Beer Brand Analysis

This assignment involves the analysis of nutritional data for 145 beer brands. It requires calculating descriptive statistics, constructing visualizations such as box plots and normal probability (Q-Q) plots to understand the distribution of alcohol percentage, calories, and carbohydrates across different brands. The goal is to evaluate whether these values are normally distributed or not.

Statistics

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
(a) Constructing a box plot..........................................................................................................1
(b) Constructing a histogram.......................................................................................................3
(c) Comparing data characteristics to theoretical properties.......................................................7
(b) Constructing a normal probability plot (quantile - quantile plot)........................................15
CONCLUSION..............................................................................................................................17
REFERENCES..............................................................................................................................18

INTRODUCTION
Business statistics may be swerved as a science that facilitates good decision making at
the time of uncertainty. By employing the tool of business statistics analyst can perform financial
analysis and solve issues related to econometrics, auditing, production as well as operations.
Further, normal distribution is the main parts of probability which in turn clearly reflects the
extent to which values are above or below the average level. Mean and standard deviation is the
main elements of such bell curve graph. The present report is based on the data set of domestic
beer which will provide deeper insight about several statistical tools such as box plot, histogram
and quantile-quantile (QQ plot).
(a) Constructing a box plot
Box plot is the standard way of presenting data set on the basis of five key numbers such
as minimum, maximum, Q1, Q3 and median. Hence, box plot method helps in depicting group of
data graphically through the means of quartiles. Such plots also provide high level of assistance
in indicating or showing variability that is outside the upper or lower quartiles (Box or Whisker
Plot, 2017). Further, by using or creating box plots one can present the variations which take
place in a sample of statistical population without making any assumption of statistical
distribution. In this, difference which takes place dispersion of
Particulars Alcohol % Calories Carbohydrates
Median 4.9 151.0 12.1
Quartile 1 4.4 129.0 8.6
min 0.4 55.0 1.9
max 11.5 330.0 32.1
quartile 3 5.6 166.0 14.6
mean 5.2 154.7 12.1
Alcohol %

0
1
2
3
4
5
6
Alchol%
n= 145
Bin range
Calories
0
1
2
3
4
5
6
7
8
9
10
Calories
n= 145
Bin range
Carbohydrates

0
20
40
60
80
100
120
140
160
180
200
Carbohydrates
n= 145
Bin range
Interpretation: The above depicted box plot clearly shows that in the case of alcohol%
mean and median accounts for 5.2 & 4.9%. Besides this, quartile 1 and 2 of data set implies for
4.4% & 5.6%. Range of alcohol % is g 11.1% significant which is the difference of higher and
lower value. Referring such box plot, it can be stated that data set does not fall into the category
of normal standard distribution. Moreover, in the case of normal standard both lower and upper
whisker is equal. Hence, it can be seen in the above box plot that lower whiskers of alcohol % is
higher as compared to upper so it is not considered as normal standard distribution.
Along with this, data of calories and carbohydrates does not consider as normally standard
distributed. Moreover, box plot of calories presents that lower whisker is longer than the upper one.
Descriptive statistics of data set pertaining to calories show that Q1, Q2 and Q3 are 129.0, 121.1 & 166
significantly. Further, minimum and maximum value of data set is 55 & 330. On the other side, data set of
carbohydrates exhibits that minimum and maximum value is 1.9 and 32.1 respectively. Further, it has
assessed from evaluation that average and median value of carbohydrates is similar such as 12.41. In
addition to this, tabular presentation shows that value of carbohydrates is increased from 1st quarter to the
3rd one. Hence, considering the situation of box plot, it can be mentioned that data of calories and
carbohydrate does not have normal standard distribution.
(b) Constructing a histogram
Histogram is the most effectual tool that presents the distribution of numerical data set
and helps in understanding the same. It presents estimated probability distribution of a
continuous variable. For constructing histogram, it is highly required for analyst to determine the

bin values that represents the division of entire range into a series of intervals. Hence, histogram
facilitates structured presentation of large data set and helps in decision making. Symmetric and
non-symmetric are the main two situations that histogram presents on the basis of data set needs
to be assessed (Histograms, 2017). Under symmetric distribution, two parts of the histogram
shows highly perfect representation in relation to each other. On the other, non-symmetric
distribution is also known as skewed one that does not present mirror imaging. Under skewed
distribution, there is one tail that attracted our in relation the next tail.
Alcohol % Frequency
0.4 1
1.3 0
2.3 0
3.2 2
4.1 10
5.0 78
6.0 30
6.9 7
7.8 8
8.7 4
9.7 2
10.6 2
More 1

