Data Analysis and Visualization Report

This assignment focuses on analyzing and visualizing data related to visitor trends. It involves calculating actual, past forecast, and future forecasts for various quarters. The data includes visitor counts categorized as families, groups, and others. The report utilizes column graphs to effectively represent these trends over time.

STATISTICS

TABLE OF CONTENTS
PART 1............................................................................................................................................3
a........................................................................................................................................................3
(i) Analysis of the histogram.......................................................................................................3
(ii) Drawing histogram and evaluating the shape of it................................................................3
b. Nominal and ordinal data.........................................................................................................5
PART 2............................................................................................................................................5
a. Descriptive statistics................................................................................................................5
c....................................................................................................................................................8
(A). Difference between mean and median.................................................................................8
(B). Ogive graph..........................................................................................................................9
PART 3..........................................................................................................................................10
a. Trend line for prediction........................................................................................................10
b. Explaining the reasons due to which values are not forecasted.............................................12
c. Assessing the model that is used for data presentation..........................................................13
d.................................................................................................................................................13
c. Constructing graph to show the data of visitors.....................................................................14
...................................................................................................................................................14
REFERENCES..............................................................................................................................16

PART 1
a.
(i) Analysis of the histogram
Interpretation
It can be seen from the image given above that there are 10 respondents that are making
expenditures in range of 250 to 300. Apart from this, there is 16 respondents that are making
expenditure in range of 300 to 350. There are 14 respondents which state that on average basis
they are making expenditure in range of 350 to 400. It can be seen that with increasing in
expenditure 400 to 450 number of people making an expenditure declined from 14 to 9. At same
pace further reduction is observed in the number of customers at price range of 450 to 500.
Same trend is observed in case of next price level and on this basis it can be said that with
increase in price level number of people making expenditure will decline sharply.
(ii) Drawing histogram and evaluating the shape of it
Number of Families
250-
300 10
300- 16

350
350-
400 14
400-
450 9
450-
500 7
500-
550 5
550-
600 2
Results are reflecting that in the price range of £300 to 350 overall there are sixteen
families that are making expenditure. It is identified that on the tour package that are devised by
the Orion tours there are 14 families that are prepared to make expenses in range of £350-400.
On comparisons of both figures it can be seen that with elevation in the level of expenses of price
of package lead to reduction in number of people traveling at higher package. One of the most
interesting fact is that most of the respondents state that they are making expenditure in range of
£250 to £400. This means that if firm will price its tour package above this level then in that case
it can receive less number of customers in its business. There are less number of customers that
are making expenditure more than 450 to 600. Thus, tour company must price its product within
range of 250 to 400.

b. Nominal and ordinal data
 Nominal data: Nominal data refers to the data that is in the discrete form. It refers to the
variables names that are in categorical form (Newbold, Carlson and Thorne, 2012). For
example in the specific question of questionnaire there are two variables like male and
female then same will be considered as nominal data. Ordinal data: Ordinal data refers to the scale that is in sequence form and all components
of scale reveal different things. For example in ordinal scale likert scale components are
used like strongly agree, agree, neutral, disagree and strongly disagree in specific
sequence. All these things arranged in the specific sequence in the questionnaire. Thus,
same are known as ordinal data.
Do you think that people are satisfied from the Orion Tour?
 Satisfied ()
 Highly satisfied ()
 Neutral ()
 Dissatisfied ()
 Highly dissatisfied ()
Respondent’s response on asked question
Particulars Frequency
Satisfied 18
Highly satisfied 25
Neutral 12
Dissatisfied 4
Highly dissatisfied 2
Total 61
PART 2
a. Descriptive statistics
Class interval Number of Families CF X FX
250-300 10 10 275 2750

300-350 16 26 325 5200
350-400 14 40 375 5250
400-450 9 49 425 3825
450-500 7 56 475 3325
500-550 5 61 525 2625
550-600 2 63 575 1150
Total 63 305 2975 24125
Standard deviation and quartiles
Class interval Number of Families CF X FX x^2 Fx^2
250-300 10 10 275 2750 75625 756250
300-350 16 26 325 5200 105625 1690000
350-400 14 40 375 5250 140625 1968750
400-450 9 49 425 3825 180625 1625625
450-500 7 56 475 3325 225625 1579375
500-550 5 61 525 2625 275625 1378125
550-600 2 63 575 1150 330625 661250
Total 63 242 2400 24125 1334375 9659375

