Statistics: Analysis of Website Visits and Sales for QA Company

This report analyzes the website visits and sales data for a QA company. It provides insights into the trends and patterns observed in the data, and makes recommendations for improving sales.

Statistics
Business intelligence and data visualization
Student name:
Tutor name:
1 | P a g e

Statistics
Executive summary
Similar to some other enterprise QA company in its operations faces competition from different
corporations which might be producing similar products. So as to grow its sales through
widening its market, it established an internet site in which customers would learn more about
the organization. Diverse records have been kept about what took place in the internet site over a
time frame. These records were analyzed and presented in form of tables and graphs. The
consequences confirmed that variety of specific visits to the website become excessive between
February and March. However, sales and the wide variety of pounds bought over the period
seemed not to enhance. This become glaring as earnings have been handiest excessive for the
duration of the pre-promotion length and then it decreased. The research recommends to the
management of QA to give you other marketing avenues aside from the website to power
income. They must also allow customers to location orders thru the website as the research has
installed that there are many individuals who visit the website.
2 | P a g e

Statistics
QUESTION ONE
Descriptive statistics
Unique visits to the QA website per week
May 25 - May 31
Jun 15 - Jun 21
Jul 6 - Jul 12
Jul 27 - Aug 2
Aug 17 - Aug 23
Sep 7 - Sep 13
Sep 28 - Oct 4
Oct 19 - Oct 25
Nov 9 - Nov 15
Nov 30 - Dec 6
Dec 21 - Dec 27
Jan 11 - Jan 17
Feb 1 - Feb 7
Feb 22 - Feb 28
Mar 15 - Mar 21
Apr 5 - Apr 11
Apr 26 - May 2
May 17 - May 23
Jun 7 - Jun 13
Jun 28 - Jul 4
Jul 19 - Jul 25
Aug 9 - Aug 15
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
Figure 1. Unique Visits to the QA website
per week
Figure 1
The bar graph above shows the frequency of unique visits to QA website per week from May
25th 2008 to August 15th 2009. It can be observed that the number of unique visits to the website
was high between February 1st and April 11th. This is after a decline was observed from May 25th
to around December 21st 2008. To add on, another decline in the number of visits to the website
starts from February 22nd 2009 to 15th August 2009.
Revenue over time per week
3 | P a g e

Statistics
May 25 - May 31
Jun 22 - Jun 28
Jul 20 - Jul 26
Aug 17 - Aug 23
Sep 14 - Sep 20
Oct 12 - Oct 18
Nov 9 - Nov 15
Dec 7 - Dec 13
Jan 4 - Jan 10
Feb 1 - Feb 7
Mar 1 - Mar 7
Mar 29 - Apr 4
Apr 26 - May 2
May 24 - May 30
Jun 21 - Jun 27
Jul 19 - Jul 25
Aug 16 - Aug 22
$0
$200,000
$400,000
$600,000
$800,000
$1,000,000
Figure 2. Revenue over time per
week
Figure 2
The figure above is of graph of revenue got by QA per week over a period of time. as can be
observed, no particular pattern can be seen from the frequencies. It can be said that the
frequencies for the revenue per week is relatively uniform throughout the period.
Profit over time per week
May 25 - May 31
Jun 22 - Jun 28
Jul 20 - Jul 26
Aug 17 - Aug 23
Sep 14 - Sep 20
Oct 12 - Oct 18
Nov 9 - Nov 15
Dec 7 - Dec 13
Jan 4 - Jan 10
Feb 1 - Feb 7
Mar 1 - Mar 7
Mar 29 - Apr 4
Apr 26 - May 2
May 24 - May 30
Jun 21 - Jun 27
Jul 19 - Jul 25
Aug 16 - Aug 22
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
Fig. 3. Profit over time per week
Figure 3
The figure above is of graph of profit got by QA per week over a period of time. As can be
observed, there is a general decline of the profits from the beginning of the period towards the
end of the period. However, the profits seem to pick up from June 19th 2009 towards the end.
4 | P a g e

