Center of Statistical Analysis Correlation and Regression Analysis

Slides:



Advertisements
Similar presentations
Learning Objectives 1 Copyright © 2002 South-Western/Thomson Learning Data Analysis: Bivariate Correlation and Regression CHAPTER sixteen.
Advertisements

1 Multiple Regression A single numerical response variable, Y. Multiple numerical explanatory variables, X 1, X 2,…, X k.
Collinearity. Symptoms of collinearity Collinearity between independent variables – High r 2 High vif of variables in model Variables significant in simple.
Chapter 14 Introduction to Linear Regression and Correlation Analysis
Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Managerial Economics, 9e Managerial Economics Thomas Maurice.
Korelasi Ganda Dan Penambahan Peubah Pertemuan 13 Matakuliah: I0174 – Analisis Regresi Tahun: Ganjil 2007/2008.
Chapter 12 Simple Regression
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
Dr. Michael R. Hyman Factor Analysis. 2 Grouping Variables into Constructs.
Business Statistics - QBM117 Interval estimation for the slope and y-intercept Hypothesis tests for regression.
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
Multiple Linear Regression
1 Chapter 17: Introduction to Regression. 2 Introduction to Linear Regression The Pearson correlation measures the degree to which a set of data points.
SW388R7 Data Analysis & Computers II Slide 1 Multiple Regression – Basic Relationships Purpose of multiple regression Different types of multiple regression.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Simple Linear Regression Analysis Chapter 13.
Lecture 14 Multiple Regression Model
Managerial Economics Demand Estimation. Scatter Diagram Regression Analysis.
Introduction to Linear Regression
AGENDA MULTIPLE REGRESSION BASICS  Overall Model Test (F Test for Regression)  Test of Model Parameters  Test of β i = β i *  Coefficient of Multiple.
Production Planning and Control. A correlation is a relationship between two variables. The data can be represented by the ordered pairs (x, y) where.
Multiple Regression Lab Chapter Topics Multiple Linear Regression Effects Levels of Measurement Dummy Variables 2.
Copyright © 2005 by the McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Managerial Economics Thomas Maurice eighth edition Chapter 4.
Statistics for Business and Economics 8 th Edition Chapter 11 Simple Regression Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Ch.
CORRELATION: Correlation analysis Correlation analysis is used to measure the strength of association (linear relationship) between two quantitative variables.
Statistics for Business and Economics 8 th Edition Chapter 11 Simple Regression Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Ch.
ECON 338/ENVR 305 CLICKER QUESTIONS Statistics – Question Set #8 (from Chapter 10)
Correlation and Regression: The Need to Knows Correlation is a statistical technique: tells you if scores on variable X are related to scores on variable.
Correlation & Regression
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice- Hall, Inc. Chap 14-1 Business Statistics: A Decision-Making Approach 6 th Edition.
SOCW 671 #11 Correlation and Regression. Uses of Correlation To study the strength of a relationship To study the direction of a relationship Scattergrams.
By: Seth Fields and Karl Morris. Hypothesis: We believe that some of the Eagles’ stats will be linear and have a positive correlation (meaning that the.
© 2000 Prentice-Hall, Inc. Chap Chapter 10 Multiple Regression Models Business Statistics A First Course (2nd Edition)
BPA CSUB Prof. Yong Choi. Midwest Distribution 1. Create scatter plot Find out whether there is a linear relationship pattern or not Easy and simple using.
Chapter 14 Introduction to Regression Analysis. Objectives Regression Analysis Uses of Regression Analysis Method of Least Squares Difference between.
AP Review Exploring Data. Describing a Distribution Discuss center, shape, and spread in context. Center: Mean or Median Shape: Roughly Symmetrical, Right.
Center of Statistical Analysis
Chapter 13 Simple Linear Regression
Center of Statistical Analysis
Scatter Plots and Correlation
Chapter 14 Introduction to Multiple Regression
CORRELATION.
REGRESSION (R2).
Dr. Amjad El-Shanti MD, PMH,Dr PH University of Palestine 2016
Improving Student Engagement Through Audience Response Systems
Basic Estimation Techniques
Linear Regression and Correlation Analysis
Multiple Regression Analysis and Model Building
Correlation and regression
Chapter 11 Simple Regression
Elementary Statistics
CHAPTER fourteen Correlation and Regression Analysis
Simple Linear Regression and Correlation
Chapter 15 Linear Regression
Simple Linear Regression
Basic Estimation Techniques
BA 275 Quantitative Business Methods
STA 282 – Regression Analysis
24/02/11 Tutorial 3 Inferential Statistics, Statistical Modelling & Survey Methods (BS2506) Pairach Piboonrungroj (Champ)
Simple Linear Regression
Chapter 13 Group Differences
Correlation and Regression
Pemeriksaan Sisa dan Data Berpengaruh Pertemuan 17
Multiple Linear Regression
Product moment correlation
Correlation & Trend Lines
Cases. Simple Regression Linear Multiple Regression.
Introduction to Regression
Business Statistics - QBM117
CORRELATION & REGRESSION compiled by Dr Kunal Pathak
Presentation transcript:

Center of Statistical Analysis Correlation and Regression Analysis CSA-C Presented By: EL Hajjar, Said Associate Professor, Ahlia University Second Semester, 2017 Dr. Said T. EL Hajjar

Activity 1: Correlation We need to study the correlation between the independent variables PP and SS with the dependent variable TP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Dr. Said T. EL Hajjar

Activity 1: Correlation(Case I ) We need to study the correlation between the independent variables PP and SS with the dependent variable TP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y There is strong positive linear correlation between TP and PP ( r = 0.9), this correlation is significant ( p-value = 0.000 < 0.01) Dr. Said T. EL Hajjar