It means that frequency has been increased in terms of variable from 63 to 70 which is
revealed from the table given below:
CI (class interval) X(Middle value) Frequency (F) FX
250-300 275 10 2750
300-350 325 16+1 = 17 5525
350-400 375 14+1 = 15 5625
400-450 425 9+1 = 10 4250
450-500 475 7 +2 = 9 4275
500-550 525 5+1 = 6 3150
550-600 575 2+1 = 3 1725
2975 70 27300
Mean: (27300/70)
= 390
Mean value is 390 and this reflects that most of people are making expenditure in range of
350 to 400.
c.
(A). Difference between mean and median
There is a huge difference between the statistical tools which are mean and median. Mean is
the tool that reflects the mean performance of the specific variable. Median is the statistical tool
that is classifying entire data set in to multiple parts (Heron, 2012). Thus, it can be said that both
statically tools are different from each other. It can be seen from the calculations that are given
above that mean value of the variable 383GBP which means that there majority if respondents

that are prepared to pay mentioned amount on the tour packager. Median value is only
369.64GBP and it is the value that is dividing entire set of values in to two multiple parts. 50%
of data lie above this median value and 50% of same is below median value. It can be observed
that there is higher number of frequency of families at low price of tour package. On other hand,
there is a low number of people of frequency at higher price range of the tour package. It can be
said that firm must sale its product at low price in the market to the customers.
(B). Ogive graph
Class
intervals Mid-value Frequency
Relative
frequency
Cumulativ
e frequency
Cumulative relative
frequency
250-300 275 10 0.16 10 16%
300-350 325 16 0.25 26 41%
350-400 375 14 0.22 40 63%
400-450 425 9 0.14 49 78%
450-500 475 7 0.11 56 89%
500-550 525 5 0.08 61 97%
550-600 575 2 0.03 63 100%
63
Results are reflecting that there are 89% of respondents who state that they
usually make an expenditure in range of 250-500. There are only 10% respondents who are
making expenditure above price range of 500-600.

PART 3
a. Trend line for prediction
Number of families visiting theme park
2014
(1) 200
2014(2) 400
2014(3) 540
2014(4) 300
2015
(1) 200
2015
(2) 400
2015
(3) 530
2015
(4) 300
2016
(1) 220
2016
(2) 400
2016
(3) 560
2016 310

(4)
2017
(1) 250
2017
(2) 400
2017
(3) 373
2017
(4) 375
2018
(1) 377
2018
(2) 379
2018
(3) 381
2018
(4) 379
Linear trend line

It can be concluded that there is number of people visiting theme park is fluctuating
consistently. In future also same trend can be observed in respect to theme park. In case of the
financial year 2017 it can be observed that in Q3 and Q4 total number of visitors may 373 and
375. Apart from this, in case of the year 2018 the total number of visitors for Q1 may be 377, for
Q2 will be 379, same for Q3 may be nearby to 381 and finally for Q4 value of the variable will
be 379. It can be concluded that in the upcoming time period number of customers will increase
in the Theme park.
b. Explaining the reasons due to which values are not forecasted
Accurate trend cannot be forecast by using trend line method because it is not advanced
that can be used for making prediction in the business. One must use regression model to analyze
the variables and making accurate prediction.

c. Assessing the model that is used for data presentation
In the trend analysis method regression equation is used to make a prediction. It must be
noted that tend line is simply using regression equation but it does not reflect entire values of the
regression model in the chart.
d.
Year Quarter Actual Forecast Past Forecast Future
2014 Q1 200 200.0
Q2 400 400.0
Q3 540 540.0
Q4 300 300.0
2015 Q1 200 200.0
Q2 400 400.0
Q3 530 530.0
Q4 300 300.0
2016 Q1 220 220.0
Q2 400 400.0
Q3 560 560.0
Q4 310 310.0
2017 Q1 250 250.0
Q2 400 400.0 400.0
Q3 373.2
Q4 375.2
2018 Q1 377.3

c. Constructing graph to show the data of visitors
Families Group Other
Quarter
1 250 65 52
Quarter
2 405 130 95
Quarter
3 575 145 106
Quarter
4 290 105 80
.

There are some specific reasons due to which column graph is selected in the present
research. It must be noted that column graph reveal the variables data on horizontal and vertical
axis. Thus, by taking a look at chart interpretation can be done in better way.

REFERENCES
Books and journals
Heron, M., 2012. Deaths: leading causes for 2008. National Vital Statistics Reports: From the
Centers for Disease Control and Prevention, National Center for Health Statistics, National
Vital Statistics System. 60(6). pp.1-94.
Newbold, P., Carlson, W. and Thorne, B., 2012. Statistics for business and economics. Pearson.