Statistics
Pounds over time per week
May 25 - May 31
Jun 22 - Jun 28
Jul 20 - Jul 26
Aug 17 - Aug 23
Sep 14 - Sep 20
Oct 12 - Oct 18
Nov 9 - Nov 15
Dec 7 - Dec 13
Jan 4 - Jan 10
Feb 1 - Feb 7
Mar 1 - Mar 7
Mar 29 - Apr 4
Apr 26 - May 2
May 24 - May 30
Jun 21 - Jun 27
Jul 19 - Jul 25
Aug 16 - Aug 22
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Fig. 4. Lbs. Sold overtime per week
Figure 4
The figure above is of graph of pounds sold by QA per week over a period of time. As can be
observed, there is a no any particular pattern over the period. The number of pounds sold over
the period can be said to be uniformly distributed.
QUESTION TWO
Visit and financial summary measures – initial period
Visits
Unique
visits Revenue Profit
Lbs.
Sold
Mean 1,055 976 608,250 200,233 18,737
Median 899 846 586,170 208,913 17,270
Std. dev
355.033
3
319.597213
9
155930.39
7
60691.5
5
5427.39
3
Minimu
m 626 594 274,568 62,580 8,633
Maximu
m 1,632 1,509 890,077 275,218 28,053
Table 1
Visit and financial summary measures – Pre-promotion period
5 | P a g e

Statistics
Visits
Unique
visits Revenue Profit
Lbs.
Sold
Mean 563 517 534,314 159,932 18,441
Median 558 510 534,542 152,476 17,215
Std. dev
80.8711
8
70.9391422
6
150502.8
2
42682.6
8
5965.6
3
Minimu
m 383 366 315,647 100,388 8,992
Maximu
m 795 734 951,216 273,175 31,969
Table 2
Visit and financial summary measures – Promotion period
Visits
Unique
visits Revenue Profit
Lbs.
Sold
Mean 1,814 1,739 456,399 131,930 17,113
Median 1,663 1,585 413,937 114,328 17,299
Std. dev
758.101
7 743.025339
161741.09
9
47776.8
5
6519.07
1
Minimu
m 1,000 930 268,160 81,841 7,814
Maximu
m 3,726 3,617 897,164 266,477 31,496
Table 3
Visit and financial summary measures – Post promotion period
Visits
Unique
visits Revenue Profit
Lbs.
Sold
Mean 857 801 371,728 111,046 14,578
Median 848 800 348,397 104,530 13,647
Std. dev
70.8885
5
72.3561475
5
145728.33
4
49065.2
7
5941.55
6
Minimu
m 772 709 133,967 32,825 3,826
Maximu
m 963 912 615,950 206,441 23,762
Table 4
6 | P a g e

Statistics
QUESTION THREE
The means of visits, unique visits, revenue, profits and pounds sold for four periods
Means
Visits
Unique
visits
Revenu
e Profits
Lbs.
Sold
Initial 1,055 976 608,250 200,233 18,737
Pre-
promotion
562.952
4
516.809523
8
534313.
5 159932
18440.7
7
Promotion 1,814 1,739 456,399 131,930 17,113
Post-
proportion
856.571
4
800.785714
3 371728
111045.
8
14577.7
9
Table 5
QUESTION FOUR
Summary of findings in 2 and 3
The table 1 above shows the results of summary statistics for visits, unique visits, revenue,
profits and pounds sold for the initial period. The mean, median, standard deviation, minimum
and maximum values for visits per week were 1055, 899, 355.03, 626 and 1632 respectively. The
mean, median, standard deviation, minimum and maximum values for unique visits per week
were 976, 846, 319.597, 694 and 1509 respectively. The mean, median, standard deviation,
minimum and maximum values for revenue per week were 608250, 586170, 155930.397,
274568 and 890077 respectively. The mean, median, standard deviation, minimum and
maximum values for profit per week were 200233, 208913, 60691.55, 62580 and 275218
respectively. Lastly, the mean, median, standard deviation, minimum and maximum values for
pounds sold per week were 18737, 17270, 5427.39, 8633 and 28053 respectively.
The table 2 above shows the results of summary statistics for visits, unique visits, revenue,
profits and pounds sold for the pre-promotion period. The mean, median, standard deviation,
minimum and maximum values for visits per week were 553, 558, 80.87, 383 and 795
respectively. The mean, median, standard deviation, minimum and maximum values for unique
visits per week were 517, 510, 70.93, 366 and 734 respectively. The mean, median, standard
deviation, minimum and maximum values for revenue per week were 534314, 534542,
7 | P a g e

