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.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text: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?
Regression
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
Model Summary
Adjusted R
Std. Error of the
Model
R
R Square
Square
Estimate
1
.606°
368
.345
.97245
results.
a. Predictors: (Constant), Socialmedia.
Scatterplot of Self-improvement vs Social Media Hours
R Linear -0.360
7.00-
Coefficients
Standardized
Unstandardized Coefficients
Coefficients
6.00
Model
B
Std. Error
Beta
t
Sig.
(Constant)
5.705
.398
14.324
.000
Socialmedia
-.863
500-
.214
-.606
-4.034
.000
a. Dependent Variable: ŞelfimprovementHRS
4 00
o y-5.7-0.86 o
Part C Conclusion:
300-
Explanatory variable: Social media (explanatory variables are independent and has an affect on the
response variable)
Response variable: selfimprovementHRS
200-
00
1.00
2.00
3.00
4.00
Socialmedia
Correlation coefficient: - 0.606
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
Correlations
Selfimntovemeot
Y: 5.705
HRS
Socialmedia
Y-intercept interpretation: on average, if social media is at 0, self-improvement will be at 5.705
SefimprovementHRS
Pearson Correlation
1
-.606"
Future prediction: If social media decreases, then self-improvement should increase.
SelfimprovementHRS
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