Data Analysis and Decision Modeling

This study material covers the topic of data analysis and decision modeling. It includes an action plan for data analysis, hypothesis formation, ANOVA tests, and the impact of pricing on brand. It also discusses the influence of location, state, and comfort level on brand pricing.

Data analysis and decision
modeling

Contents
Part 1................................................................................................................................................3
Part 2................................................................................................................................................3
Part 3................................................................................................................................................3

Part 1
Action plan
In order to analyse and interpret data the action plan is as follows :
1. Sorting data by brand and recognizing it with brand name
Resort Cottage Classic
198 191 199
201 192 197
200 195 192
2. By forming of hypothesis
It is assumed that average price of resort brand is p1
It is assumed that average price of cottage brand P2
It is assumed that average price of classic brand P3
3. Now, significance value is identified = 0.05
4. So, if value of P is more than 0.05 that reject null hypothesis
5. The Anova tests is run with turkey Kramer process
6. Then, decision rule is applied for analysis and making conclusion
Part 2
Part 3
It is important to communicate finding of Mr Oscar so that it is identified whether pricing is
influencing on brand or not. Also, it can be analyzed whether null or alternate hypothesis is
accepted or rejected. Besides, affect of decision rule can be interpreted as well. Therefore, one by

one resuof each issue is been discussed. Hence it is summarized that in issue one the there is
difference in current pricing among brands, state and location. Also, it is found that average
pricing in all brands is 200. However , it only varies on basis of certain point. Along with it,
brand state and locations does not influence in price of brand. Thus, there average is similar to
each other. There is change in things on how brand pricing is done on basis of its location.
However, in issue 2 it is found that as each brands are allowed to set their own price. So, there is
different between brand price but only to some extent. It means that in in resort brand it is 201.32
whereas in cottager brand it is 201.64 and in classic brand it is 201.65. thus, rise in brand the
pricing also rises. Moreover, price of classic brand is highest among them. Therefore, Mr. Oscar
data info is right as price between brands are different. Here, in ANOVA test it has been
identified that P value is .637 which is more than significant value. Thus, null hypothesis is
rejected as which means that there is no change in average pricing even if each brand is allowed
to charge their prices according.
In addition, in issue 3 it is found that there is there is price difference in 3 states as well. This is
because of state factor affect on pricing of resort, cottage and classic brand. So, it is identified
that that in in NSW it is 1.97. whereas in QLC it is 2.32 and in VIC it is 2.92. in this issue the
ANOVA test result state that P value generated is .708 which is more than P = 0.05. therefore,
mr Oscar can analyze that there is null hypothesis is rejected. It means that state factor does not
influence in pricing of brand. Usually, there is no little change in price of it.
In issue 4 it is analysed that Mr. Oscar wants to find out whether price difference exist at location
or not within brands. Therefore, from data it is found that at location there is slight variation in
price between brand. The first location it is 1.50 and in second it is 1.51. so, it is similar in both.
Furthermore, the price remains same of all brans that is of resort brand it is 201.32 whereas in
cottager brand it is 201.64 and in classic brand it is 201.65. hence, there is no influence of
location on brand pricing. In this ANOVA test result interpreted that P value is more than 0.05
that is .870. this means that there is no change in price even if location is changed. So, there is no
difference in price in both locations. The brands are able ot make things easy and allow in
establishing at various locations. There are many ways of how brand price can be influenced.

In the last issue that is 5 it is evaluated that introducing comfort brand has increased in internal
competition but only to some limited extent. It has also influenced on pricing of brand but they
have remained same. However, as comfort level increases there is rise in price of brand. In this
classic brand price is highest and there is change other brand pricing as well. So, when comfort
level increases within brand it enforces other brand to rise their prices as well. So, it is clearly
analysed that even if brand price is high then as well comfort level has to be high. Besides,
pricing of brand does not increase to great extent. Furthermore, that null hypothesis is rejected. It
means there is no difference is increase in competition even if comfort level rises. Here, P value
obtained is .890 which is more than P = 0.05.
So, from above it can be concluded that brand pricing is not influenced due to location, state etc
if they are allowed to set on their own. But there is somewhat difference found in comfort level
and its impact of competition within brand. If there is any change in comfort level even if pricing
of brand is low this result in rise in competition. This is because other brands start to increase
price as well on basis of comfort level. It lead to issue in it and making change in average pricing
of all brands.