Hello, Can an expert please help me with this, I am struggling so hard and I really need a good grade. I only have an hour to finish this assignment and I will be trying to work on it as well, but I really need help. Thank you! QUESTION 1 In the equation Y’ = b0 + b1 X1 , Y’ is level of bordem and X is listening to statistics tutorials. If b1 = 0, what can be said about the relationship between bordem and listening to statistics tutorials? No relationship exists A positive relationship exists A negative relationship exists QUESTION 2 A Bivariate Regression was conducted to evaluate the predictive relationship between total years of schooling and annual income. The results of the regression model were F(1,88) = 4.1, p < .05. What can be concluded about these results? total years of schooling is a predictor of annual income. total years of schooling is not predictor of annual income. QUESTION 3 In bivariate regression, the difference between the obtained value and the predicted value of Y, is: Intercept (b0) Residual Slope (b1) QUESTION 4 What assumption is not required for a bivariate regression to be a valid description of the relationship between X and Y? Normality Curvilinearity Independent observations Linearity QUESTION 5 To evaluate whether average life satisfaction self reported by residents of 119 nations was predictable from each nations’ GNP per capita, a bivariate linear regression was performed. Because of the small N (only 19 countries), the distributions of scores on GNP and life satisfaction did not correspond closely to an ideal normal distribution. The results of the overall regression equation were, F(1, 117) = 4.04, p = .067. The equation to predict Life Satisfaction from GNP in raw score units was: Sat’ = 6.59 + 0.00 * GNP (the b slope coefficient was zero to at least three decimal places). The standardized equation to predict z scores on life satisfaction from z scores on GNP was zy’ = .44 * zx. Based on these results, what can the researcher conclude? The prediction model was not statistically significant at the conventional a = .05 level, each nations’ GNP per capita can not predicts average life satisfaction The prediction model was statistically significant at the conventional a = .05 level, each nations’ GNP per capita predicts average life satisfaction The prediction model was not statistically significant at the conventional a = .05 level, each nations’ GNP per capita predicts average life satisfaction The prediction model was statistically significant at the conventional a = .05 level, each nations’ GNP per capita can not predicts average life satisfaction QUESTION 6 Given Y’ = b0 + b1X. If b0 = 0 and b1 = 5 and X = 1, Y will equal: 2.5 5 10 20 QUESTION 7 The “line of best fit” that represents a straight line drawn through a scatterplot is called a: Covariance line Regression line Curvilinear line Coefficient line QUESTION 8 A Multiple Linear Regression analysis generates an equation to describe the statistical relationship between one or more predictor variables and the response variable. The t-statistic and its corresponding p-value for each term tests the null hypothesis that the coefficient is equal to zero. True False QUESTION 9 Table 1 provides a summary of the regression analysis for the variable predicting happiness. What can the researcher say about the variable sense of humor? The variable sense of humor does not contribute to the model for predicting happiness. The variable sense of humor does contribute to the model for predicting happiness. The variable sense of humor is not considered in the model for predicting happiness. QUESTION 10 In a correlation analysis, we examine scatterplots and "imagine" a line running through the datapoints that characterizes the general linear pattern of the data. We add a number, the Pearson correlation, which summarized how tightly clustered the points would be around that imaginary line. The process of placing a line onto the scatterplots is called ________. Correlation coiefficient Regression Beta F ratio QUESTION 11 A researcher wants to evaluate the null hypothesis that the amount of time college students’ spend online does not significantly predict their GPA. What is the best analysis to test this null hypothesis? Independent samples t test One-way ANOVA Pearson’s r Regression analysis Partial correlation analysis QUESTION 12 In a survey that included assessment of husband and wife heights, Hodges, Krech & Crutchfield (1975) reported the following results. Let’s treat wife height as the predictor (X) variable, and husband height as the outcome (Y) variable. Based on these values, what is the raw score predictive equation? Wife Height’ = 51.78 + .29*Wife height Husband Height’ = .29 + . 51.78*Wife height Wife Height’ = .29 + . 51.78*Husband height Husband Height’ = 51.78 + .29*Wife height QUESTION 13 In the equation, Y’ = b0 + b1X, b0 represents the: correlation between X and Y. slope coefficient of the regression line. intercept of the regression line with the Y axis. predicted value of Y from knowing X. QUESTION 14 r2 = .547 be interpreted as 54.7% of the variance in the outcome or criterion is explained by the predictor. True False QUESTION 15 In bivariate regression, the amount of change in Y for one-unit change in X is: Coiefficient Residual Slope Nove of the above