Trend Projection Model b0b0 b1b1 YiYi << The X variable in a Trend Projection model is the time period t.

Slides:

Advertisements

Similar presentations

Lesson 10: Linear Regression and Correlation

Advertisements

Applied Econometrics Second edition

Forecasting Using the Simple Linear Regression Model and Correlation

Regresi Linear Sederhana Pertemuan 01 Matakuliah: I0174 – Analisis Regresi Tahun: Ganjil 2007/2008.

Localized Trendlines LSP 120 Week 6 Joanna Deszcz.

Chapter 12 Simple Regression

Correlation and Regression Analysis

Chapter 13 Introduction to Linear Regression and Correlation Analysis

Chapter 12a Simple Linear Regression

Linear Regression In Excel. Linear Regression  In this presentation you will learn the following: How to make a scatter plot in Excel (Click Here)Here.

Pengujian Parameter Koefisien Korelasi Pertemuan 04 Matakuliah: I0174 – Analisis Regresi Tahun: Ganjil 2007/2008.

Chapter Topics Types of Regression Models

Linear Regression and Correlation Analysis

Chapter 11 Solved Problems 1. Exhibit 11.2 Example Linear and Nonlinear Trend Patterns 2.

Korelasi dalam Regresi Linear Sederhana Pertemuan 03 Matakuliah: I0174 – Analisis Regresi Tahun: Ganjil 2007/2008.

© 2000 Prentice-Hall, Inc. Chap Forecasting Using the Simple Linear Regression Model and Correlation.

Pertemua 19 Regresi Linier

Chapter 14 Introduction to Linear Regression and Correlation Analysis

Chapter 7 Forecasting with Simple Regression

Simple Linear Regression

Mathematical Modeling Making Predictions with Data.

Introduction to Linear Regression and Correlation Analysis

1 1 Slide © 2009 Thomson South-Western. All Rights Reserved Slides by JOHN LOUCKS St. Edward’s University.

Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 12-1 Chapter 12 Simple Linear Regression Statistics for Managers Using.

Statistics for Business and Economics 8 th Edition Chapter 11 Simple Regression Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Ch.

Linear Trend Lines Y t = b 0 + b 1 X t Where Y t is the dependent variable being forecasted X t is the independent variable being used to explain Y. In.

1 1 Slide © 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole.

1 1 Slide Simple Linear Regression Part A n Simple Linear Regression Model n Least Squares Method n Coefficient of Determination n Model Assumptions n.

OPIM 303-Lecture #8 Jose M. Cruz Assistant Professor.

Linear Trend Lines = b 0 + b 1 X t Where is the dependent variable being forecasted X t is the independent variable being used to explain Y. In Linear.

1 1 Slide © 2004 Thomson/South-Western Slides Prepared by JOHN S. LOUCKS St. Edward’s University Slides Prepared by JOHN S. LOUCKS St. Edward’s University.

© 2003 Prentice-Hall, Inc.Chap 13-1 Basic Business Statistics (9 th Edition) Chapter 13 Simple Linear Regression.

You want to examine the linear dependency of the annual sales of produce stores on their size in square footage. Sample data for seven stores were obtained.

Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc. Chap 12-1 Correlation and Regression.

Introduction to Linear Regression

Chap 12-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition Chapter 12 Introduction to Linear.

EQT 373 Chapter 3 Simple Linear Regression. EQT 373 Learning Objectives In this chapter, you learn: How to use regression analysis to predict the value.

Statistical Methods Statistical Methods Descriptive Inferential

LBSRE1021 Data Interpretation Lecture 11 Correlation and Regression.

Chapter 5: Regression Analysis Part 1: Simple Linear Regression.

Linear Trend Lines = b 0 + b 1 X t Where is the dependent variable being forecasted X t is the independent variable being used to explain Y. In Linear.

Math & Formula Do math under any tab ■ Click the cell (B32) where put the result mean, and next to f x type: average(B2:B31) ■ (B2:B31) is define the data.

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 13-1 Introduction to Regression Analysis Regression analysis is used.

Correlation and Regression. Section 9.1  Correlation is a relationship between 2 variables.  Data is often represented by ordered pairs (x, y) and.

Example 13.2 Quarterly Sales of Johnson & Johnson Regression-Based Trend Models.

Lecture 10: Correlation and Regression Model.

