Answer the questions based on the regression results summarized below (if necessary, scroll down or right to view the (a) The regression is overall not significant ata =0.01 significance level. entire table). O True OLS Regression Resulta O False www * Dep. Variabler VariableY OLS Least Squares Tue, 25 May 2021 R-squared: Adj. R-squared F-statistic: 0.608 0.605 Model Method: (b) The independent variables can collectively explain % of the variability in Variable Y. (Round to one decimal place, 222.9 2.37e-87 Dates Prob (P-statistie) Log-Likelihood including any zeros.) Time No. Obeervatione DE Residuals Df Hodel. O1619 -1284.6 2577. 436 432 AIC DICI (c) There is a significant relation between the dependent variable and gach of the three independent variables ata = 0.01 significance level. 2593. Covariance Type: nonrobuat td e O True coet (0.025 0.9751 O False 25.941 -17.056 53.737 -0.713 Intercept Variable R Variable z VariableO 49.9519 -0.8064 1.926 0.047 0.000 0.000 46.167 199 0.0104 -1.0051 -0.009 -1.217 0.010 1.036 0.301 0.000 0.030 -0.793 (d) If Variable Q increases one unit, Variable Y would 0.108 -9.330 Omnibun Prob(Omnibus) s0.296 0.000 Durbin-wataon Jarque-Bera (JB) O A. Increase units 1.174 148.594 Skev Kurtosis Prob( JB) 1.038 : 5.41e-33 Cond. No. OB. Decrease units 4.967 644. OC. Not change (Round to three decimal places, including any zeros.) (e) Regression residuals are Normally distributed a = 0.01 significance level and therefore satisfy linear regression Normality assumption. O True O False
Answer the questions based on the regression results summarized below (if necessary, scroll down or right to view the (a) The regression is overall not significant ata =0.01 significance level. entire table). O True OLS Regression Resulta O False www * Dep. Variabler VariableY OLS Least Squares Tue, 25 May 2021 R-squared: Adj. R-squared F-statistic: 0.608 0.605 Model Method: (b) The independent variables can collectively explain % of the variability in Variable Y. (Round to one decimal place, 222.9 2.37e-87 Dates Prob (P-statistie) Log-Likelihood including any zeros.) Time No. Obeervatione DE Residuals Df Hodel. O1619 -1284.6 2577. 436 432 AIC DICI (c) There is a significant relation between the dependent variable and gach of the three independent variables ata = 0.01 significance level. 2593. Covariance Type: nonrobuat td e O True coet (0.025 0.9751 O False 25.941 -17.056 53.737 -0.713 Intercept Variable R Variable z VariableO 49.9519 -0.8064 1.926 0.047 0.000 0.000 46.167 199 0.0104 -1.0051 -0.009 -1.217 0.010 1.036 0.301 0.000 0.030 -0.793 (d) If Variable Q increases one unit, Variable Y would 0.108 -9.330 Omnibun Prob(Omnibus) s0.296 0.000 Durbin-wataon Jarque-Bera (JB) O A. Increase units 1.174 148.594 Skev Kurtosis Prob( JB) 1.038 : 5.41e-33 Cond. No. OB. Decrease units 4.967 644. OC. Not change (Round to three decimal places, including any zeros.) (e) Regression residuals are Normally distributed a = 0.01 significance level and therefore satisfy linear regression Normality assumption. O True O False
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Concept explainers
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.
Question
Transcribed Image Text:Answer the questions based on the regression results summarized below (if necessary, scroll down or right to view the
entire table).
(a) The regression is overall not significant at c = 0.01 significance level.
True
OLS Regression Resulta
O False
-----
Dep. variable:
Modeli
Variable_Y
R-squaredi
Adj. R-squaredi
F-statistic:
Prob (P-statistic)) :
Log-Likelihood:
0.608
OLS
0.605
(b) The independent variables can collectively explain % of the variability in Variable Y. (Round to one decimal place,
Method:
Least Squares
Tue, 25 May 2021
08:16:19
222.9
Date:
2.37e-87
including any zeros.)
Time:
No. Obeervations:
Df Residuals:
-1284.6
436
AIC:
2577.
(c) There is a significant relation between the dependent variable and each of the three independent variables at a = 0.01
significance level.
432
BIC:
2593.
Df Model:
3
Covariance Type:
noarobuat
P>t|
O True
coef
std err
ro.025
0.9751
25.941
O False
Intercept
Variable_R
Variable_z
Variable_Q
-
49.9519
1.926
0.000
46.167
53.737
-0.8064
0.0104
0.047
-17.056
0.000
-0.899
-0.713
0.010
1.036
0.301
-0.009
0.030
(d) If Variable Q increases one unit, Variable Y would
-1.0051
0.108
-9.330
0-009
0.000
-1.217
-0.793
O A. Increase
Durbin-Watson:
Jarque-Bera (JB) :
Prob(JB)
Cond. No.
-----
Omnibus:
80.296
1.174
units
0.000
Prob(Omnibus):
Skew:
148.594
1.038
5.4le-33
O B. Decrease
units
Kurtosis:
4.967
644.
-
OC. Not change
(Round to three decimal places, including any zeros.)
(e) Regression residuals are Normally distributed a = 0.01 significance level and therefore satisfy linear regression
Normality assumption.
True
False
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 2 steps
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman