STA 1132 Descriptive Statistics

Definition of Statistics and Role of Statistics

Dr. Thiyanga S. Talagala
Department of Statistics, Faculty of Applied Sciences
University of Sri Jayewardenepura, Sri Lanka

Learning Objective:

By the end of this lecture, students will be able to:

  • Define statistics and explain its fundamental concepts.
  • Identify the various fields and contexts where statistics is used.
  • Explain the importance and significance of statistics in decision-making and problem-solving processes.

Outline

What is statistics?

Where do we use statistics?

Why do we need statistics?

Outline

What is statistics?

Where do we use statistics?

Why do we need statistics?

What is Statistics?

The science of collecting, organizing, and analyzing data, and presenting and interpreting the results derived from that data to gain insights and make informed decisions.

The science of collecting, organizing, and analyzing data, and presenting and interpreting the results derived from that data to gain insights and make informed decisions.

The science of collecting, organizing, and analyzing data, and presenting and interpreting the results derived from that data to gain insights and make informed decisions.

Tabular data (Structured data)

Source: Le Dinh, T., Lee, S. H., Kwon, S. G., & Kwon, K. R. (2022). COVID-19 Chest X-ray Classification and Severity Assessment Using Convolutional and Transformer Neural Networks. Applied Sciences, 12(10), 4861.

Tabular data (Structured data)

Image data

Tabular data (Structured data)

Audio data

Image data

Tabular data (Structured data)

Audio data

Image data

Video data

Link

The science of collecting, organizing, and analyzing data, and presenting and interpreting the results derived from that data to gain insights and make informed decisions.

How to choose a representative subset of the population?

Elephant distribution map for Sri Lanka. Image courtesy of Fernando et al (2019). (accessed from https://news.mongabay.com/2019/02/sri-lanka-gets-its-first-data-based-elephant-distribution-map/)

The science of collecting, organizing, and analyzing data, and presenting and interpreting the results derived from that data to gain insights and make informed decisions.

The science of collecting, organizing, and analyzing data, and presenting and interpreting the results derived from that data to gain insights and make informed decisions.

