Relationship between Region and Amount Paid for Version 1

This report analyzes the relationship between different regions and the amount of money they would pay for version 1 of the laptops. It provides insights into the average, maximum, minimum, and standard deviation of the amount paid for version 1. The report also includes a graph comparing the amount paid for version 1 and version 2, as well as a test of the claim that people would pay more than $900 for version 1 on average. Additionally, it discusses other variables such as hard disk capacity, laptop generation, core processor, and lurking variables that can influence laptop preferences.

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Running head: BUSINESS STATISTICS
Business Statistics
Student Name
Institution Name

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BUSINESS STATISTICS
a. Relationship between “which region” and “how much you would buy version 1”
Row Labels Average of how much would
they pay for version 1?
A 1016.8
B 1054.4
Grand Total 1035.6
The above table shows the average amount of money the regions will buy version 1. The
average region B will buy version 1 is $1054.4 which is higher than region A which will buy
version 1 with an average amount of $1016.8. Both the regions will pay for version 1 an average
amount of $1035.6
Row Labels Max of how much would they
pay for version 1?
A 1198
B 1255
Grand Total 1255
The above table shows that region A paid a maximum of $1198 which is less than
maximum of region B which paid a maximum of $1255. The maximum from both regions is
$1255
Row Labels Min of how much would they
pay for version 1?
A 800
B 819
Grand Total 800
The above table shows that region B is willing to pay more minimum amount of $819
compared to region A who paid minimum amount of $800. From both the regions, the minimum
amount is $800

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Row Labels StdDev of how much would
they pay for version 1?
A 128.3347027
B 118.5726334
Grand Total 124.3682216
The above table shows the variations among the amount paid for version 1 between the
regions. Region A shows wide variation with a standard variation of 128.33 while the variation
of region B is 118.57 and the overall standard deviation is 124.368
From the tables we can see that region B welcomed version 1 compared to region A.
b. Graph
1
5
9
13
17
21
25
29
33
37
41
45
49
53
57
61
65
69
73
77
81
85
89
93
97
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
How much they pay for version 1 vs How much they pay for
version 2
how much would they pay for version 1? how much would they pay for version 2?
Index
Amount
When we plot the line graph of the two variables, we get the above graph. From the graph
we can see the people from both the region that is, region A and region B, would pay more for
the version 2 more than they would pay for version 1 of the laptops.
When “How much paid for version 1” is regressed against “How much paid for version 2” we
find the relationship between them is linear.

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$600 $800 $1,000 $1,200 $1,400
$0
$500
$1,000
$1,500
X Variable 1 Line Fit Plot
Y
Predicted Y
X Variable 1
Y
c. Which version against version 1
Row Labels Average of how much would
they pay for version 1?
N 1023.575758
Y 1041.522388
Grand Total 1035.6
The above table shows the average amount of money those who would pay more for
version 1 or not. The average amount those who would pay more for version 1 is 1041.522 while
the average amount those who wouldn’t pay more is 1023.58. For both those who would pay
more and those who wouldn’t, the average come to 1035.6.
Row Labels Max of how much would they
pay for version 1?
N 1253
Y 1255
Grand Total 1255
The above table shows the maximum amount for those who would pay more is 1255
while the maximum for those who wouldn’t pay more is 1253.
Row Labels Min of how much would they
pay for version 1?

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N 801
Y 800
Grand Total 800
The above table shows the minimum amount for those who would pay more for version 1
is 800 while the minimum for those who wouldn’t pay more for version 1is 801.
Row Labels StdDev of how much would
they pay for version 1?
N 140.564716
Y 116.2473015
Grand Total 124.3682216
The above table shows the standard deviation for those who would pay more for version 1 is
116.25 while for those who wouldn’t pay more for version 1 is 140.56.
d. Confident interval of proportion for people who would pay more for version 1 (Białek,
2015); (Wang, Reich & Horton, 2019).
Row Labels Count of how much would
they pay for version 1?
N 33
Y 67
Grand Total 100
CI = ^p± z . √ ^p ( 1− ^p )
n
^p= x
n , wherex=67 ∧n=100 , p=0.67 , z=1.96

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∴ CI=0.67 ±1.96 √ 0.67 ( 1−0.67 )
100
CI =0.67 ± 1.96 √ 0.002211
CI =0.67 ± 0.092
CI = ( 0.578,0 .762 )
e. Test the claim that people would pay more than $900 for version 1 on average.
Row Labels Average of how much would they pay
for version 1?
N 1023.575758
Y 1041.522388
Grand Total 1035.6
Row Labels StdDev of how much would they pay
for version 1?
N 140.564716
Y 116.2473015
Grand Total 124.3682216
H0 : μ=$ 900
H1 : μ> $ 900
z= x−μ
σ
z= 1041.52−900
116.25