Statistics
150502.82, 315642, and 951216 respectively. The mean, median, standard deviation, minimum
and maximum values for profit per week were 159932, 152476, 42682.68, 100388 and 273175
respectively. Lastly, the mean, median, standard deviation, minimum and maximum values for
pounds sold per week were 18441, 17215, 5965.63, 8992 and 31969 respectively.
The table 3 above shows the results of summary statistics for visits, unique visits, revenue,
profits and pounds sold for the promotion period. The mean, median, standard deviation,
minimum and maximum values for visits per week were 1814, 1663, 758.10, 1000 and 3726
respectively. The mean, median, standard deviation, minimum and maximum values for unique
visits per week were 1739, 1585, 743.02, 930 and 3617 respectively. The mean, median,
standard deviation, minimum and maximum values for revenue per week were 456399, 413937,
161741.099, 268160, and 897164 respectively. The mean, median, standard deviation, minimum
and maximum values for profit per week were 131930, 114328, 47776.85, 81841 and 266477
respectively. Lastly, the mean, median, standard deviation, minimum and maximum values for
pounds sold per week were 17113, 17229, 6519.07, 7814 and 31496 respectively.
The table 4 above shows the results of summary statistics for visits, unique visits, revenue,
profits and pounds sold for the post promotion period. The mean, median, standard deviation,
minimum and maximum values for visits per week were 857, 848, 70.89, 772 and 963
respectively. The mean, median, standard deviation, minimum and maximum values for unique
visits per week were 801, 800, 72.35, 709 and 912 respectively. The mean, median, standard
deviation, minimum and maximum values for revenue per week were 371728, 348397,
145728.33, 133967 and 615950 respectively. The mean, median, standard deviation, minimum
and maximum values for profit per week were 111046, 104530, 49065.27, 32825 and 206441
respectively. Lastly, the mean, median, standard deviation, minimum and maximum values for
pounds sold per week were 14578, 13647, 5941.56, 3826 and 23762 respectively.
It can be observed from table 5 that the mean number of visits during the initial, pre-promotion,
promotion and post promotion periods were 1055, 562.95, 1814 and 856.57. The mean number
of unique visits during the initial, pre-promotion, promotion and post promotion periods were
976, 516.81, 1739 and 800.79. The mean number of revenue during the initial, pre-promotion,
promotion and post promotion periods were 608250, 53431.5, 456339 and 371728. The mean
number of profits during the initial, pre-promotion, promotion and post promotion periods were
200233, 159932, 131930 and 111045.8. Lastly, the mean number of pounds sold during the
initial, pre-promotion, promotion and post promotion periods were 18737, 18440.77, 17113 and
14577.79
RELATIONSHIP BETWEEN VARIABLES
QUESTION FIVE
8 | P a g e

Statistics
Correlation coefficient between revenue and pounds sold.
Revenu
e
Lbs.
Sold
Revenue 1
Lbs.
Sold
0.86893 1
Table 6
From my intuition, there is a positive relationship between revenue and pounds sold. This is
because any number of pounds sold can only increase the amount of revenue and not decrease.
Scatterplot of revenue versus pounds sold
0 5,000 10,000 15,000 20,000 25,000 30,000 35,000
$0
$100,000
$200,000
$300,000
$400,000
$500,000
$600,000
$700,000
$800,000
$900,000
$1,000,000
f(x) = 24.5679059575216 x + 69380.9472593738
R² = 0.755038845893767
Scatterplot of revenue vs pounds sold
Pounds sold
Revenue
Figure 5
The correlation coefficient r, between revenue and pounds sold is 0.87. This indicates that there
is a strong and positive relationship between the two variables. The scatterplot above also depicts
a linear relationship with a high value of R-squared (0.76).
Question six
Correlation of revenue versus visits
Visits Revenue
Visits 1
9 | P a g e

