Q2. Based on the following Excel outputs, answer the following questions. (A). What does the scatter diagram indicate about the relationship between the two variables? (a) A negative linear relationship. (b) A positive linear relationship. (c) No relationship. (d) A nonlinear relationship. (e) Cannot be identified. (B). Use the estimated regression equation to predict the value of y when x=3.5 (a) 120.8954 (b) 23.7049 (c) 20.4191 (d) 14.8076 (e) None of the above
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Q2. Based on the following Excel outputs, answer the following questions.
(A). What does the
(a) A negative linear relationship.
(b) A positive linear relationship.
(c) No relationship.
(d) A nonlinear relationship.
(e) Cannot be identified.
(B). Use the estimated regression equation to predict the value of y when x=3.5
(a) 120.8954
(b) 23.7049
(c) 20.4191
(d) 14.8076
(e) None of the above
![Content
https://learn-us-east-1-prod-fleet02-xythos.content.blackboardcdn.com/5eb042...
Exam-3(10).html
SUMMARY OUTPUT
X Variable 1 Line Fit Plot
Regression Statistics
Multiple R
R Square
Adjusted R S 0.88363
0.952315
40
0.906904
30
Standard Errc 2.259372
> 20
Observations
10
I Predicted Y
ANOVA
4
6.
Significance F
1 198.9143 198.9143 38.96642 0.003356561
df
SS
MS
F
X Variable 1
Regression
Residual
4 20.41905 5.104762
Total
5 219.3333
Coefficientsindard Err
35.50476 2.599564 13.65797 0.000166 28.28721546 42.72231 28.28722 42.72231
1 Stat
P-value
Lower 95% Upper 95%ower 95.0%pper 95.0%
Intercept
X Variable 1 -3.37143 0.540093 -6.24231 0.003357 -4.87096773 -1.87189 -4.87097 -1.87189
(A). What does the scatter diagram indicate about the relationship between the two variables?
(a) A negative linear relationship. (b) A positive linear relationship. (c) No relationship.
(d) A nonlinear relationship. (e) Cannot be identified.
(B). Use the estimated regression equation to predict the value of y when x=3.5
(a) 120.8954 (b) 23.7049 (c) 20.4191
(d) 14.8076 (e) None of the above
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