compared to how Ob. much error still remains The ratio of how much error there is in the model, compared to how much variability there is in depression C. Scores d. The proportion of variance in depression explained by news exposure

Dependent variable: Agression 3 O O 8 2 O 0 O O 0 1 0 0 o OO O Regression Standardized Predicted Value 0 O 08 DoDo 08 90 ca & O . o ם ם -1 på Bo 7 O D 08 GO O O -2 -3 O -3 -2 -1 O 1 2 Regression Standardized Residual a. Heteroscedasticity. b. Regression assumptions that have been met c. Non-linearity d. Heteroscedasticity and non-linearity