**SPSSS Analysis for analyzing the price fluctuations in British Gas**

In order to analyze the factors which are responsible for price fluctuations in the British gas statistics assignment SPSS analysis would be done which will account for the most probable reason responsible for fluctuations in the prices of gas. Some of the major factors which are accountable for fluctuations in price would be adjusted for their permutation and combination as per respondent preferences each profile would be given preference and finally conclusion would be drawn for the factor which influence the price.

In order to analyze the factors which influence the prices of gas for the British Gas we need to do the conjoint analysis. In order to carry out the conjoint analysis we will carry out the following mentioned steps:

**Step 1.Coding**

Factors affecting the prices of British Gas and their probable values

Step 2.ID Generation

Step 2.ID Generation

Cards containing the permutation and combination of the several values of the factors in order to record respondent preferences

**Step 3.Date collection**

Based on the above questionnaire formed respondent responses would be recording from least preferred Id to the most preferred Id. And the responses given by customer in that format would be analyzed with the conjoint analysis in SPSS.

**Step 4.DataAnalysis and result discussion **

**4.1 Conjoint Analysis-Model Description**

**
**The model description table shown above shows the no of level in which each factor of the conjoint Statistics and Analytics has been divided. For example the factor named market driven gas prices are divided into three different –different levels which are Agree, neutral and disagree. The third column of the table shows the relationship f the each factor with the main variable of the analysis i.e. the main factor which is the price fluctuations in British gas industry. Hence all other factors except difference in retail and bulk prices are having the discrete relationship with the variable. Discrete relationship shows there is no definite positive or negative relationship of the variable with the main variable. While linear relationship of some factor with the main factor shows positive or negative relationship with the main factor. Hence Difference in retail and bulk prices is having linear relationship which increased with more fluctuations in the prices of the British Gas.

**4.2 Cramer’s V Statistics**

** Analysis:** The table above shows that there are two major factors which are having better co-relation among itself in comparison to the rest of factors which are present under the main factor.Factors are not all orthogonal. Above table shows Market driven gas prices and demand-supply price determination are having strong correlation (0.71) with all four factors while other three factors are not strongly correlated with other factors as indicated in the table. Hence market driven gas prices and demand supply prices are the most important factors which impact the other sub factors as well as the primary factor which is fluctuation in the overall gas prices in British Gas.

**4.3 Overall Statistics- Part worth Utilities of each factor**

**Analysis: **The table above shows the utility factor for each level of the factors. Hence for above mentioned 5 factors each of the level has certain level of utility which is represented by some positive or negative figure. For every factor the total of utility is coming out to be 0, e.g. for regular price revision factor has two variables i.e. Yes and no. For Yes level utility is positive 0.209 while for No factor utility is -0.209 hence making total sum zero. Hence maximum positive utility value for any factor shows the reason for positive variance in primary factor due to that sub factor.

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**4.4 Importance Values**

**Analysis: **Importance value table provides the major factors wise importance level which affects the overall pricing fluctuations in the British Gas. Hence as shown above in the table that application of demand supply is having maximum importance value followed by government intervention in prices, market driven gas prices, difference in retail and bulk prices and regular price revision. Hence it shows the application of demand supply in Britain is much more and it is the most important phenomenon which affects the prices of gas. Also government intervention is another factor which counts for the 27% variation in the prices of gas while other factors are having small variance in the price fluctuations like Market driven price 15.33%, Difference in retail and bulk price14.85% and Regular price revision 7.49% of the total variation in the prices.

**4.5 Coefficients**

**Analysis: **The table above also confirms the results given by the importance value table as the coefficients for the application of demand and supply is highest among the all given variable. Hence application of demand and supply is determining factor in case of the British gas prices.

**4.6 Correlations (A)**

**Analysis **The above table shows the validity of the model i.e. conjoint analysis which we have applied in order to find out the results for price fluctuations. Hence both Pearson and Kendall’s tau model shows that it is more than 94% valid from both the models.

**Conclusion**

Hence for calculation of price fluctuations in British Gas application of demand supply and government intervention in pricing are the most important factors which drives the phenomenon.