Statistics and Decision Analysis: Supermarket Price Comparison

This assignment delves into the statistical analysis of supermarket prices across various locations and stores. It begins with descriptive statistics, examining mean, standard deviation, and other measures to understand price variations among different supermarkets and across states. The analysis extends to comparisons between locations within supermarkets, and specifically focuses on the prices of basic staple baskets in Giant and Tesco stores across different states. Furthermore, the assignment applies statistical tests, particularly the t-test, to determine the significance of price differences. Hypothesis testing is employed to assess whether location significantly impacts average prices. The findings provide insights into price trends, store performance, and the application of statistical tools in retail analysis, with the goal of making informed decisions based on the data.

STATISTIC AND
DECISION ANALYSIS

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
PART 1............................................................................................................................................1
1. Measuring descriptive analysis based on prices at difference supermarkets.....................1
2. Measuring descriptive analysis based or Prices among various states...............................2
3. Measuring Descriptive statistics based on prices at locations among super markets.........3
4. Measuring descriptive statistics based on prices of Tesco stores in states.........................4
PART 2............................................................................................................................................6
1. Application of various Tests to analyse significant differences of average prices.............6
2. Analysing the significant differences in Giant stores at different locations.......................7
3. Ascertaining the differences between Penang and Selangor..............................................8
4. Ascertaining in the significant differences in prices among grocery stores.....................10
5. Measuring the significant differences of average prices across three states....................11
CONCLUSION..............................................................................................................................12
REFERENCES..............................................................................................................................13

INTRODUCTION
The implication of statistic tools in measuring the operational need of identifying the
operations on which it can be said that there have been fruitful identification of all the statistical
analysis. There has been determination of appropriate probability theory which will be adequate
and helpful as per making suitably decisions. In the present assessment there will be analysis
over various supermarkets located at various states. It comprised with the support of descriptive
analysis as well as various statistical tests. Thus, to identify the outcomes it will be appropriate
and adequate as per making suitable changes in the operations. Ascertaining the various
outcomes through identify values like, mean, standard deviation and several tests.
PART 1
1. Measuring descriptive analysis based on prices at difference supermarkets
Ascertaining the differences of prices in each supermarkets as per implicating descriptive
analysis over the data set. Identification of the differences with will be adequate and helpful as
per making suitable determination of the facts (Zhang and et.al., 2018). However, the below
statement will be adequate and helpful as per analysing the differences in the price at various
supermarkets.
Descriptive Statistics:
Price name
Mean 77.5792 Mean 2.5
Standard Error 0.94471 Standard Error 0.10249
Median 81.415 Median 2.5
Mode 60.05 Mode 1
Standard Deviation 10.3488 Standard Deviation 1.12272
Sample Variance 107.098 Sample Variance 1.2605
Kurtosis -0.7795 Kurtosis -1.3667
Skewness -0.8941 Skewness 1.50E-017
Range 32.34 Range 3
Minimum 59.61 Minimum 1
Maximum 91.95 Maximum 4
Sum 9309.5 Sum 300
1

Count 120 Count 120
Interpretation: On the basis of above listed measurement it can be said that there have
been huge differences in the prices and supermarket outcomes. Therefore, on the basis of derived
results on which the average prices of products is 77.58 and standard deviation is of 0.944. Thus,
as per ascertaining the outcomes on which it can be said that there are various prices on which
mean prices are of 77.58, median is 81.41 and mode of 60.05. Similarly, in relation with
analysing the supermarket data set. It brings the outcomes like mean value of 2.5, standard
deviation is of 0.102, median is 2.5 and mode is 1. Thus, as per assessing the data set outcomes it
has been analysed here that Tesco is more capable of using the information rather than other
supermarkets. Considering the standard deviation such as 1.122 on which it can be said that the
most effective operations is being operated by Tesco in various states.
2. Measuring descriptive analysis based or Prices among various states
Determination of differences between supermarkets and states as per basic staple basket
prices. Thus, in relation with this it can be said that there are various outcomes which will be
used to have satisfactory analysis over differences in such variables (Chen and et.al., 2017).
Therefore, addressing the differences between variables such as supermarket and states they
operate which will be analysed as per below listed descriptive analysis.
Descriptive Statistics:
name state
Mean 2.5 Mean 2
Standard Error 0.10249 Standard Error 0.07485
Median 2.5 Median 2
Mode 1 Mode 1
Standard Deviation 1.12272 Standard Deviation 0.81992
Sample Variance 1.2605 Sample Variance 0.67227
Kurtosis -1.3667 Kurtosis -1.5127
Skewness 1.50E-017 Skewness -4.00E-018
Range 3 Range 2
Minimum 1 Minimum 1
2