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z= 141.52
116.25
z=1.217
From the z tables, z=1.217 is within the acceptance region, −1.96 ↔1.96we therefore reject
the null hypothesis and conclude that people will pay more than average of $900
f. To get the relationship between “which region” and “How much they would pay for
version1” we use the Mann-Whitney U test
From excel we rank the variable “how much they would pay for version 1” by;
=RANK(B3,$B$3:$B$102,1)
We then use the function SUMIF() to get the totals from region A totals from region B
U A =SUMIF ( A 3 : A 102, “ A ” , E 3: E 102 )=2321
‘
U B=SUMIF ( A 3 : A 102, A ,E3:E102 ) =2716
U A =R1− n1 ( n1 +1 )
2
U B=R2− n2 ( n2 +1 )
2
U A =2321− 50 ( 50+1 )
2 =1046
U B=2716−50 ( 50+1 )
2 =1491
U =min ( U A , UB ) =1042

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g. To get the relationship between “which region” and “How much they would pay for
version1” we use the Mann-Whitney U test (Zhao & Ding-Geng, 2018);( Corder &
Foreman, 2009).
From excel we rank the variable “how much they would pay for version 1” by;
=RANK(B3,$B$3:$B$102,1)
We then use the function SUMIF() to get the totals from region A totals from region B
U A =SUMIF ( A 3 : A 102, “ A ” , E 3: E 102 ) =2321
‘
U B=SUMIF ( A 3 : A 102, A ,E3:E102 ) =2716
U A =R1− n1 ( n1 +1 )
2
U B=R2− n2 ( n2 +1 )
2
U A =2321− 50 ( 50+1 )
2 =1046
U B=2716−50 ( 50+1 )
2 =1491
U =min ( U A , UB ) =1042
h. Some other variables
a. Hard disk capacity
Hard disk is memory disk which is capable of storing information in the computer.
Different laptops have different sizes. Some have capacity of 1TB, 500GB, 320GB, 160GB etc.
These size of the laptops also affects the taste of people towards them. The prices of the laptops

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are likely to increase with the increase of their hard disk capacity and since people like laptops
with higher capacity. they will go for the laptops with higher disk capacity even if they are
expensive. When the companies make the laptops with higher capacity, they will be bought even
if they are expensive (Bugnion, Nieh and Tsafrir 2017); ( El Zein and Rendell, 2010).
b. The generation of the laptops.
The generation of the laptops can also influence the marketing of the laptops. The
generation in a laptop enables it to load faster or slower when connected to the internet. The
generation differs in different laptops and it ranges from one to five (Chen, et al., 2017). The
higher the generation of a laptop, the faster it will load when connected to the internet. As the
generation goes high there is a likelihood that the price will go up. People prefer to buy the
laptops with higher generation even if they are expensive. This can also affect the way people
view the laptops meaning they will be sold even if they are expensive (Falsafi & Wenisch, 2014).
c. Core processor
Core processor is another feature in the laptops which can affect the taste of laptop lovers.
Core processor generally affect how the computer carryout the normal computer processing. As
the core processor of the laptop increase, the price of the laptops also increases. Laptops with
higher processor are expensive than those with low processor. People who need laptops to do a
lot of worker will require laptops with high core processor meaning they will go for the high
price laptops.
i. Lurking variable.
Lurking variable is a variable that is not included under explanatory variable or dependent
variable but it can bring effect in the interpretation in the relationship between dependent and
independent variables. Lurking variables may lead to make a wrong conclusion on the
relationship between variables especially it can show that there is a strong relationship between
independent variables and dependent variables or it can simply hide the relationship between
variables and show that there is no relationship at all between variables.
For example, the relationship between the proportion of people who would pay more for
version 1 of the laptop, it clear that high proportion of people will pay more for version 1. There
are two variables being compared here, those who will pay more and version 1 of the laptop. The

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relationship between these two variable can be seen to be very strong, but the data is clearly
examined, it id found that the relationship between the two variables cannot be that strong.
Therefore, there must be a variable which was not considered during the creation of the model
which influence the reason why high proportion prefer laptop of version 1. For example, the
reason why people can go for an expensive laptop is due to their speed and storage capacity.
Since the researcher did not consider the storage capacity in his research and the storage capacity
influenced the laptop preference, storage capacity becomes our lurking variable(García-
Belmonte & Ventosa-Santaulària, 2011) (Sabbaghi & Huang, (2018).
j. Report
From the data there are four variables researcher used; “which region”, “how much would you
pay from version 1”, “how much you would pay for version 2” and “would you pay for version
1”. When the relationships between these variables are developed, it is found that the people
from region B have higher average Amount of money they would pay for the version 1 of the
laptops compared to average amount of money region A would for the same version of the
laptop. For the manufacturer, therefore, it is advisable to manufacture to supply version 1 of the
laptops to region B than they would supply version 1 to region A. this option has higher return
than if they supply more to region A than region B
From the confident interval of the proportion of people who would pay more for version 1, the
total number of people who would pay more for version 1 is high compared to the people who
won’t pay more for the version 1. It clearly shows the version 1 of the laptop is preferred by
many people and they are willing even to pay more for it. This can be a greater advantage for the
manufacturer to make more of version 1. From the graph, in question b, it is also clear that the
prices of version 1 of the laptop were higher than the prices of the version 2 of the laptop. It,
therefore, means that the version 1 of the laptop will sell even with the high prices. Company
XYZ can therefore focus much attention in manufacturing version 1 of the laptops and mainly
supply them to region B.
Company XYZ can also consider adding more features in the laptops manufactured. Features
like high hard disk capacity, high core Intel processor and the generation of the laptops can
attract customers to the laptops.

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