logging in or signing up forecasting using trand analysis ahmedsamra Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT lite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 391 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: July 21, 2010 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide 1: "I always avoid prophesying beforehand because it is much better to prophesy after the event has already taken place. " --Winston Churchill Forecasting using trend analysis : Quantitative forecasting methods in library management 2 Forecasting using trend analysis Part 1. Theory Part 2. Using Excel: a demonstration. Assignment 1, 2 Learning objectives : Quantitative forecasting methods in library management 3 Learning objectives To compute a trend for a given time-series data using Excel To choose a best fitting trend line for a given time-series To calculate a forecast using regression equation To learn how: Main idea of the trend analysis forecasting method : Quantitative forecasting methods in library management 4 Main idea of the trend analysis forecasting method Main idea of the method: a forecast is calculated by inserting a time value into the regression equation. The regression equation is determined from the time-serieas data using the “least squares method” Prerequisites: 1. Data pattern: Trend : Quantitative forecasting methods in library management 5 Prerequisites: 1. Data pattern: Trend Prerequisites: 2. Correlation : Quantitative forecasting methods in library management 6 Prerequisites: 2. Correlation There should be a sufficient correlation between the time parameter and the values of the time-series data The Correlation Coefficient : Quantitative forecasting methods in library management 7 The Correlation Coefficient The correlation coefficient, R, measure the strength and direction of linear relationships between two variables. It has a value between –1 and +1 A correlation near zero indicates little linear relationship, and a correlation near one indicates a strong linear relationship between the two variables Main idea of the trend analysis method : Quantitative forecasting methods in library management 8 Main idea of the trend analysis method Trend analysis uses a technique called least squares to fit a trend line to a set of time series data and then project the line into the future for a forecast. Trend analysis is a special case of regression analysis where the dependent variable is the variable to be forecasted and the independent variable is time. While moving average model limits the forecast to one period in the future, trend analysis is a technique for making forecasts further than one period into the future. The general equation for a trend line : Quantitative forecasting methods in library management 9 The general equation for a trend line F=a+bt Where: F – forecast, t – time value, a – y intercept, b – slope of the line. Least Square Method : Quantitative forecasting methods in library management 10 Least Square Method Least square method determines the values for a and b so that the resulting line is the best-fit line through a set of the historical data. After a and b have been determined, the equation can be used to forecast future values. The trend line is the “best-fit” line: an example : Quantitative forecasting methods in library management 11 The trend line is the “best-fit” line: an example Statistical measures of goodness of fit : Quantitative forecasting methods in library management 12 Statistical measures of goodness of fit The Correlation Coefficient The Determination Coefficient In trend analysis the following measures will be used: The Coefficient of Determination : Quantitative forecasting methods in library management 13 The Coefficient of Determination The coefficient of determination, R2, measures the percentage of variaion in the dependent variable that is explained by the regression or trend line. It has a value between zero and one, with a high value indicating a good fit. Goodness of fitt: Determination Coefficient RSQ : Quantitative forecasting methods in library management 14 Goodness of fitt: Determination Coefficient RSQ Range: [0, 1]. RSQ=1 means best fitting; RSQ=0 means worse fitting; Evaluation of the trend analysis forecasting method : Quantitative forecasting methods in library management 15 Evaluation of the trend analysis forecasting method Advantages: Simple to use (if using appropriate software) Disadvantages: 1) not always applicable for the long-term time series (because there exist several ternds in such cases); 2) not applicable for seasonal and cyclic datta patterns. Part 2. Switch to Excel : Part 2. Switch to Excel Open a Workbook trend.xls, save it to your computer Working with Excel : Quantitative forecasting methods in library management 17 Working with Excel Demonstration of the forecasting procedure using trend analysis method Assignment 1. Repeating of the forecasting procedure with the same data Assignment 2. Forecasting of the expenditure Using Excel to calculate linear trend : Quantitative forecasting methods in library management 18 Using Excel to calculate linear trend Select a line on the diagram Right click and select Add Trendline Select a type of the trend (Linear) Part 3. Non-linear trends : Quantitative forecasting methods in library management 19 Part 3. Non-linear trends Non-linear trends : Quantitative forecasting methods in library management 20 Non-linear trends Logarythmic Polynomial Power Exponential Excel provides easy calculation of the following trends Slide 21: Quantitative forecasting methods in library management 21 Slide 22: Quantitative forecasting methods in library management 22 Slide 23: Quantitative forecasting methods in library management 23 Slide 24: Quantitative forecasting methods in library management 24 Choosing the trend that fitts best : Quantitative forecasting methods in library management 25 Choosing the trend that fitts best 1) Roughly: Visually, comparing the data pattern to the one of the 5 trends (linear, logarythmic, polynomial, power, exponential) 2) In a detailed way: By means of the determination coefficient End : End You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
