Computing Analysis: Relationship between Variables

This document provides an analysis of the relationship between different variables in computing. It explores the impact of ingredient X, ship choice, and country on payment amounts. The document includes tables, figures, and statistical tests to test claims and discuss the findings.

COMPUTING ANALYSIS

TABLE OF CONTENTS
(A) Relationship between the fields (variables) “How much ingredient X?” and “How much
would they pay?”.............................................................................................................................1
(B) Relationship between the fields (variables) “Which ship?” and “How much would they pay?”
..........................................................................................................................................................1
(C) Relationship between the fields (variables) “Which country?” and “How much would they
pay?”................................................................................................................................................2
(D) Relationship between the fields (variables) “Which country?” and “which ship”....................3
(E) Sample proportion of customers from country A, if the hypothesis p=0.9 is true....................4
(F) Sample proportion of customers from country A, if the hypothesis p=0.5 is true.....................5
(G) 95% confidence interval for the average of the variable “How much would they pay?...........5
(H) 95% confidence interval for the average of the variable “How much would they pay?” if the
hypothesis they are on ship B is true...............................................................................................6
(I) Paste in the output for testing the claim there is a relationship between the variables “How
much ingredient X?” and “How much would they pay?”................................................................6
(J) Paste in the output for testing the claim there is a relationship between the “Which ship?” and
“Amount they would pay?”.............................................................................................................8
(K) Paste in the output for testing the claim there is a relationship between the “Which country?”
and “Amount they would pay?”.......................................................................................................9
(L) Paste in the output for testing the claim there is a relationship between the “Which country?”
and “which ship?”..........................................................................................................................11
(M) Discussion of topics................................................................................................................13
(N) Relevancy of topic...................................................................................................................13
(O) Comment on report formatting................................................................................................13
REFERENCES..............................................................................................................................................14
Figure 1Relationship between ingredient and pay...........................................................................1
Figure 2Ships comparison in respect to variable pay......................................................................2
Figure 3Country comparison in respect to pay................................................................................3

Figure 4Ships across nations...........................................................................................................4
Figure 5Ingredient and pay..............................................................................................................8
Figure 6Histogram...........................................................................................................................8
Figure 7Histogram...........................................................................................................................9
Figure 8Histogram.........................................................................................................................10
Figure 9Histogram.........................................................................................................................10
Figure 10Histogram.......................................................................................................................12
Figure 11Histogram.......................................................................................................................12
Table 1Correlation table..................................................................................................................1
Table 2Payment across nations........................................................................................................2
Table 3Statistics of ship A and B....................................................................................................3
Table 4Sample proportion calculation.............................................................................................4
Table 5Sample proportion calculation if hypothesis p = 0.5 is true................................................5
Table 6CI level for variable pay......................................................................................................5
Table 7CI for variable pay if hypothesis is true..............................................................................6
Table 8Relationship between ingredient and pay............................................................................6
Table 9Sample statistics for ship and amount pay...........................................................................8
Table 10T stat and p value for ship and amount pay.......................................................................8
Table 11Sample statistics for country and amount pay...................................................................9
Table 12T stat and p value for country and amount pay...............................................................10
Table 13Sample statistics for country and ship.............................................................................11
Table 14T statistics for country and ship.......................................................................................12

(A) Relationship between the fields (variables) “How much ingredient X?”
and “How much would they pay?”
Table 1Correlation table
How much Ingredient X?
How much would they
pay?
How much Ingredient X? 1
How much would they pay? -0.994164713 1
Figure 1Relationship between ingredient and pay
Interpretation
On basis of table given above it can be observed that correlation value is -0.99 which is
indicating that there is negative correlation between variables. Scatter plot given above indicate
that with increase in ingredient pay value decrease significantly.
(B) Relationship between the fields (variables) “Which ship?” and “How
much would they pay?”
Table 2Average of variable pay across ships
Row Average of How much would they
1

