Action Plan for Desklib

Part 1: Action plan
This section presents the action plan for solving each and every issue presented
Action plan for Issue 1:
This issue seeks to determine current average pricing of the accommodation by brands, states,
and locations
The following is the action plan to help solve issue 1;
i) Construct a Pivot Table from the data given (CHL Accommodation Data.xlsx)
ii) Restructure the Pivot Table fields to present the required information.
Action plan for Issue 2:
Determine whether price differentiation exists among the accommodation brands.
The following is the action plan to help solve issue 2;
i) Sort the data by BRAND. Copy and reorganize the data into three columns by brand
name.
Resort Cottage Classic
200.20 201.75 196.11
198.21 201.08 196.22
199.21 199.18 196.86
198.98 201.83 198.49
199.13 202.82 200.11
199.43 204.05 205.52
195.00 200.91 200.63
195.71 202.55 201.89
199.61 203.17 209.65
199.18 197.63 197.16
199.25 200.93 201.02
201.66 202.22 201.96
202.58 203.03 202.73
203.02 203.69 198.66
198.29 204.51 198.85
198.88 201.77 198.90
199.71 202.31 199.31
199.92 202.53 202.17
200.64 198.43 199.45
200.84 201.17 200.72
ii) Hypothesis testing procedure
a) Let u1 = average weekly rate for Resort brand u2 = average weekly rate for Cottage brand u3 =
average weekly rate for Classic brand
H0: u1 = u2 = u3
H1: at least one u is different
b) Level of significance (α) = 0.05

c) If p-value < α, Reject H0.
d) Using Excel data analysis add-inn, a One-Way ANOVA (Single factor) was ran
Action plan for Issue 3:
Determine whether price differentiation exists between states among the accommodation brands.
The following is the action plan to help solve issue 3;
i) Sort the data by STATE. Copy and reorganize the data into three columns by State name.
After sorting by state sort by brand and have the data as follows;

Brand NSW QLD VIC
1 200.2 199.71 199.18
1 198.21 199.92 199.16
1 199.21 200.64 199.38
1 198.98 200.84 199.55
1 199.13 198.58 199.55
1 199.43 199.20 202.50
1 195 199.87 195.66
1 195.71 199.99 195.77
1 199.61 199.45 202.49
1 199.18 204.08 200.26
1 199.25 204.69 197.84
1 201.66 205.99 198.36
1 202.58 206.12 200.58
1 203.02 199.05 200.65
1 198.29 199.49 207.01
1 198.88 202.07 207.01
2 201.75 201.77 203.93
2 201.08 202.31 207.20
2 199.18 202.53 202.65
2 201.83 198.43 198.14
2 202.82 201.17 198.43
iii) Hypothesis testing procedure
a) Three hypotheses are to be tested.
The first hypothesis will test the difference in average price for the three states
Let u1 = average weekly rate for NSW State u2 = average weekly rate for QLD State u3 =
average weekly rate for VIC State
H0: u1 = u2 = u3
H1: at least one u is different
The second hypothesis will test the difference in average price for the three brands
Let u1 = average weekly rate for Resort brand u2 = average weekly rate for Cottage brand
u3 = average weekly rate for Classic brand
H0: u1 = u2 = u3
H1: at least one u is different
The third hypothesis will test the significance of the interaction effect. The hypothesis is;
H0: There is no significant effect of interaction between state and brand on the
average price.
H1: There is significant effect of interaction between state and brand on the
average price.
b) Level of significance (α) = 0.05
c) If p-value < α, Reject H0.
d) Using Excel data analysis add-inn, ANOVA: Two-factor with replication was ran as
follows;

Action plan for Issue 4:
Determine whether price differentiation exists between locations among the accommodation
brands.
The following is the action plan to help solve issue 3;
i) Sort the data by LOCATION. Copy and reorganize the data into three columns by
Location name. After sorting by state sort by brand and have the data as follows;
Brand Metropolitan Cities Regional cities
1 200.20 198.21
1 199.21 199.13
1 198.98 199.43
1 198.29 204.08
1 198.88 199.18
1 199.71 202.50
1 199.92 197.84
1 200.64 200.65
1 200.84 195.00
1 198.58 195.71
1 199.20 199.18
1 199.87 201.66
1 204.69 199.99
1 199.05 199.45
1 199.49 198.36
1 202.07 200.58
1 199.16 199.61
1 199.38 199.25
1 199.55 202.58
1 199.55 203.02
iii) Hypothesis testing procedure
Three hypotheses are to be tested.
The first hypothesis will test the difference in average price for the two locations
Let u1 = average weekly rate for Metropolitan cities u2 = average weekly rate for regional
cities
H0 : μ1=μ2
H1 : μ1 ≠ μ2