Statistics
Revenu
e
-0.0593 1
Table 7
Scatterplot of revenue versus visits
0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000
$0
$100,000
$200,000
$300,000
$400,000
$500,000
$600,000
$700,000
$800,000
$900,000
$1,000,000
f(x) = − 15.970543633977 x + 512241.046258343
R² = 0.00352738952999587
Scatterplot of revenue vs visits
Visits
Revenue
Figure 6
I expect this plot to be positively linear. However, it is linear but not positive. The value of
correlation coefficient is -0.06. This indicates a very weak linear relationship in the negative
direction.
Number seven
Summary of results
The correlation coefficient r, between revenue and pounds sold is 0.87. This indicates that there
is a strong and positive relationship between the two variables. The scatterplot above also depicts
a linear relationship with a high value of R-squared (0.76).
The relationship between visits and revenue were expected to be positive, however, it is linear
but not positive. The value of correlation coefficient is -0.06. This indicates a very weak linear
relationship in the negative direction.
10 | P a g e

Statistics
Number eight
a. Summary statistics for Lbs. sold from January 3, 2015 to January 19, 2010
Results table
Lbs. Sold
Mean
18681.5551
7
Median 17673
Standard
Deviation 6840.50794
Minimum 3826
Maximum 44740
Table 8
The summary statistics for pounds sold is as shown in the table above. The mean Lbs sold was
18681.56 while the median and the standard deviation were 17,673 and 6840.51. The minimum
and maximum number of Lbs sold was 3826 and 44740 respectively.
b. Histogram for Lbs. sold from January 3, 2015 to January 19, 2010
11 | P a g e

Statistics
Figure 7
c. It can be observed that the Lbs. sold distribution is bell-shaped. The distribution depicts a
perfect normal distribution.
d. The empirical rule table
Table of results
Interval
Theoretical % of
data
Theoretical no. of
observations
Actual no. of
observations
Mean ± 1 std dev 68% 197 201
Mean ± 2 std dev 95% 276 276
Mean ± 3 std dev 99% 287 288
Table 9. The values in the table have been rounded off to nearest whole number.
e. Refined analysis
Interval
Theoretical no. of
obs Actual no. of obs
Mean - 1 std dev 99 117
Mean + 1 std dev 99 84
1 std dev to 2 std dev 138 35
-1 std dev to .-2 std
dev 138 40
12 | P a g e

Statistics
2 std dev to 3 std dev 144 11
-2 std dev to -3 std
devn 144 3
Table 10
f. How well does the data follow normal distribution can be determined by observing the
number of actual observations within the negative and the positive intervals. For example
how many actual observations are in the interval between 1 standard deviation and 2
standard deviations? These numbers should be equal on both sides of the symmetry of the
normal curve. However, in this case, the numbers are not equal. For example 11 and 3 for
the interval between 2 standard deviation and 3 standard deviations positive side and
negative side respectively. So I can conclude in this respect that the data is not perfectly
normally distributed.
g. Skewness and kurtosis of the data
Table of results
Lbs. Sold
Mean 18681.55517
Standard Error 401.6884574
Median 17673
Mode 14905
Standard Deviation 6840.50794
Sample Variance 46792548.87
Kurtosis 0.563661442
Skewness 0.632307485
Range 40914
Minimum 3826
Maximum 44740
Sum 5417651
Count 290
Table 11
13 | P a g e