     ID Gender     A   B   C Weight
1     1   Male  80.0 3.6 2.5   4000
2     2 Female  90.0 2.5 6.3   5000
3     3 Female 110.0 4.0 4.5   6000
4     4 Female 100.0 4.5 3.2   7000
5     5 Female  91.5 3.0 3.5   7550
6     6   Male  92.0 3.9 3.7   4500
7     7   Male  88.0 4.2 3.8   3375
8     8   Male  70.0 4.6 3.9   5500
9     9 Female  99.6 4.9 3.4   4988
10   10 Female 100.2 5.5 2.8   5594
11   11 Female  98.9 3.4 4.9   3530
12   12 Female 101.8 2.9 3.3   3007
13   13 Female 100.0 4.2 4.2   4259
14   14 Female 100.3 3.5 2.6   3595
15   15 Female  98.7 4.4 3.0   4516
16   16 Female  98.4 2.2 3.6   2307
17   17 Female 100.5 2.7 3.8   2847
18   18 Female 100.1 2.9 4.5   2991
19   19 Female 100.2 2.8 2.6   2906
20   20 Female  99.9 4.6 3.0   4694
21   21 Female  99.6 4.8 2.5   4905
22   22 Female 101.0 3.6 0.7   3694
23   23 Female 100.3 3.1 3.6   3242
24   24 Female  98.6 4.2 3.6   4281
25   25 Female  99.5 3.4 5.0   3534
26   26 Female 100.6 2.9 4.6   3044
27   27 Female  99.5 3.4 4.7   3455
28   28 Female 100.9 3.2 3.6   3324
29   29 Female  98.1 2.7 3.3   2793
30   30 Female  98.5 2.9 5.3   3050
31   31 Female  99.3 3.5 3.1   3622
32   32 Female 101.5 3.8 2.7   3870
33   33 Female 100.8 3.5 3.7   3611
34   34 Female 100.0 4.4 5.1   4482
35   35 Female  98.5 2.5 3.9   2563
36   36 Female  99.9 4.1 3.9   4155
37   37 Female  99.8 4.0 3.3   4117
38   38 Female  99.2 3.9 1.7   4023
39   39 Female 100.2 5.4 4.4   5535
40   40 Female 101.2 3.7 3.5   3778
41   41 Female 100.4 4.1 2.4   4151
42   42 Female  99.8 3.6 4.2   3677
43   43 Female 100.9 3.4 3.4   3504
44   44 Female 100.5 2.4 3.5   2494
45   45 Female  98.6 4.5 3.6   4631
46   46 Female  99.2 3.0 2.6   3098
47   47 Female  99.7 4.3 3.0   4351
48   48 Female 100.5 3.2 3.9   3274
49   49 Female  99.8 3.5 3.4   3575
50   50 Female  99.9 1.7 3.5   1796
51   51 Female  99.9 2.0 4.4   2075
52   52 Female 100.6 3.2 3.6   3273
53   53 Female 100.4 2.7 3.0   2837
54   54 Female 101.2 3.0 4.1   3140
55   55   Male  98.4 2.3 4.9   3561
56   56   Male 102.1 3.9 3.3   5965
57   57   Male  99.7 3.5 1.9   5405
58   58   Male  98.4 1.4 4.7   2176
59   59   Male  98.7 2.5 3.8   3789
60   60   Male  98.0 1.9 3.2   2887
61   61   Male  99.5 2.3 3.0   3537
62   62   Male  99.0 2.7 1.8   4172
63   63   Male 101.0 3.3 2.8   4993
64   64   Male 100.0 3.2 4.1   4903
65   65   Male 100.1 2.1 3.5   3319
66   66   Male 100.7 1.2 3.5   1962
67   67   Male 100.2 3.4 3.5   5268
68   68   Male  99.5 3.1 4.6   4685
69   69   Male  98.9 2.6 3.9   4047
70   70   Male 101.1 6.0 3.9   9121
71   71   Male  99.3 2.6 3.3   3961
72   72   Male  99.2 4.3 3.2   6567
73   73   Male  99.4 1.9 2.8   2891
74   74   Male  99.8 1.7 3.4   2680
75   75   Male 100.1 4.9 3.3   7506
76   76   Male 100.3 3.7 2.6   5675
77   77   Male  99.7 2.4 4.2   3736
78   78   Male 100.8 4.0 4.5   6160
79   79   Male 100.8 3.3 3.6   5072
80   80   Male 102.4 3.3 2.1   4994
81   81   Male 100.8 3.3 3.3   5055
82   82   Male  98.9 3.8 4.3   5798
83   83   Male 100.2 0.7 3.1   1184
84   84   Male 100.2 4.2 4.8   6432
85   85   Male 100.0 2.3 2.6   3592
86   86   Male 100.0 2.4 4.6   3654
87   87   Male 100.7 2.0 3.0   3086
88   88   Male 100.0 2.0 2.7   3128
89   89   Male  99.0 3.8 3.5   5787
90   90   Male 100.3 1.8 3.3   2775