forecasting using trand analysis ahmedsamra Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT lite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 391 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: July 21, 2010 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide 1: "I always avoid prophesying beforehand because it is much better to prophesy after the event has already taken place. " --Winston Churchill Forecasting using trend analysis : Quantitative forecasting methods in library management 2 Forecasting using trend analysis Part 1. Theory Part 2. Using Excel: a demonstration. Assignment 1, 2 Learning objectives : Quantitative forecasting methods in library management 3 Learning objectives To compute a trend for a given time-series data using Excel To choose a best fitting trend line for a given time-series To calculate a forecast using regression equation To learn how: Main idea of the trend analysis forecasting method : Quantitative forecasting methods in library management 4 Main idea of the trend analysis forecasting method Main idea of the method: a forecast is calculated by inserting a time value into the regression equation. The regression equation is determined from the time-serieas data using the “least squares method” Prerequisites: 1. Data pattern: Trend : Quantitative forecasting methods in library management 5 Prerequisites: 1. Data pattern: Trend Prerequisites: 2. Correlation : Quantitative forecasting methods in library management 6 Prerequisites: 2. Correlation There should be a sufficient correlation between the time parameter and the values of the time-series data The Correlation Coefficient : Quantitative forecasting methods in library management 7 The Correlation Coefficient The correlation coefficient, R, measure the strength and direction of linear relationships between two variables. It has a value between –1 and +1 A correlation near zero indicates little linear relationship, and a correlation near one indicates a strong linear relationship between the two variables Main idea of the trend analysis method : Quantitative forecasting methods in library management 8 Main idea of the trend analysis method Trend analysis uses a technique called least squares to fit a trend line to a set of time series data and then project the line into the future for a forecast. Trend analysis is a special case of regression analysis where the dependent variable is the variable to be forecasted and the independent variable is time. While moving average model limits the forecast to one period in the future, trend analysis is a technique for making forecasts further than one period into the future. The general equation for a trend line : Quantitative forecasting methods in library management 9 The general equation for a trend line F=a+bt Where: F – forecast, t – time value, a – y intercept, b – slope of the line. Least Square Method : Quantitative forecasting methods in library management 10 Least Square Method Least square method determines the values for a and b so that the resulting line is the best-fit line through a set of the historical data. After a and b have been determined, the equation can be used to forecast future values. The trend line is the “best-fit” line: an example : Quantitative forecasting methods in library management 11 The trend line is the “best-fit” line: an example Statistical measures of goodness of fit : Quantitative forecasting methods in library management 12 Statistical measures of goodness of fit The Correlation Coefficient The Determination Coefficient In trend analysis the following measures will be used: The Coefficient of Determination : Quantitative forecasting methods in library management 13 The Coefficient of Determination The coefficient of determination, R2, measures the percentage of variaion in the dependent variable that is explained by the regression or trend line. It has a value between zero and one, with a high value indicating a good fit. Goodness of fitt: Determination Coefficient RSQ : Quantitative forecasting methods in library management 14 Goodness of fitt: Determination Coefficient RSQ Range: [0, 1]. RSQ=1 means best fitting; RSQ=0 means worse fitting; Evaluation of the trend analysis forecasting method : Quantitative forecasting methods in library management 15 Evaluation of the trend analysis forecasting method Advantages: Simple to use (if using appropriate software) Disadvantages: 1) not always applicable for the long-term time series (because there exist several ternds in such cases); 2) not applicable for seasonal and cyclic datta patterns. Part 2. Switch to Excel : Part 2. Switch to Excel Open a Workbook trend.xls, save it to your computer Working with Excel : Quantitative forecasting methods in library management 17 Working with Excel Demonstration of the forecasting procedure using trend analysis method Assignment 1. Repeating of the forecasting procedure with the same data Assignment 2. Forecasting of the expenditure Using Excel to calculate linear trend : Quantitative forecasting methods in library management 18 Using Excel to calculate linear trend Select a line on the diagram Right click and select Add Trendline Select a type of the trend (Linear) Part 3. Non-linear trends : Quantitative forecasting methods in library management 19 Part 3. Non-linear trends Non-linear trends : Quantitative forecasting methods in library management 20 Non-linear trends Logarythmic Polynomial Power Exponential Excel provides easy calculation of the following trends Slide 21: Quantitative forecasting methods in library management 21 Slide 22: Quantitative forecasting methods in library management 22 Slide 23: Quantitative forecasting methods in library management 23 Slide 24: Quantitative forecasting methods in library management 24 Choosing the trend that fitts best : Quantitative forecasting methods in library management 25 Choosing the trend that fitts best 1) Roughly: Visually, comparing the data pattern to the one of the 5 trends (linear, logarythmic, polynomial, power, exponential) 2) In a detailed way: By means of the determination coefficient End : End