Question 3: How many hours a week do you spend on self-improvement? The graphs and charts below represent a survey using two qualitative variables. In the space provided below the last graph of question 3, please state a conclusion for these graphs. This should include answering the following. What are the explanatory and response variables? What is the correlation coefficient? Is there a linear correlation? Also state what the least squares regression line is and explain the meaning of the slope and y-intercept in this situation, State other things that you found interesting from this study. Make a prediction about what you expect to happen in the future based on your results. Regression Model Summary Adjusted R Std. Error of the Model R Square Estimate R Square 606 368 345 97245 a Predictors: (Constant), Socialmedia Scatterplot of Self-improvement vs Social Media Hours Lne0 Coefficients 700 Standardized Unstandardized Coefficients Coefficients .00 Model B Std. Error Beta Sig (Constant) 5.705 398 14.324 .000 Socialmedia -863 214 -606 -4.034 000 500 a. Dependent Variable: SelfimncavemeottiRS 400 Part C Conclusion: 300- Explanatory variable: Social media (explanatory variables are independent and has an affect on the response variable) Response variable: selfimprovementHRS Correlation coefficient: - 0.606 200 100 200 300 400 Socialmedia Linear relationship: Yes, because when social media increases, self-improvement decreases Slope: -0.863 Slope interpretation: 1 unit increase for hours spent on social media will decrease the self-improvement by 0.863 unit Y: 5.705 Correlations Selfaacovement HRS Socialmedia Y-intercept interpretation: on average, if social media is at 0, self-improvement will be at 5.705 SallmacaamanltiRS Pearson Corelation 1 -606 Future prediction: If social media decreases, then self-improvement should increase.
Question 3: How many hours a week do you spend on self-improvement? The graphs and charts below represent a survey using two qualitative variables. In the space provided below the last graph of question 3, please state a conclusion for these graphs. This should include answering the following. What are the explanatory and response variables? What is the correlation coefficient? Is there a linear correlation? Also state what the least squares regression line is and explain the meaning of the slope and y-intercept in this situation, State other things that you found interesting from this study. Make a prediction about what you expect to happen in the future based on your results. Regression Model Summary Adjusted R Std. Error of the Model R Square Estimate R Square 606 368 345 97245 a Predictors: (Constant), Socialmedia Scatterplot of Self-improvement vs Social Media Hours Lne0 Coefficients 700 Standardized Unstandardized Coefficients Coefficients .00 Model B Std. Error Beta Sig (Constant) 5.705 398 14.324 .000 Socialmedia -863 214 -606 -4.034 000 500 a. Dependent Variable: SelfimncavemeottiRS 400 Part C Conclusion: 300- Explanatory variable: Social media (explanatory variables are independent and has an affect on the response variable) Response variable: selfimprovementHRS Correlation coefficient: - 0.606 200 100 200 300 400 Socialmedia Linear relationship: Yes, because when social media increases, self-improvement decreases Slope: -0.863 Slope interpretation: 1 unit increase for hours spent on social media will decrease the self-improvement by 0.863 unit Y: 5.705 Correlations Selfaacovement HRS Socialmedia Y-intercept interpretation: on average, if social media is at 0, self-improvement will be at 5.705 SallmacaamanltiRS Pearson Corelation 1 -606 Future prediction: If social media decreases, then self-improvement should increase.
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section: Chapter Questions
Problem 8P: Noise and Intelligibility Audiologists study the intelligibility of spoken sentences under different...
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