91   91   Male 100.4 5.1 3.9   7735
92   92   Male 101.0 4.2 4.1   6371
93   93   Male  99.1 3.7 5.4   5721
94   94   Male  98.8 3.9 4.6   5935
95   95   Male 100.3 4.2 5.1   6358
96   96   Male 100.3 3.7 2.8   5654
97   97   Male 100.0 3.1 2.1   4704
98   98   Male 100.7 2.4 3.3   3627
99   99   Male 100.4 3.8 3.3   5800
100 100   Male  99.6 1.3 3.1   2005
ID Gender A B C Weight
1 Male 80.0 3.6 2.5 4000
2 Female 90.0 2.5 6.3 5000
3 Female 110.0 4.0 4.5 6000
4 Female 100.0 4.5 3.2 7000
5 Female 91.5 3.0 3.5 7550
6 Male 92.0 3.9 3.7 4500
7 Male 88.0 4.2 3.8 3375
8 Male 70.0 4.6 3.9 5500
9 Female 99.6 4.9 3.4 4988
10 Female 100.2 5.5 2.8 5594
11 Female 98.9 3.4 4.9 3530
12 Female 101.8 2.9 3.3 3007
13 Female 100.0 4.2 4.2 4259
14 Female 100.3 3.5 2.6 3595
15 Female 98.7 4.4 3.0 4516
16 Female 98.4 2.2 3.6 2307
17 Female 100.5 2.7 3.8 2847
18 Female 100.1 2.9 4.5 2991
19 Female 100.2 2.8 2.6 2906
20 Female 99.9 4.6 3.0 4694
21 Female 99.6 4.8 2.5 4905
22 Female 101.0 3.6 0.7 3694
23 Female 100.3 3.1 3.6 3242
24 Female 98.6 4.2 3.6 4281
25 Female 99.5 3.4 5.0 3534
26 Female 100.6 2.9 4.6 3044
27 Female 99.5 3.4 4.7 3455
28 Female 100.9 3.2 3.6 3324
ID Gender A B C Weight
29 29 Female 98.1 2.7 3.3 2793
30 30 Female 98.5 2.9 5.3 3050
31 31 Female 99.3 3.5 3.1 3622
32 32 Female 101.5 3.8 2.7 3870
33 33 Female 100.8 3.5 3.7 3611
34 34 Female 100.0 4.4 5.1 4482
35 35 Female 98.5 2.5 3.9 2563
36 36 Female 99.9 4.1 3.9 4155
37 37 Female 99.8 4.0 3.3 4117
38 38 Female 99.2 3.9 1.7 4023
39 39 Female 100.2 5.4 4.4 5535
40 40 Female 101.2 3.7 3.5 3778
41 41 Female 100.4 4.1 2.4 4151
42 42 Female 99.8 3.6 4.2 3677
43 43 Female 100.9 3.4 3.4 3504
44 44 Female 100.5 2.4 3.5 2494
45 45 Female 98.6 4.5 3.6 4631
46 46 Female 99.2 3.0 2.6 3098
47 47 Female 99.7 4.3 3.0 4351
48 48 Female 100.5 3.2 3.9 3274
49 49 Female 99.8 3.5 3.4 3575
50 50 Female 99.9 1.7 3.5 1796
51 51 Female 99.9 2.0 4.4 2075
52 52 Female 100.6 3.2 3.6 3273
53 53 Female 100.4 2.7 3.0 2837
54 54 Female 101.2 3.0 4.1 3140
55 55 Male 98.4 2.3 4.9 3561
56 56 Male 102.1 3.9 3.3 5965
ID Gender A B C Weight
57 57 Male 99.7 3.5 1.9 5405
58 58 Male 98.4 1.4 4.7 2176
59 59 Male 98.7 2.5 3.8 3789
60 60 Male 98.0 1.9 3.2 2887
61 61 Male 99.5 2.3 3.0 3537
62 62 Male 99.0 2.7 1.8 4172
63 63 Male 101.0 3.3 2.8 4993
64 64 Male 100.0 3.2 4.1 4903
65 65 Male 100.1 2.1 3.5 3319
66 66 Male 100.7 1.2 3.5 1962
67 67 Male 100.2 3.4 3.5 5268
68 68 Male 99.5 3.1 4.6 4685
69 69 Male 98.9 2.6 3.9 4047
70 70 Male 101.1 6.0 3.9 9121
71 71 Male 99.3 2.6 3.3 3961
72 72 Male 99.2 4.3 3.2 6567
73 73 Male 99.4 1.9 2.8 2891
74 74 Male 99.8 1.7 3.4 2680
75 75 Male 100.1 4.9 3.3 7506
76 76 Male 100.3 3.7 2.6 5675
77 77 Male 99.7 2.4 4.2 3736
78 78 Male 100.8 4.0 4.5 6160
79 79 Male 100.8 3.3 3.6 5072
80 80 Male 102.4 3.3 2.1 4994
81 81 Male 100.8 3.3 3.3 5055
82 82 Male 98.9 3.8 4.3 5798
83 83 Male 100.2 0.7 3.1 1184
ID Gender A B C Weight
84 84 Male 100.2 4.2 4.8 6432
85 85 Male 100.0 2.3 2.6 3592
86 86 Male 100.0 2.4 4.6 3654
87 87 Male 100.7 2.0 3.0 3086
88 88 Male 100.0 2.0 2.7 3128
89 89 Male 99.0 3.8 3.5 5787
90 90 Male 100.3 1.8 3.3 2775
91 91 Male 100.4 5.1 3.9 7735
92 92 Male 101.0 4.2 4.1 6371
93 93 Male 99.1 3.7 5.4 5721
94 94 Male 98.8 3.9 4.6 5935
95 95 Male 100.3 4.2 5.1 6358
96 96 Male 100.3 3.7 2.8 5654