Statistics
From the summary statistics above, we can see that the skewness value is 0.63. This indicates
that the data is positively skewed. It has a longer tail to the right. However, it is not much skewed
since 0.63 is close to 0 (zero). When it comes to kurtosis, we can see that its value is 0.56, this
means that the distribution is platykurtic; the tail of the distribution is short and thin. To add on,
the distribution has a lower and broader peak.
Question nine
Comparison of the pounds sold and daily visit distribution
From the summary statistics of the visits attached, we can see that the skewness value is 2.17
compared to that of pounds sold which is 0.63. This indicates that the data of visits is more
positively skewed than that of pounds sold. It has a longer tail to the right than the data of pounds
sold. Thus we conclude that the distribution of visits data is so much skewed to the right than the
distribution of pounds sold. When it comes to kurtosis, we can see that the kurtosis for number
of visits is 5.86 compared to 0.56 for number of pounds. This means that the distribution visits is
more kurtic than that of pounds sold. Its curve has a higher and sharper peak.
Question ten
Graph of distribution of visits by traffic source
Referring Sites Search Engines Direct Traffic Other
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
38,754
20,964
9,709
4
Distribution of visits by traffic source
Figure 8
14 | P a g e

Statistics
The graph above shows the distribution of visits by traffic source. It can be observed that most
traffic came from referrals which were 38,754. The least number came from direct traffic which
was 9709. Only 4 sources were not specified.
Graph of distribution of visits by referring sites
googleads.g.doubleclick.net
pagead2.googlesyndication.com
sedoparking.com
globalspec.com
freepatentsonline.com
thomasnet.com
mu.com
mail.google.com
psicofxp.com
0
4,000
8,000
12,000
16,000 15,626
8,044
3,138
693 582 389 379 344 337 310
Distribution of visits by referring sites
Figure 9
15 | P a g e

Statistics
The graph above shows the distribution of visits by referral sites. It can be observed that most
referral sites were googleads.doubleclick.net (15,626) while the least referrals sites were
psicofx.com (310).
Graph of distribution of visits by search engine
google yahoo search msn aol ask live bing voila netscape
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000 17,681
1,250 592 424 309 268 145 122 63 26
Distribution of visits by search engine
Figure 10
The graph above shows the distribution of visits by search engine. It can be observed that most
used search engine was google (17,681) while the least used search engine was netscape (26).
Graph of distribution of visits by geographic sources
16 | P a g e

Statistics
South America
Northern America
Central America
Western Europe
Eastern Asia
Northern Europe
Southern Asia
South-Eastern Asia
Southern Europe
Eastern Europe
0
5,000
10,000
15,000
20,000
25,000 22,616
17,509
6,776 5,214 3,228 2,721 2,589 1,968 1,538 1,427
Distribution of visits by Geographic
Sources
Figure 11
The graph above shows the distribution of visits by geographic sources. It can be observed that
most visits came from South America (22,616) while the least visits came from Eastern Europe
(1,427).
Graph of distribution of visits by top 10 browsers
17 | P a g e

Statistics
Internet Explorer
Firefox
Opera
Safari
Chrome
Mozilla
Netscape
Konqueror
SeaMonkey
Camino
0
10,000
20,000
30,000
40,000
50,000
60,000 53,080
13,142
938 850 792 478 47 31 24 9
Distribution of visits by browser type
Figure 11
The graph above shows the distribution of visits by browser type. It can be observed that most
used browser was internet explorer (53,080) while the least used browser was Camino (9).
Graph of distribution of visits by top 10 operating systems used.
Windows
Macintosh
Linux
(not set)
iPhone
SymbianOS
FreeBSD
iPod
Playstation 3
Playstation Portable
0
20,000
40,000
60,000
80,000 67,063
1,184 1,045 48 29 20 18 8 4 3
Distribution of visits by operating
system used
Figure 12
18 | P a g e

Statistics
The graph above shows the distribution of visits by operating system used. It can be observed
that most used operating system was windows (67,063) while the least used operating system
was playstation portable (3).
19 | P a g e