Maximum 4 Maximum 3
Sum 300 Sum 240
Count 120 Count 120
Interpretation: In consideration with the above listed analysing on which it can be said
that there are differences in the outcomes of supermarkets and the states they operate in. mean
value of name is 2.5 which brings the outcomes that there are comparatively large numbers of
stores of Tesco and Aeon. Similarly, the mean value of states ascertains as 2 which presents the
outcomes as Penang has higher stores in the market than compared to other states. Further, there
has been various tests and the tools used for analysing the fruitful outcomes on which standard
deviation of supermarkets is 1.22 and for states it was 0.8199, sample variance in names as 1.26
and in states it is 0.67 etc. Moreover, in relation with such outcomes on which it can be
demonstrated here that the highest sale of Basic staple basket is in Penang and mainly from
Tesco and Aeon.
3. Measuring Descriptive statistics based on prices at locations among super markets
Ascertaining the differences between prices at various locations and supermarkets which
will be addressed through making adequate analysis over the market value and operational needs
of firm (Frisch and et.al., 2018). Here, in the below listed table there will be demonstration of
descriptive analysis which represents the differences between location and supermarkets.
However, it will be analysed as:
Descriptive Statistics:
name location
Mean 2.5 Mean 1.5
Standard Error 0.10249 Standard Error 0.04583
Median 2.5 Median 1.5
Mode 1 Mode 1
Standard Deviation 1.12272 Standard Deviation 0.5021
Sample Variance 1.2605 Sample Variance 0.2521
Kurtosis -1.3667 Kurtosis -2.0342
Skewness 1.50E-017 Skewness -2.00E-018
3

Range 3 Range 1
Minimum 1 Minimum 1
Maximum 4 Maximum 2
Sum 300 Sum 180
Count 120 Count 120
Interpretation: By considering the outcomes ascertained over the above listed analysis
on which it can be said that there are huge similarity or differences in such variables. Therefore,
as per ascertaining the outcomes derived in the analysis on which it can be said that there are
various elements that have been addressed such as mean value of name is 2.5 and location as 1.5.
It indicates that there are the highest stores of Tesco and Aeon are operating in other places than
metropolitan. Considering the demonstration which brings the suitable analysis over the
outcomes and that will be effective as per analysis the adequate outcomes. Standard deviation of
names is 1.122 and of location is 0.502 it brings the details that there will be appropriate and
equal numbers of stores located in both locations but the outcomes leads Other places.
4. Measuring descriptive statistics based on prices of Tesco stores in states
Ascertaining the changes in prices of basic staple basket in giant stores and in Tesco with
compares to three states. However, in relation with ascertaining the differences in the outcomes
on which it can be said tat there are huge variations in such differences which will be fruitful and
adequate as per making suitable changes in the operational practices (Vahidpour and et.al.,
2018). To analyse the difference there has been ascertainment of descriptive analysis which will
be helpful as per making suitable changes in operational practices.
Descriptive analysis of Giant stores:
Price Giant store state location
Mean 83.296 1 2 1.5
Standard Error 0.0041455856 0
0.00092272
76 0.0005650529
Median 82.37 1 2 1.5
Mode #VALUE! 1 1 1
Standard Deviation 3.731027038 0 0.83045479 0.5085476277
4