0.4 1.3 2.3 3.2 4.1 5.0 6.0 6.9 7.8 8.7 9.7 10.6 More
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
Histogram
Frequency
Bin
Frequency
Calories Frequency
55 1
78 2
101 8
124 23
147 27
170 49
193 12
215 10
238 8
261 0
284 1
307 1
More 3

55 78 101 124 147 170 193 215 238 261 284 307 More
0
5
10
15
20
25
30
35
40
45
50
55
Histogram
Frequency
Bin
Frequency
Carbohydrates Frequency
2 1
4 8
7 15
9 17
12 23
14 43
17 19
20 9
22 6
25 2
27 1
30 0
More 1

2 4 7 9 12 14 17 20 22 25 27 30 More
0
5
10
15
20
25
30
35
40
45
50
Histogram
Frequency
Bin
Frequency
Interpretation: By preparing histograms, it has assessed carbohydrate element of most of
the brands be fall on the right side of mean such as 12.1 significantly. By considering this, it can
be presented that data set is positively skewed. Along with this, histogram of alcohol % and
calories also clearly shows that large number of brands fall into the right side which in turn
clearly presents that data set comes under the category non-symmetric distribution.
(c) Comparing data characteristics to theoretical properties.
Alcoho
l % Ranks
Percentil
e of
Alcohol
%
Z
score
of
Alcoho
l %
0.4 1 0.00345 -

2.7018
2.4 2 0.01034
-
2.3136
2.8 3 0.01724
-
2.1144
3.8 4 0.02414
-
1.9749
3.8 4 0.02414
-
1.9749
3.9 6 0.03793
-
1.7752
4.1 7 0.04483
-
1.6972
4.1 7 0.04483
-
1.6972
4.1 7 0.04483
-
1.6972
4.1 7 0.04483
-
1.6972
4.1 7 0.04483
-
1.6972
4.1 7 0.04483
-
1.6972
4.1 7 0.04483
-
1.6972
4.1 14 0.0931
-
1.3219
4.2 15 0.1
-
1.2816
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069 -

1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.2 16 0.1069
-
1.2432
4.3 29 0.19655 -0.854
4.3 29 0.19655 -0.854
4.3 29 0.19655 -0.854
4.3 29 0.19655 -0.854
4.4 33 0.22414
-
0.7583
4.4 33 0.22414
-
0.7583
4.4 33 0.22414
-
0.7583
4.4 33 0.22414
-
0.7583
4.4 33 0.22414
-
0.7583
4.5 38 0.25862
-
0.6476
4.5 38 0.25862
-
0.6476
4.5 38 0.25862
-
0.6476
4.5 38 0.25862
-
0.6476
4.6 42 0.28621
-
0.5645
4.6 42 0.28621
-
0.5645
4.6 42 0.28621
-
0.5645
4.6 42 0.28621
-
0.5645
4.6 46 0.31379
-
0.4851
4.7 47 0.32069
-
0.4658
4.7 48 0.32759
-
0.4466

4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.7 49 0.33448
-
0.4276
4.8 61 0.41724 -0.209
4.8 62 0.42414
-
0.1913
4.8 62 0.42414
-
0.1913
4.8 62 0.42414
-
0.1913
4.8 62 0.42414
-
0.1913
4.8 62 0.42414
-
0.1913
4.8 62 0.42414
-
0.1913
4.9 68 0.46552
-
0.0865
4.9 68 0.46552
-
0.0865
4.9 68 0.46552
-
0.0865
4.9 68 0.46552
-
0.0865

4.9 68 0.46552
-
0.0865
4.9 68 0.46552
-
0.0865
4.9 74 0.5069
0.0172
9
4.9 75 0.51379
0.0345
8
4.9 75 0.51379
0.0345
8
4.9 75 0.51379
0.0345
8
4.9 75 0.51379
0.0345
8
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.0 79 0.54138
0.1039
1
5.1 92 0.63103
0.3345
9
5.1 92 0.63103
0.3345
9
5.1 92 0.63103
0.3345
9

