Model Trendline Multi Excel 2013 V0F 1 by Milo Schield Member: International Statistical Institute US Rep: International Statistical Literacy Project Director,

Slides:

Advertisements

Similar presentations

Objective : 1)Students will be able to identify linear, exponential, and quadratic equations when given an equation, graph, or table. 2)Students will be.

Advertisements

Class 7.2: Graphical Analysis and Excel Solving Problems Using Graphical Analysis.

Forecasting Models With Linear Trend. Linear Trend Model If a modeled is hypothesized that has only linear trend and random effects, it will be of the.

Excel Notes Phys244/246 © 2007, B.J. Lieb. Calculating Velocity The velocity is calculated by entering the following: =(B3-B2) / (A3-A2). Then drag the.

Guide to Using Excel 2007 For Basic Statistical Applications To Accompany Business Statistics: A Decision Making Approach, 8th Ed. Chapter 16: Analyzing.

San Jose State University Engineering 101 JKA & KY.

Regression Analysis Module 3. Regression Regression is the attempt to explain the variation in a dependent variable using the variation in independent.

EGR 105 Foundations of Engineering I

Excel Part III Curve-Fitting, Regression Section 8 Fall 2013 EGR 105 Foundations of Engineering I.

Analysis of the Rainfall of Tropical Storm Allison Creating an Excel Model Creating an Excel Model.

The Best-Fit Line Linear Regression. PGCC CHM 103 Sinex How do you determine the best-fit line through data points? x-variable y-variable Fortunately.

LSP 120: Quantitative Reasoning and Technological Literacy Section 118 Özlem Elgün.

Assignment Read course PowerPoint file: MBD 2 Proj1.pptx (Slides 21-34)

Statistics: Data Analysis and Presentation Fr Clinic II.

Chapter 12a Simple Linear Regression

Session 10a. Decision Models -- Prof. Juran2 Overview Forecasting Methods Exponential Smoothing –Simple –Trend (Holt’s Method) –Seasonality (Winters’

EGR 105 Foundations of Engineering I Fall 2007 – week 7 Excel part 3 - regression.

Chapter 3 Forecasting McGraw-Hill/Irwin

Statistics: Data Presentation & Analysis Fr Clinic I.

Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

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

Regression in EXCEL r2 SSE b0 b1 SST.

Chapter 5 Plotting Data Curve Fitting, Good Graphing Practices Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

Types of Graphs Creating a Graph With Microsoft Excel.

Forecasting using trend analysis

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

Extending that Line into the Future St. Louis CMG February 12, 2008 Wayne Bell – UniGroup, Inc.

LINEAR REGRESSION Introduction Section 0 Lecture 1 Slide 1 Lecture 5 Slide 1 INTRODUCTION TO Modern Physics PHYX 2710 Fall 2004 Intermediate 3870 Fall.

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.

Chapter 8: Regression Analysis PowerPoint Slides Prepared By: Alan Olinsky Bryant University Management Science: The Art of Modeling with Spreadsheets,

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.

16-1 Linear Trend The long term trend of many business series often approximates a straight line.

Create Pivot Tables using Excel 2008 V1F 1 by Milo Schield Member: International Statistical Institute US Rep: International Statistical Literacy Project.

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.

Trend Projection Model b0b0 b1b1 YiYi

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.

Graphical Analysis in Excel EGN 1006 – Introduction to Engineering.

Model Trendline Linear Excel 2013 V0F 1 by Milo Schield Member: International Statistical Institute US Rep: International Statistical Literacy Project.

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

4.1 Modeling Nonlinear Data.  Create scatter plots of non linear data  Transform nonlinear data to use for prediction  Create residual plots.

Graphing Types of graphs & how to create graphs in Excel.

Revision: Pivot Table 1. Histogram 2. Trends 3. Linear 4. Exponential

Model Regress Linear 3Factor Excel 2013 V0F 1 by Milo Schield Member: International Statistical Institute US Rep: International Statistical Literacy Project.

LSP 120: Quantitative Reasoning and Technological Literacy Topic 1: Introduction to Quantitative Reasoning and Linear Models Lecture Notes 1.3 Prepared.

Creating a Scatter Plot On a Mac. Data in Excel Spreadsheet Insert the variable you want on the x-axis in the left column Insert the variable you want.