85
Sample Variance
13.920562758
6 0
0.68965517
24 0.2586206897
Kurtosis
-
0.0987888508 #DIV/0!
-
1.55357142
86 -2.1481481481
Skewness 0.8261750817 Err:502
1.14850657
719844E-
016
8.20361840856027E
-018
Range 13.88 0 2 1
Minimum 77.77 1 1 1
Maximum 91.65 1 3 2
Sum 2498.88 30 60 45
Count 30 30 30 30
Descriptive analysis of Tesco:
Price Tesco State Location
Mean
82.11233
33333 2 2 1.5
Standard Error
0.002572
7271 0
0.000922727
6 0.0005650529
Median 81.52 2 2 1.5
Mode 81.18 2 1 1
Standard Deviation
2.315454
3508 0
0.830454798
5 0.5085476277
Sample Variance
5.361328
8506 0
0.689655172
4 0.2586206897
Kurtosis
1.188374
1616 #DIV/0!
-
1.553571428
6 -2.1481481481
Skewness 0.374074 Err:502 0.066275839 0.072829043
5

5858 1
Range 11.15 0 2 1
Minimum 77 2 1 1
Maximum 88.15 2 3 2
Sum 2463.37 60 60 45
Count 30 30 30 30
Interpretation: On contrary with the above listed analysis on which it can be said that
there have been various changes in the outcomes of giant stores and Tesco. Thus, the mean value
of prices ion Giant stores are 83.29 while in Tesco it is 82.11. It represents that the sale of basic
Staple Basket comparatively higher is Giant stores. In relation with the mean value as per state
and location Giant has the highest numbers of stores in Penang and location in both Metropolitan
or other places. Similarly, Tesco also have the highest store in Penang and in both locations as
well. Considering the standard deviation in both stores as per their prices on which Giant stores
has 3.73 and Tesco has 2.31. On contrary with such outcomes it can be said that there will be
appropriate analysis over the market and which will be helpful as per bringing the suitable
analysis over operational practices.
PART 2
1. Application of various Tests to analyse significant differences of average prices
Argument based on the issues like there have been variation in the prices of the products
in supermarkets in each locations. Thus, to address the appropriate outcomes there will be
ascertainment of adequate operations which will be fruitful as per having suitable analysis over
the market (Cywińska and et.al., 2018). On contrary with such operations there have been
preparation of various hypothesis which will be addressed through implicating the tests like T-
test analysis. However, to address the significant differences between average price and locations
there have been proper administration of the outcomes such as:
Hypothesis 1
Null hypothesis (H0): There will be no significant difference in the mean value of
average prices as per locations.
6

Alternative hypothesis (H1): There will be a statistical significant difference in the
mean value of average prices as per locations.
t-Test: Paired Two Sample for Means
Price location
Mean 77.57916667 1.5
Variance 107.0978413 0.2521008
Observations 120 120
Pearson Correlation -0.003994593
Hypothesized Mean Difference 0
df 119
t Stat 80.42137741
P(T<=t) one-tail 7.0929E-106
t Critical one-tail 1.657759285
P(T<=t) two-tail 1.4186E-105
t Critical two-tail 1.980099853
Interpretation: On the basis of above applied tests which ascertains the differences
between lactation and average prices implied over product which brings various outputs. The
mean value of prices are 77.57 and location has 1.5. Therefore, it can be said that there are large
number of stores are located in the other places than metropolitan. In relation with variance
analyse the prices have variance of 107.09 while location has 0.252. Pearson correlation between
the variables is 0.00399, Differences is of 119, t statistics as 80.42, P value One tail is 7.09.
Thus, it indicates that the T<=t it indicates that the P value is higher such as 7.09 and 1.41 both
are more than 1 therefore there will be a significant relation between prices and locations. Thus,
alternative hypothesis will be followed here as it brings the outcomes that as per location of
stores changes there has v\been changes in the prices took place accordingly. Moreover, it will
be said that the changes in the prices of products took place as per variation in the location. It is
due to economic variation in each places which bounds the firm in making pricing changes in
each locations.
2. Analysing the significant differences in Giant stores at different locations
To address the appropriate outcomes based on analysing the variation in the outcomes
which represent that there have been changes in the numbers of giant stores in different location.
The argument likes over the context is that there have been changes in the prices as per Giant
store's location in various places (Zhang and et.al., 2018). To address the significant relationship
7

