CIMA Paper P1 Management Accounting

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Presentation transcript:

CIMA Paper P1 Management Accounting 江西财经大学会计学院熊家财 xiongjc-p@163.com

13 Chapter Forecasting Techniques

Chapter Content Forecasting Techniques The High Low Method Regression Time Series Analysis

Section 1 The need for forecasting 迎评工作一 Section 1 The need for forecasting

The need for forecasting

Section 2 High-low method 迎评工作一 Section 2 High-low method

High Low Method Choose highest and lowest output

High Low Method Example 1

High Low Method Example 2

Section 3 Regression analysis 迎评工作一 Section 3 Regression analysis

迎评工作一 Section 3.1 Regression

Least Squares Regression Analysis Equation of a straight line Intercept (on y-axis) Gradient Dependent variable y = a +bx Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours… Independent variable

Least Squares Regression Analysis n∑xy – ∑x∑y b = n∑x2 – (∑x)2 a = y – bx Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Least Squares Regression Analysis Example 3 Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Least Squares Regression Analysis Example 3 Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Least Squares Regression Analysis Example 4 Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Least Squares Regression Analysis Example 4 Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

迎评工作一 Section 3.2 Correlation

Correlation Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Correlation Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Correlation Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Least Squares Regression Analysis Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Least Squares Regression Analysis Please can we make this look like later slides in session 5 with formulae. Animate such that formula appears first, then the arrows & definitions appear in a clockwise direction starting at average hours…

Section 4 Time series analysis 迎评工作一 Section 4 Time series analysis

Time Series Analysis A time series is a series of figures relating to the changing value of a variable over time.

Components of a time series

Components of a time series

Components of a time series

Components of a time series

迎评工作一 Section 4.1 Find the trend

The trend

The trend: moving average

The trend: moving average for even number

The trend: moving average for even number Example 5

The trend: moving average for even number Example 5

Section 4.2 Find the seasonal variation 迎评工作一 Section 4.2 Find the seasonal variation

Seasonal variation Example 6

Seasonal variation Example 6 Example in p593

Section 4.3 Multiplicative model 迎评工作一 Section 4.3 Multiplicative model

The Multiplicative Model The Multiplicative Model looks at the seasonal variation in proportional terms. Actual (A) = T x S x R

Seasonal variation Example7

Seasonal variation Example7

迎评工作一 Section 4.4 Forecasting

Forecasting

Chapter Summary