1 1 Slide © 2003 South-Western/Thomson Learning™ Slides Prepared by JOHN S. LOUCKS St. Edward’s University.

Scatter Diagrams scatter plot scatter diagram A scatter plot is a graph that may be used to represent the relationship between two variables. Also referred.

© 2001 Prentice-Hall, Inc.Chap 13-1 BA 201 Lecture 18 Introduction to Simple Linear Regression (Data)Data.

Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights reserved.

2.5 Modeling Real-World Data Using Scatter plots Linear Regression.

STATISTICS 12.0 Correlation and Linear Regression “Correlation and Linear Regression -”Causal Forecasting Method.

1 Forecasting/ Causal Model MGS Forecasting Quantitative Causal Model Trend Time series Stationary Trend Trend + Seasonality Qualitative Expert.

Lecture 10 Introduction to Linear Regression and Correlation Analysis.

Chapter 4 Minitab Recipe Cards. Correlation coefficients Enter the data from Example 4.1 in columns C1 and C2 of the worksheet.

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.

© 2001 Prentice-Hall, Inc.Chap 13-1 BA 201 Lecture 19 Measure of Variation in the Simple Linear Regression Model (Data)Data.

BUSINESS MATHEMATICS & STATISTICS. Module 6 Correlation ( Lecture 28-29) Line Fitting ( Lectures 30-31) Time Series and Exponential Smoothing ( Lectures.

Chapter 12 Simple Regression Statistika.  Analisis regresi adalah analisis hubungan linear antar 2 variabel random yang mempunyai hub linear,  Variabel.

Introduction Many problems in Engineering, Management, Health Sciences and other Sciences involve exploring the relationships between two or more variables.

Statistics for Managers using Microsoft Excel 3rd Edition

Linear Regression and Correlation Analysis

BUSINESS MATHEMATICS & STATISTICS.

Simple Linear Regression

Correlation and Regression

PENGOLAHAN DAN PENYAJIAN

Coefficient of Determination

Help with Excel Graphs CHM 2046L.

Presentation transcript:

Trend Projection Model b0b0 b1b1 YiYi << The X variable in a Trend Projection model is the time period t

Trend Projection in Excel Two techniques: –On the Chart, select the time series and then right- click to ADD TRENDLINE. Pick the linear trendline option and display the equation and R-square or –On a Worksheet that contains the time series, select the TOOLS menu in Excel 2003 or the DATA tab in Excel 2007; open the DATA ANALYSIS submenu, and select the REGRESSION option in the dialog box. See snippits in Blackboard to add-in the Data Analysis submenu if it does not show up as an option in Excel on your PC at home.

Excel’s Regression Option

Class Exercise: Trend Projection Output for Trend.xls

Trend Projection Model From Excel Printout:

The Coefficient of Determination r 2 is a number between 0 and 100% Measures the proportion of variation in Y that is explained by the independent variable X in the regression model In trend projections, you can interpret it as the proportion of variation in Y that is explained by the presence of linear trend.

Simple Linear Regression: Example You want to examine the linear dependency of the annual sales of produce stores on their size in square footage. Sample data for seven stores were obtained. Find the equation of the straight line that fits the data best. Annual Store Square Sales Feet($1000) 1 1,726 3, ,542 3, ,816 6, ,555 9, ,292 3, ,208 5, ,313 3,760

Which is the dependent Y variable? A.The Store Number B.The Square Footage of the Store C.The Annual Sales of the Store

Which is the independent X variable? A.The Store Number B.The Square Footage of the Store C.The Annual Sales of the Store

Scatter Diagram: Example Excel Output

Equation for the Sample Regression Line: Example From Excel Printout:

Graph of the Sample Regression Line: Example Y i = X i 

Interpretation of Results: Example The slope of means that for each increase of one unit in X, we predict the average of Y to increase by an estimated units. The model estimates that for each increase of one square foot in the size of the store, the expected annual sales are predicted to increase by $1487.

Restaurant Sales Exercise (Regress.xls) The manager wants to forecast restaurant sales for quarter 11 On the Trend Projection worksheet, generate the Trend Projection output starting in cell A17 and forecast restaurant sales for quarters 1-10 On the Regression worksheet, perform a regression of restaurant sales on student population. Write the regression output starting in cell A17 and forecast restaurant sales for quarters 1-10

Trend Projection Output

Regression on Student Population Output