Labels pay?
Ship B 25.07407407
Ship A 25.84782609
Grand
Total 25.43
X1-X2 0.773752013
Figure 2Ships comparison in respect to variable pay
Interpretation
There is slight difference between the amount people pay across both ships. This is
evidenced from the table given above. It can be said that on this front there is no difference
between ships.
(C) Relationship between the fields (variables) “Which country?” and “How
much would they pay?”
Table 2Payment across nations
Row
Labels
Average of How much would they
pay?
country A 25.32222222
country B 25.55652174
2

Grand
Total 25.43
X1-X2 0.234299517
Figure 3Country comparison in respect to pay
Interpretation
If variable payment is analyzed in context of countries then in that case it can be observed
that there is not a big difference in average value of variable pay across nation.
(D) Relationship between the fields (variables) “Which country?” and “which
ship”
Table 3Statistics of ship A and B
Row Labels
Count of which
ship?
country A 27
Ship B 17
Ship A 10
country B 23
Ship B 10
Ship A 13
Grand Total 50
3

Difference in ships between both
country 4
Difference in ship A between both
country 3
Difference in ship B between both
country 7
Figure 4Ships across nations
On basis of table given above it can be observed that there is difference of 4 ships between
countries. In respect to ship A there is difference of 3 ships across both nations. On other hand,
in respect to ship B there is difference of 7 ships between both nations.
(E) Sample proportion of customers from country A, if the hypothesis p=0.9 is
true
Table 4Sample proportion calculation
Row Labels
Sum of which
sample
Country A 7614
Country B 6486
Grand Total 14100
4

Country A proportion 0.54
Standard error of sample
proportion 1.7617E-05
0.539970051
0.540029949
On basis of table given above it can be said that sample proportion from country A is
between 0.53 to 0.54.
(F) Sample proportion of customers from country A, if the hypothesis p=0.5 is
true
Table 5Sample proportion calculation if hypothesis p = 0.5 is true
Row Labels
Sum of which
sample
Country A 7614
Country B 6486
Grand Total 14100
Country A proportion 0.54
Standard error of sample
proportion 1.7617E-05
0.539965471
0.540034529
On basis of table given above it can be said that sample proportion from country A is around
0.54.
(G) 95% confidence interval for the average of the variable “How much
would they pay?
Table 6CI level for variable pay
Confidence
Level 95%
Ship A
n 23
Mean 25.848
Std Dev 2.65173521
RESULTS
5

SE 0.553
t 2.074
Margin of
Error 1.147
Lower Limit 24.701
Upper Limit 26.995
Results are indicating that for variable payment upper and lower limit is 24.71 and 26.99.
This range is obtained at 95% confidence interval.
(H) 95% confidence interval for the average of the variable “How much
would they pay?” if the hypothesis they are on ship B is true.
Table 7CI for variable pay if hypothesis is true
Confidence
Level 95%
Ship B
n 27
Mean 25.074
Std Dev 3.17678994
RESULTS
SE 0.611
t 2.056
Margin of
Error 1.257
Lower Limit 23.817
Upper Limit 26.331
Results are indicating that for variable payment upper and lower limit is 23.81 and 26.33.
This range is obtained at 95% confidence interval.
(I) Paste in the output for testing the claim there is a relationship between the
variables “How much ingredient X?” and “How much would they pay?”
Table 8Relationship between ingredient and pay
t-Test: Two-Sample Assuming Equal Variances
How much How much would they
6

Ingredient X? pay?
Mean 1.4606 25.43
Variance 0.089165 8.663776
Observations 50 50
Pooled Variance 4.37647
Hypothesized Mean
Difference 0
df 98
t Stat -57.2882
P(T<=t) one-tail 1.84E-77
t Critical one-tail 1.660551
P(T<=t) two-tail 3.67E-77
t Critical two-tail 1.984467
Figure 5Ingredient and pay
Value of p 3.67>0.05 which is indicating that with change in ingredient significant
difference does not come in price.
(J) Paste in the output for testing the claim there is a relationship between the
“Which ship?” and “Amount they would pay?”
Table 9Sample statistics for ship and amount pay
sample statistics
7