5.2 95 0.65172
0.3899
8
5.2 95 0.65172
0.3899
8
5.2 95 0.65172
0.3899
8
5.2 95 0.65172
0.3899
8
5.3 99 0.67931
0.4657
7
5.4 100 0.68621
0.4851
3
5.5 101 0.6931
0.5046
7
5.5 101 0.6931
0.5046
7
5.5 101 0.6931
0.5046
7
5.5 101 0.6931
0.5046
7
5.6 105 0.72069
0.5848
9
5.6 105 0.72069
0.5848
9
5.6 105 0.72069
0.5848
9
5.6 105 0.72069
0.5848
9
5.6 105 0.72069
0.5848
9
5.6 105 0.72069
0.5848
9
5.8 111 0.76207
0.7129
7
5.8 112 0.76897
0.7354
4
5.8 112 0.76897
0.7354
4
5.9 114 0.78276
0.7815
4
5.9 114 0.78276
0.7815
4
5.9 114 0.78276
0.7815
4
5.9 114 0.78276
0.7815
4

5.9 114 0.78276
0.7815
4
5.9 114 0.78276
0.7815
4
5.9 114 0.78276
0.7815
4
5.9 114 0.78276
0.7815
4
6.0 122 0.83793
0.9859
9
6.0 122 0.83793
0.9859
9
6.1 124 0.85172
1.0438
6
6.5 125 0.85862
1.0741
4
6.6 126 0.86552
1.1054
5
6.7 127 0.87241
1.1378
8
6.8 128 0.87931
1.1715
5
6.9 129 0.88621 1.2066
7.0 130 0.8931 1.2432
7.0 130 0.8931 1.2432
7.1 132 0.9069
1.3218
8
7.4 133 0.91379
1.3644
9
7.5 134 0.92069
1.4097
3
7.8 135 0.92759
1.4580
5
7.8 135 0.92759
1.4580
5
8.0 137 0.94138
1.5664
6
8.1 138 0.94828
1.6283
6
8.1 138 0.94828
1.6283
6
8.3 140 0.96207
1.7752
2
9.2 141 0.96897 1.8658
9.6 142 0.97586 1.9749

3
9.9 143 0.98276
2.1143
8
10.5 144 0.98966 2.3136
11.5 145 0.99655 2.7018
Calori
es
Carbohydra
tes Calories
Carbohydra
tes
Calori
es
Carbohydra
tes
55 1 1.9 1
3.448E-
03 0.00345
-
2.701
8
-
2.70179862
8
64 2 2.4 2
1.034E-
02 0.01034
-
2.313
6
-
2.31360033
7
70 3 2.6 3
1.724E-
02 0.01724
-
2.114
4
-
2.11438077
2
94 4 2.6 3
2.414E-
02 0.01724
-
1.974
9
-
2.11438077
2
95 5 3.1 5
3.103E-
02 0.03103
-
1.865
8
-
1.86580276
4
95 5 3.2 6
3.103E-
02 0.03793
-
1.865
8
-
1.77521696
9
95 5 3.2 6
3.103E-
02 0.03793
-
1.865
8
-
1.77521696
9
96 8 3.2 6
5.172E-
02 0.03793
-
1.628
4
-
1.77521696
9
98 9 3.5 9
5.862E-
02 0.05862
-
1.566
5
-
1.56645823
3
98 9 5.3 10
5.862E-
02 0.06552
-
1.566
5
-
1.51003504
3
99 11 5.5 11
7.241E-
02 0.07241 -1.458
-
1.45804700
9
103 12 5.7 12
7.931E-
02 0.07931
-
1.409
7
-
1.40972571
2

103 12 5.8 13
7.931E-
02 0.08621
-
1.409
7
-
1.36448874
8
104 14 5.9 14
9.310E-
02 0.0931
-
1.321
9
-
1.32188365
3
105 15 6.0 15
1.000E-
01 0.1
-
1.281
6
-
1.28155156
6
110 16 6.2 16
1.069E-
01 0.1069
-
1.243
2
-
1.24320282
1
110 16 6.2 16
1.069E-
01 0.1069
-
1.243
2
-
1.24320282
1
110 16 6.2 16
1.069E-
01 0.1069
-
1.243
2
-
1.24320282
1
110 16 6.2 16
1.069E-
01 0.1069
-
1.243
2
-
1.24320282
1
110 16 6.5 20
1.069E-
01 0.13448
-
1.243
2
-
1.10544799
4
110 16 6.6 21
1.069E-
01 0.14138
-
1.243
2
-
1.07414294
2
110 16 6.6 21
1.069E-
01 0.14138
-
1.243
2
-
1.07414294
2
110 16 6.6 21
1.069E-
01 0.14138
-
1.243
2
-
1.07414294
2
110 16 6.7 24
1.069E-
01 0.16207
-
1.243
2
-
0.98599018
1
110 16 7.0 25
1.069E-
01 0.16897
-
1.243
2
-
0.95826125
8
111 26 7.0 25
1.759E-
01 0.16897
-
0.931
3
-
0.95826125
8
113 27 7.0 25
1.828E-
01 0.16897
-
0.904
9
-
0.95826125
8
113 27 7.0 25 1.828E- 0.16897 - -