between such variables there will be preparation of various techniques to resolve the outcomes
and make appropriate analysis over the market.
Hypothesis
Null hypothesis (H0): There is no significant difference of average prices of Giant stores
in different locations.
Alternative hypothesis (H1): There is a significant difference of average prices of Giant
stores in different locations.
t-Test: Two-Sample Assuming
Unequal Variances
prices location
Mean 83.296 1.5
Variance 13.92056 0.258621
Observations 30 30
Hypothesized Mean Difference 0
df 30
t Stat 118.9781
P(T<=t) one-tail 5.47E-42
t Critical one-tail 1.697261
P(T<=t) two-tail 1.09E-41
t Critical two-tail 2.042272
Interpretation: By considering the above outcomes which bring the acknowledgement
of significant variations in prices and locations. To address the appropriate outcomes there will
be ascertainments of mean value of prices as 83.26 while locations as 1.5. Similarly, as per
addressing the variances of the elements on which prices has 13.92 while locations has 0.2586.
The differences took place as per addressing truth of the outcomes. In relation with the P values
on which P(T<=t) On tail is 5.47E-42 and P(T<=t) Two tail is 1.09E-41 IT addresses that these
values are lower than 1. Thus, here it can be said that will be consideration of Null hypothesis. It
represents that changeset in the value of Giant store are not based on locations. Moreover, it can
8

be said that there is no significant difference of average prices of Giant stores in different
locations. Variations in the locations does not affect the average prices at Giant stores.
3. Ascertaining the differences between Penang and Selangor
Implication of various statistical measurements in addressing the outcomes based on
differences in the average prices of staple basket in Penang and Selangor. Thus, to address the
adequacy over the outcome on which it can bes aid that there are various operations which will
be helpful as per addressing the outcomes (Chen and et.al., 2017). However, in relation with
addressing the relationship between both the states as peer average prices changes there will be
implication of various tests which will be helpful as per addressing the outcomes.
Hypothesis:
Null hypothesis (H0): Mean price of basic Staple basket in Penang is not significantly
different compared to the in Selangor.
Alternative hypothesis (H1): Mean price of basic Staple basket in Penang is statistically
significantly different compared to the in Selangor.
T-Test
Group
Statistics
states N Mean Std. Deviation Std. Error Mean
pricecharged Selangor 40 77.0135 9.92860 1.56985
Penang 40 77.6408 10.84615 1.71493
Independent sample t test
Levene's
Test for
Equality
of
Variance
s
t-test for Equality of Means
9

F Sig. t df Sig.
(2-
tailed
)
Mean
Differenc
e
Std. Error
Differenc
e
95%
Confidence
Interval of the
Difference
Lower Upper
pricecharge
d
Equal
variance
s
assumed
.170 .68
1
-.27
0 78 .788 -.62725 2.32495
-
5.2558
7
4.00137
Equal
variance
s not
assumed
-.27
0
77.39
8 .788 -.62725 2.32495
-
5.2564
4
4.00194
Interpretation: Addressing the adequate outcomes on which it can be said that there are
various analysis which will be appropriate as per demonstrating the fruitful outcomes. Hence,
implicating T-Test statistics as per group statistics which ascertains that mean value as 77.01 for
Selangor and 77.64 for Penang. Similarly, the standard deviation of the variables is 9.92 for
Selangor and 10.84 for Penang. However, as per addressing the outcomes there have been huge
variations in the operations of business in both the locations.
As per determining the significant value of the test and the data set brings the adequate
outcomes which represents here as 0.681. The idol value of significance is needed to be >0.05.
Moreover, here the outcome derived has 0.681 which states there will be scarification to the
Alternative hypothesis. H1 states that Mean price of basic Staple basket in Penang is statistically
significantly different compared to the in Selangor. However, it will be effective determination of the
analysis which in turn will be useful and appropriate as per bringing the suitable outcomes. Thus, the
prices in Penang is significantly different from Selangor.
4. Ascertaining in the significant differences in prices among grocery stores
Addressing the concrete reasons behind the outcomes and the variable is that there has
been larger buying power of supermarket chains which offers the cheaper rates to their buyers.
Thus, to attract the consumers, implication of this strategy is quiet common (Frisch and et.al.,
2018). Moreover, in relation with the demonstrating the differences there will be various analysis
which are as follows.
10