xbar1 xbar2 s1 s2 n1 n2
25.0741 25.8478 3.17679 2.7 27 23
Figure 6Histogram
Figure 7Histogram
Table 10T stat and p value for ship and amount pay
Test stat and p-value calculation paste this into
assignment
(the word file) and add a comment
Estimate
xbar1-xbar2
-0.77375
8

standard error of estimate xbar1-xbar2
0.82432
t test stat df two sided pvalue
-0.93865 47 0.35271
To calculate the p-value H0:μ1=μ2 is assumed to be
true
since the test is two sided H1 is H1:μ1≠μ2
Value of level of significance is 0.35>0.05 which is reflecting that there is no significant
difference between both variables. Means that both variables move in same direction.
(K) Paste in the output for testing the claim there is a relationship between the
“Which country?” and “Amount they would pay?”
Table 11Sample statistics for country and amount pay
sample statistics
xbar1 xbar2 s1 s2 n1 n2
25.3222 25.5565 3.16669 2.7 27 23
Figure 8Histogram
9

Figure 9Histogram
Table 12T stat and p value for country and amount pay
Test stat and p-value calculation paste this into
assignment
(the word file) and add a comment
Estimate
xbar1-xbar2
-0.2343
standard error of estimate xbar1-xbar2
0.83293
t test stat df two sided pvalue
-0.2813 47 0.77972
To calculate the p-value H0:μ1=μ2 is assumed to be
true
since the test is two sided H1 is H1:μ1≠μ2
Value of level of significance is 0.77>0.05 which is reflecting that there is no significant
difference between both variables. Means that with change in country amount pay change at
same rate.
(L) Paste in the output for testing the claim there is a relationship between the
“Which country?” and “which ship?”
Table 13Sample statistics for country and ship
sample statistics
10

xbar1 xbar2 s1 s2 n1 n2
1.62963 1.43478 0.4921 0.5 27 23
Figure 10Histogram
Figure 11Histogram
Table 14T statistics for country and ship
Test stat and p-value calculation paste this into
assignment
11

(the word file) and add a comment
Estimate
xbar1-xbar2
0.19485
standard error of estimate xbar1-xbar2
0.14191
t test stat df two sided pvalue
1.373 46 0.17641
To calculate the p-value H0:μ1=μ2 is assumed to be
true
since the test is two sided H1 is H1:μ1≠μ2
Value of level of significance is 0.17>0.05 which is reflecting that there is no significant
difference between both variables. Means that with change in ship variable does not change
significantly.
(M) Discussion of topics
 Demography: In Australia total population 25.4% people are those whose ancestors are
from mentioned nation. 25.9% people have English ancestors. 7.5% Scottish and 3.3%
are Irish (Goldstone, 2018). Thus, demography of Australia is diversified. Due to this
reason specific region people like Indian clashes happened with Australians due to
different colour of religion etc. This is very serious matter of concern for Australia which
need to be taken in to account.
 Cruise ships: Cruise ship tourism is increasing at rapid pace but it is also affecting
natural environment negatively. As per study conducted normal human being have more
carbon footprint on Cruise then on land (Pratt. and et.al., 2015). Hence, pollution is
increasing at rapid rate through cruise which need to be controlled.
(N) Relevancy of topic
There is no relevancy of topic’s because first one is related to demographic factors. Second
one is related to cruise which is different from ship. Hence, both topics have no relevant to ship
or data analysed above.
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(O) Comment on report formatting
It is observed that report is not in proper format for example tables and graphs are not
labelled in proper manner. Moreover, file is not structured in systematic way like header of sub
section can be placed in heading 1 or heading 2. Thus, there is need to restructure file in proper
manner. Apart from this, unnecessary facts given in descriptive statistics table must also be
removed so that on single glance user can ready all relevant facts.
13

REFERENCES
Books and journals
Goldstone, J.A., 2018. Demography, environment, and security. In Environmental conflict (pp.
84-108). Routledge.
Pratt, G. and et.al., 2015. Traffic, air pollution, minority and socio-economic status: addressing
inequities in exposure and risk. International journal of environmental research and public
health. 12(5). pp.5355-5372.
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