01
0.904
9
0.95826125
8
114 29 7.3 29
1.966E-
01 0.19655 -0.854
-
0.85400278
1
115 30 7.4 30
2.034E-
01 0.20345
-
0.829
4
-
0.82936738
4
115 30 7.5 31
2.034E-
01 0.21034
-
0.829
4
-
0.80522534
2
120 32 7.5 31
2.172E-
01 0.21034
-
0.781
5
-
0.80522534
2
123 33 7.8 33
2.241E-
01 0.22414
-
0.758
3
-
0.75829255
7
123 33 8.0 34
2.241E-
01 0.23103
-
0.758
3
-
0.73544427
6
124 35 8.3 35
2.379E-
01 0.23793 -0.713
-
0.71297364
128 36 8.3 35
2.448E-
01 0.23793
-
0.690
9
-
0.71297364
129 37 8.6 37
2.517E-
01 0.25172
-
0.669
1
-
0.66907399
8
130 38 8.7 38
2.586E-
01 0.25862
-
0.647
6
-
0.64760358
3
131 39 8.9 39
2.655E-
01 0.26552
-
0.626
4
-
0.62642764
3
132 40 8.9 39
2.724E-
01 0.26552
-
0.605
5
-
0.62642764
3
133 41 9.3 41
2.793E-
01 0.27931
-
0.584
9
-
0.58489147
7
135 42 9.7 42
2.862E-
01 0.28621
-
0.564
5
-
0.56450015
7
135 42 9.8 43
2.862E-
01 0.2931
-
0.564
5
-
0.54434091
5

135 42 9.9 44
2.862E-
01 0.3
-
0.564
5
-
0.52440051
3
138 45 9.9 44
3.069E-
01 0.3
-
0.504
7
-
0.52440051
3
138 45 10.0 46
3.069E-
01 0.31379
-
0.504
7
-
0.48512707
6
140 47 10.0 46
3.207E-
01 0.31379
-
0.465
8
-
0.48512707
6
142 48 10.0 46
3.276E-
01 0.31379
-
0.446
6
-
0.48512707
6
142 48 10.2 49
3.276E-
01 0.33448
-
0.446
6
-
0.42756820
7
143 50 10.2 49
3.414E-
01 0.33448
-
0.408
7
-
0.42756820
7
143 50 10.4 51
3.414E-
01 0.34828
-
0.408
7
-
0.38997947
5
144 52 10.5 52
3.552E-
01 0.35517
-
0.371
4
-
0.37139301
5
144 52 10.6 53
3.552E-
01 0.36207
-
0.371
4
-
0.35293398
6
144 52 10.6 53
3.552E-
01 0.36207
-
0.371
4
-
0.35293398
6
145 55 11.0 55
3.759E-
01 0.37586
-
0.316
4
-
0.31636676
8
145 55 11.1 56
3.759E-
01 0.38276
-
0.316
4
-
0.29824360
7
145 55 11.2 57
3.759E-
01 0.38966
-
0.316
4
-
0.28021788
6
145 55 11.2 57
3.759E-
01 0.38966
-
0.316
4
-
0.28021788
6
146 59 11.4 59 4.034E- 0.40345 - -

01
0.244
4
0.24443162
4
146 59 11.4 59
4.034E-
01 0.40345
-
0.244
4
-
0.24443162
4
146 59 11.5 61
4.034E-
01 0.41724
-
0.244
4
-
0.20895578
147 62 11.6 62
4.241E-
01 0.42414
-
0.191
3
-
0.19131876
3
147 62 11.8 63
4.241E-
01 0.43103
-
0.191
3
-
0.17374106
2
148 64 11.9 64
4.379E-
01 0.43793
-
0.156
2
-
0.15621688
4
148 64 12.0 65
4.379E-
01 0.44483
-
0.156
2
-
0.13874055
2
149 66 12.0 65
4.517E-
01 0.44483
-
0.121
3
-
0.13874055
2
149 66 12.0 65
4.517E-
01 0.44483
-
0.121
3
-
0.13874055
2
149 66 12.0 65
4.517E-
01 0.44483
-
0.121
3
-
0.13874055
2
149 66 12.0 69
4.517E-
01 0.47241
-
0.121
3
-
0.06920356
4
150 70 12.1 70
4.793E-
01 0.47931
-
0.051
9
-
0.05188454
4
150 70 12.1 70
4.793E-
01 0.47931
-
0.051
9
-
0.05188454
4
150 70 12.1 70
4.793E-
01 0.47931
-
0.051
9
-
0.05188454
4
151 73 12.1 70
5.000E-
01 0.47931
-1E-
16
-
0.05188454
4
152 74 12.2 74
5.069E-
01 0.5069
0.017
29
0.01728795
3