Data Analysis, Presentation, and Statistics

Model Trendline Linear 2Y1X Excel 2013 V0D 1 by Milo Schield Member: International Statistical Institute US Rep: International Statistical Literacy Project.

Model Trendline Linear 3Factor Excel by Milo Schield Member: International Statistical Institute US Rep: International Statistical Literacy Project.

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

MGS3100_03.ppt/Feb 11, 2016/Page 1 Georgia State University - Confidential MGS 3100 Business Analysis Time Series Forecasting Feb 11, 2016.

Example 13.3 Quarterly Sales at Intel Regression-Based Trend Models.

1 Ch 3: Forecasting: Techniques and Routes Introduction Forecasting is the establishment of future expectations by the analysis of past data, or the formation.

B-ball lab data. What does a graph of x –vs- t look like for your b-ball roll data? X (m) t (s) 0 0 x t Parabola (non-linear) not great for.

Plotting in Excel Ken youssefi Engineering 10.

Plotting in Excel KY San Jose State University Engineering 10.

TRANSFORMING RELATIONSHIPS

Trend Fitting in Excel Copyright (c) 2008 by The McGraw-Hill Companies. This material is intended solely for educational use by licensed users of LearningStats.

Fitting Exponentials and Polynomials to Data

Types of graphs, their relationship and equation

CHM 103 Sinex The Best-Fit Line Linear Regression.

Lesson 8: Graphing Multi-Variable Equations

Tell a Story with the Data

Microsoft Excel Chapters 6&7

Microsoft Excel Chapters 6&7

Multivariate Analysis Regression

Help with Excel Graphs CHM 2046L.

Creating a Graph With Microsoft Excel

1. How do I Solve Linear Equations

Microsoft Excel 2007 – Level 2

MATH 2311 Section 5.5.

Presentation transcript:

Model Trendline Multi Excel 2013 V0F 1 by Milo Schield Member: International Statistical Institute US Rep: International Statistical Literacy Project Director, W. M. Keck Statistical Literacy Project Slides at: /Model-Trendline-Multi-Excel2013-6up.pdf Model Using Trendline Non-Linear in Excel 2013

Model Trendline Multi Excel 2013 V0F 2 Goal: Summarize association between two variables 1.Generate seven charts showing association between two quantitative variables (slides 5-11). 2.Use seven different models: linear with forecast, linear with intercept = 0, polynomial, logarithmic, power, exponential and moving average. 3.For each chart (except moving average), show trend-line, regression equation and R 2. Show title and axis for all 4.Review comparison of model R-squared on slide 12. No description of association (trend) is necessary. For details on using Trendline to build a model, see > Model-Trendline-Linear-Excel2013-6up.pdf

Model Trendline Multi Excel 2013 V0F 3 Using Chart Trendline Create Graph. Look for + Sign. Select Chart Elements. Check Trendline box. Select More Options. Select Algebraic model Check Equation & R-square [Check Forecast or Intercept]

Model Trendline Multi Excel 2013 V0F 4 Algebraic Models 1) Linear: Y=a+bx. Straight line, simplest 2) Polynomial: Y= a+bx+cx 2. Multiple curves 3) Logarithmic: Y=aLn(x)+b. Ratio scale. Equal ratios have equal differences Log 10 (1) = 0; Log 10 (10) = 1; Log 10 (100) = 2 4) Power model: Y=ax b [Between log & exp.] 5) Exponential: Y=ae x/b. Constant rate of change 6) Moving average: For time series

Model Trendline Multi Excel 2013 V0F 5 1)Linear Model w Forecast

Model Trendline Multi Excel 2013 V0F 6 1)Linear Model: Intercept = 0

Model Trendline Multi Excel 2013 V0F 7 2) Polynomial Model

Model Trendline Multi Excel 2013 V0F 8 3) Logarithmic Model

Model Trendline Multi Excel 2013 V0F 9 4) Power Model

Model Trendline Multi Excel 2013 V0F 10 5) Exponential Model

Model Trendline Multi Excel 2013 V0F 11,

Model Trendline Multi Excel 2013 V0F 12 Comparison of R-squared Percentage of Weight “explained by” Height 61.6% Linear model 40.6% Linear (intercept = 0) << Worst fit 62.1% Polynomial model 61.2% Logarithmic model 63.1% Power model 63.3% Exponential model << Best fit! No equation/fit for Moving-Average model.