“DEMAND FOR VE MICROWAVE OVEN”
TABLE OF CONTACT
3.0 DATA DEMAND FOR VE MICROWAVE OVEN
5.0 FINDINGS AND INTERPRETATION
5.1 Evaluation of Statically Significant At 95% Or Significant Level for Each Independent Variable. 5.2 Interpretation Coefficient of Determination
5.3 Interpretation of F-Test
5.4 Interpretation of Standard Error of Estimate
5.5 Derivation of Demand Curve
5.6 Elasticity of Demand
VE Microwave Products Limited is engaged in designing and manufacturing of high value added Radio Frequency and microwave super components and sub systems findings application in Defense, Space, and Civil communication system.
The major technique that we used in order to extract the data given is by using SPSS program which is by linear regression analysis. Regression analysis includes any techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables that is, the average value of the dependent variable when the independent variables are held fixed. In all cases, the estimation target is a function of the independent variables called the regression function. In regression analysis, it is also of interest to characterize the variation of the dependent variable around the regression function, which can be described by a probability distribution. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables. By using SPSS program, we can identify and analyze the regression result. From there, we can also found the related concept of elasticity being formed. The concept of elasticity is introduced as the tools for measuring the responsiveness of quantity demanded to changes in various factors. The first major section is considered regresiion analysis which is a statistical method for fitting the equation to set the data. It is used for demand estimation and we can analyse the result by using regression analysis. Finally, by using SPSS program, it is easier to identify and analyze the price ticket and the demand which have been effect from various sector. It lead us to get the perfect relationship between the consumption and demand.
3.0 DEMAND ESTIMATION FOR VE MICROWAVE OVENS.
Quantity of VE Microwave Ovens (Q)| Price of VE Microwave Ovens (P)| Price of Competitors (Pc)| Average Annual Household Income (I)| 340| 900| 1140| 21000|
510| 800| 1100| 26000|
440| 800| 900| 24000|
470| 800| 1000| 23000|
555| 700| 800| 30000|
490| 700| 800| 32000|
550| 675| 1000| 33000|
510| 675| 750| 34000|
560| 630| 600| 33000|
610| 630| 650| 31000|
550| 630| 600| 35000|
610| 595| 500| 36000|
580| 595| 550| 39000|
630| 595| 500| 43000|
550| 595| 580| 43500|
590| 625| 650| 43000|
520| 625| 600| 46000|
570| 625| 750| 45000|
Based on the data given and SPSS result, we derive the equation of quantity demanded for VE microwave ovens as follow
Qd = 1347.807 – 1.166P + 0.117Pc – 0.003Y
Qd = Quantity of VE Microwave Ovens.
P = Price of VE Microwave Ovens.
Pc = Price of Competitors.
Y = Average Annual...