152 74 12.2 74
5.069E-
01 0.5069
0.017
29
0.01728795
3
152 74 12.3 76
5.069E-
01 0.52069
0.017
29
0.05188454
4
153 77 12.5 77
5.276E-
01 0.52759
0.069
2
0.06920356
4
153 77 12.5 77
5.276E-
01 0.52759
0.069
2
0.06920356
4
153 77 12.5 77
5.276E-
01 0.52759
0.069
2
0.06920356
4
153 77 12.5 77
5.276E-
01 0.52759
0.069
2
0.06920356
4
154 81 12.7 81
5.552E-
01 0.55517
0.138
74
0.13874055
2
154 81 12.9 82
5.552E-
01 0.56207
0.138
74
0.15621688
4
155 83 13.0 83
5.690E-
01 0.56897
0.173
74
0.17374106
2
155 83 13.0 83
5.690E-
01 0.56897
0.173
74
0.17374106
2
156 85 13.0 83
5.828E-
01 0.56897
0.208
96
0.17374106
2
157 86 13.1 86
5.897E-
01 0.58966
0.226
66
0.22665804
3
157 86 13.1 86
5.897E-
01 0.58966
0.226
66
0.22665804
3
157 86 13.1 86
5.897E-
01 0.58966
0.226
66
0.22665804
3
157 86 13.3 89
5.897E-
01 0.61034
0.226
66
0.28021788
6
157 86 13.3 89
5.897E-
01 0.61034
0.226
66
0.28021788
6
158 91 13.4 91
6.241E-
01 0.62414
0.316
37
0.31636676
8
158 91 13.4 91
6.241E-
01 0.62414
0.316
37
0.31636676
8
160 93 13.5 93
6.379E-
01 0.63793
0.352
93
0.35293398
6
160 93 13.7 94
6.379E-
01 0.64483
0.352
93
0.37139301
5
160 93 13.7 94
6.379E-
01 0.64483
0.352
93
0.37139301
5
160 93 13.9 96
6.379E-
01 0.65862
0.352
93
0.40870165
3
160 93 13.9 96
6.379E-
01 0.65862
0.352
93
0.40870165
3

161 98 13.9 96
6.724E-
01 0.65862
0.446
59
0.40870165
3
162 99 14.0 99
6.793E-
01 0.67931
0.465
77 0.46577116
162 99 14.0 99
6.793E-
01 0.67931
0.465
77 0.46577116
163
10
1 14.0 99
6.931E-
01 0.67931
0.504
67 0.46577116
163
10
1 14.0 99
6.931E-
01 0.67931
0.504
67 0.46577116
163
10
1 14.1
10
3
6.931E-
01 0.7069
0.504
67
0.54434091
5
163
10
1 14.1
10
3
6.931E-
01 0.7069
0.504
67
0.54434091
5
165
10
5 14.1
10
3
7.207E-
01 0.7069
0.584
89
0.54434091
5
165
10
5 14.2
10
6
7.207E-
01 0.72759
0.584
89
0.60552896
3
166
10
7 14.3
10
7
7.345E-
01 0.73448
0.626
43
0.62642764
3
166
10
7 14.5
10
8
7.345E-
01 0.74138
0.626
43
0.64760358
3
166
10
7 14.6
10
9
7.345E-
01 0.74828
0.626
43
0.66907399
8
169
11
0 14.8
11
0
7.552E-
01 0.75517
0.690
86
0.69085737
9
170
11
1 15.0
11
1
7.621E-
01 0.76207
0.712
97 0.71297364
171
11
2 15.0
11
1
7.690E-
01 0.76207
0.735
44 0.71297364
174
11
3 15.0
11
1
7.759E-
01 0.76207
0.758
29 0.71297364
174
11
3 15.0
11
1
7.759E-
01 0.76207
0.758
29 0.71297364
175
11
5 15.3
11
5
7.897E-
01 0.78966
0.805
23
0.80522534
2
175
11
5 15.6
11
6
7.897E-
01 0.79655
0.805
23
0.82936738
4
177
11
7 16.0
11
7
8.034E-
01 0.80345 0.854
0.85400278
1
179
11
8 16.0
11
7
8.103E-
01 0.80345
0.879
17
0.85400278
1
188
11
9 16.0
11
7
8.172E-
01 0.80345
0.904
9
0.85400278
1
188
11
9 16.0
11
7
8.172E-
01 0.80345
0.904
9
0.85400278
1