Activity 1: Correlation(Case II ) We need to study the correlation between the independent variables PP and SS with the dependent variable TP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Although there is weak positive linear correlation between TP and PP ( r = 0.4), this correlation is significant ( p-value = 0.000 < 0.01) Dr. Said T. EL Hajjar

Activity 1: Correlation(Case III ) We need to study the correlation between the independent variables PP and SS with the dependent variable TP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y There is strong positive linear correlation between TP and PP ( r = 0.8); however, this correlation is not significant ( p-value = 0.050 > 0.01) Dr. Said T. EL Hajjar

Activity 1: Correlation(Case IV ) We need to study the correlation between the independent variables PP and SS with the dependent variable TP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y There is weak positive linear correlation between TP and PP ( r = 0.8) and this correlation is not significant ( p-value = 0.060 > 0.01) Dr. Said T. EL Hajjar

Output: Effect of PP on TP Activity 1I: Regression Analysis (Case I ) Output: Effect of PP on TP 81.1% of the variation in TP is explained by a portion variation in PP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Moreover, the independent variable PP does explain a significant portion of the variation in the dependent variable TP ( p-value = 0.000 < 0.05) Dr. Said T. EL Hajjar

Output: Effect of PP on TP Activity 1I: Regression Analysis (Case I ) Output: Effect of PP on TP Estimated Regression Line : 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Moreover, there is sufficient evidence that PP affects TP ( p-value = 0.000 < 0.05 ). (Positive Effect) -Note that 0.052 is the portion of TP not explained by PP. -Value of TP will increase, on average, by 1.095 unit value of PP for each one unit increase in PP value. Dr. Said T. EL Hajjar

Output: Effect of PP on TP Activity 1I: Regression Analysis (Case II ) Output: Effect of PP on TP 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y 10.1% of the variation in TP is explained by a portion variation in PP. However, the independent variable PP does explain a significant portion of the variation in the dependent variable TP ( p-value = 0.000 < 0.05) Dr. Said T. EL Hajjar

Output: Effect of PP on TP Activity 1I: Regression Analysis (Case II ) Output: Effect of PP on TP Estimated Regression Line : 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Moreover, there is sufficient evidence that PP affects TP ( p-value = 0.000 < 0.05 ). ( Negative Effect ) -Note that 0.052 is the portion of TP not explained by PP. -Value of TP will decrease, on average, by 1.095 unit value of PP for each one unit increase in PP value. Dr. Said T. EL Hajjar

Output: Effect of PP on TP Activity 1I: Regression Analysis (Case III ) Output: Effect of PP on TP 1.1% of the variation in TP is explained by variation in PP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y And, the independent variable PP does not explain a significant portion of the variation in the dependent variable TP ( p-value = 0.102 > 0.05) So, No need to proceed. PP does not influence TP Dr. Said T. EL Hajjar

Output: Effect of PP on TP Activity 1I: Regression Analysis (Case IV ) Output: Effect of PP on TP 10.1% of the variation in TP is explained by a portion variation in PP. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y However, the independent variable PP does explain a significant portion of the variation in the dependent variable TP ( p-value = 0.000 < 0.05) Dr. Said T. EL Hajjar

Output: Effect of PP on TP Activity 1I: Regression Analysis (Case IV ) Output: Effect of PP on TP Estimated Regression Line : 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Moreover, there is no sufficient evidence that PP affects house price ( p-value = 0.070 > 0.05 ). ( No Effect ) So, PP does not influence TP Dr. Said T. EL Hajjar

Consider the following Model Activity III: Multiple Regression Analysis Consider the following Model 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Dr. Said T. EL Hajjar

Step2 : Continue / OK .We get the output: Multiple Regression Analysis Step2 : Continue / OK .We get the output: 87.3% of the variation in TP is explained by a portion variation in PP and SS. 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Moreover, the independent variables PP and SS do explain a significant portion of the variation in the dependent variable TP ( p-value = 0.000 < 0.05) Dr. Said T. EL Hajjar

Step2 : Continue / OK .We get the output: Multiple Regression Analysis Step2 : Continue / OK .We get the output: Estimated Regression Line : 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Value of TP will increase, on average, by 0.769 unit for each 1 unit increase in the value of PP, net of the effects of changes due to SS score. Value of TP will increase, on average, by 0.454 unit for each 1 unit increase in the value of SS, net of the effects of changes due to PP score. Moreover, there is sufficient evidence that overall PP and SS affects TP ( p-value for PP = 0.000 < 0.05 and p-value for SS = 0.000 < 0.05. Dr. Said T. EL Hajjar

Step2 : Continue / OK .We get the output: Multiple Regression Analysis Step2 : Continue / OK .We get the output: Estimated Regression Line : 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Value of TP will increase, on average, by 0.769 unit for each 1 unit increase in the value of PP, net of the effects of changes due to SS score. Value of TP will decrease, on average, by 0.454 unit for each 1 unit increase in the value of SS, net of the effects of changes due to PP score. Moreover, there is sufficient evidence that overall PP and SS affects TP ( p-value for PP = 0.000 < 0.05 and p-value for SS = 0.000 < 0.05. Dr. Said T. EL Hajjar

End Freedom is the first five minutes of your born. Afterwards, they decide your name, your nationality, your religion, your sect,…. And you will spend your whole life struggling and defending stupidly about things you did not select. Ziad AL Rahbani THANK YOU 1 Items (statements) designated are scored 1,2,3,4 and 5, respectively for responses Strongly Disagree, Disagree, Undecided, Agree, and Strongly Agree 2 Independent = X, Dependent = Y Dr. Said T. EL Hajjar