190
12
1 16.2
12
1
8.310E-
01 0.83103
0.958
26
0.95826125
8
190
12
1 16.6
12
2
8.310E-
01 0.83793
0.958
26
0.98599018
1
194
12
3 16.7
12
3
8.448E-
01 0.84483
1.014
5
1.01449874
6
195
12
4 16.8
12
4
8.517E-
01 0.85172
1.043
86
1.04385663
5
197
12
5 16.9
12
5
8.586E-
01 0.85862
1.074
14
1.07414294
2
200
12
6 17.0
12
6
8.655E-
01 0.86552
1.105
45
1.10544799
4
200
12
6 17.3
12
7
8.655E-
01 0.87241
1.105
45
1.13787564
2
202
12
8 17.7
12
8
8.793E-
01 0.87931
1.171
55
1.17154617
1
205
12
9 17.9
12
9
8.862E-
01 0.88621
1.206
6
1.20660005
2
214
13
0 18.0
13
0
8.931E-
01 0.8931
1.243
2
1.24320282
1
215
13
1 18.0
13
0
9.000E-
01 0.8931
1.281
55
1.24320282
1
215
13
1 18.4
13
2
9.000E-
01 0.9069
1.281
55
1.32188365
3
218
13
3 18.9
13
3
9.138E-
01 0.91379
1.364
49
1.36448874
8
220
13
4 19.3
13
4
9.207E-
01 0.92069
1.409
73
1.40972571
2
222
13
5 19.4
13
5
9.276E-
01 0.92759
1.458
05
1.45804700
9
222
13
5 19.7
13
6
9.276E-
01 0.93448
1.458
05
1.51003504
3
222
13
5 19.9
13
7
9.276E-
01 0.94138
1.458
05
1.56645823
3
225
13
8 20.0
13
8
9.483E-
01 0.94828
1.628
36
1.62836140
7
231
13
9 20.0
13
8
9.552E-
01 0.94828
1.697
22
1.62836140
7
238
14
0 20.2
14
0
9.621E-
01 0.96207
1.775
22
1.77521696
9
271
14
1 21.5
14
1
9.690E-
01 0.96897
1.865
8
1.86580276
4
288
14
2 22.3
14
2
9.759E-
01 0.97586
1.974
93
1.97493202
9
313
14
3 23.9
14
3
9.828E-
01 0.98276
2.114
38
2.11438077
2

314
14
4 25.0
14
4
9.897E-
01 0.98966
2.313
6
2.31360033
7
330
14
5 32.1
14
5
9.966E-
01 0.99655
2.701
8
2.70179862
8
(b) Constructing a normal probability plot (quantile - quantile plot)
Alcohol %
-3 -2 -1 0 1 2 3
0
2
4
6
8
10
12
14
Normal Quantile Plot
Rank-based Z-score
Alcohol %
Calories

-3 -2 -1 0 1 2 3
0
50
100
150
200
250
300
350
Normal Quantile Plot
Rank-based Z-score
Navigation Times (seconds)
Carbohydrates

-3 -2 -1 0 1 2 3
0
5
10
15
20
25
30
35
Normal Quantile Plot
Rank-based Z-score
Carbohydrates
CONCLUSION
By summing up this report, it has been concluded that different methods such as
descriptive statistics, box and Q-Q plot clearly present that mean and median alcohol % as well
as calories of 145 beer brands are not equal. It can be seen in the report that values of mean
median of such elements pertaining to different brands vary to some extent. However, it has
found from evaluation carbohydrate level of concerned 145 brands are equal such as 12.1
respectively. Considering the outcome of statistical tools, it can be summarized that given data
set of alcohol % and calories are not normally distributed.

REFERENCES
Online
Box or Whisker Plot. 2017. [Online]. Available through: <http://ksrowell.com/blog-visualizing-
data/2012/08/24/making-a-box-and-whisker-plot-in-excel/>.
Histograms. 2017. [Online]. Available through:
<https://statistics.laerd.com/statistical-guides/understanding-histograms.php>.