97 97 Male 100.0 3.1 2.1 4704
98 98 Male 100.7 2.4 3.3 3627
99 99 Male 100.4 3.8 3.3 5800
100 100 Male 99.6 1.3 3.1 2005
ID Gender B Weight
1 Male 3.6 4000
2 Female 2.5 5000
3 Female 4.0 6000
4 Female 4.5 7000
5 Female 3.0 7550
6 Male 3.9 4500
7 Male 4.2 3375
8 Male 4.6 5500
9 Female 4.9 4988
10 Female 5.5 5594
11 Female 3.4 3530
12 Female 2.9 3007
13 Female 4.2 4259
14 Female 3.5 3595
15 Female 4.4 4516
16 Female 2.2 2307
17 Female 2.7 2847
18 Female 2.9 2991
19 Female 2.8 2906
20 Female 4.6 4694
21 Female 4.8 4905
22 Female 3.6 3694
23 Female 3.1 3242
24 Female 4.2 4281
25 Female 3.4 3534
26 Female 2.9 3044
27 Female 3.4 3455
28 Female 3.2 3324
ID Gender B Weight
29 29 Female 2.7 2793
30 30 Female 2.9 3050
31 31 Female 3.5 3622
32 32 Female 3.8 3870
33 33 Female 3.5 3611
34 34 Female 4.4 4482
35 35 Female 2.5 2563
36 36 Female 4.1 4155
37 37 Female 4.0 4117
38 38 Female 3.9 4023
39 39 Female 5.4 5535
40 40 Female 3.7 3778
41 41 Female 4.1 4151
42 42 Female 3.6 3677
43 43 Female 3.4 3504
44 44 Female 2.4 2494
45 45 Female 4.5 4631
46 46 Female 3.0 3098
47 47 Female 4.3 4351
48 48 Female 3.2 3274
49 49 Female 3.5 3575
50 50 Female 1.7 1796
51 51 Female 2.0 2075
52 52 Female 3.2 3273
53 53 Female 2.7 2837
54 54 Female 3.0 3140
55 55 Male 2.3 3561
56 56 Male 3.9 5965
ID Gender B Weight
57 57 Male 3.5 5405
58 58 Male 1.4 2176
59 59 Male 2.5 3789
60 60 Male 1.9 2887
61 61 Male 2.3 3537
62 62 Male 2.7 4172
63 63 Male 3.3 4993
64 64 Male 3.2 4903
65 65 Male 2.1 3319
66 66 Male 1.2 1962
67 67 Male 3.4 5268
68 68 Male 3.1 4685
69 69 Male 2.6 4047
70 70 Male 6.0 9121
71 71 Male 2.6 3961
72 72 Male 4.3 6567
73 73 Male 1.9 2891
74 74 Male 1.7 2680
75 75 Male 4.9 7506
76 76 Male 3.7 5675
77 77 Male 2.4 3736
78 78 Male 4.0 6160
79 79 Male 3.3 5072
80 80 Male 3.3 4994
81 81 Male 3.3 5055
82 82 Male 3.8 5798
83 83 Male 0.7 1184
ID Gender B Weight
84 84 Male 4.2 6432
85 85 Male 2.3 3592
86 86 Male 2.4 3654
87 87 Male 2.0 3086
88 88 Male 2.0 3128
89 89 Male 3.8 5787
90 90 Male 1.8 2775
91 91 Male 5.1 7735
92 92 Male 4.2 6371
93 93 Male 3.7 5721
94 94 Male 3.9 5935
95 95 Male 4.2 6358
96 96 Male 3.7 5654
97 97 Male 3.1 4704
98 98 Male 2.4 3627
99 99 Male 3.8 5800
100 100 Male 1.3 2005

Summary measures

Gender A B C Weight
Female:50 Min. : 70.00 Min. :0.700 Min. :0.700 Min. :1184
Male :50 1st Qu.: 99.20 1st Qu.:2.600 1st Qu.:3.000 1st Qu.:3216
NA Median :100.00 Median :3.400 Median :3.500 Median :3916
NA Mean : 99.16 Mean :3.311 Mean :3.562 Mean :4225
NA 3rd Qu.:100.42 3rd Qu.:4.000 3rd Qu.:4.100 3rd Qu.:5059
NA Max. :110.00 Max. :6.000 Max. :6.300 Max. :9121

The science of collecting, organizing, and analyzing data, and presenting, and interpreting and interpreting the results derived from that data to gain insights and make informed decisions.

Presenting Data: Example

https://thiyangt.github.io/dsjobtraker_dashboard_mc/#top-software-and-skills

The science of collecting, organizing, and analyzing data, and presenting, and interpreting results derived from that data to gain insights and make informed decisions.

The science of collecting, organizing, and analyzing data, and presenting, and interpreting results derived from that data to gain insights and make informed decisions.

The science of collecting, organizing, and analyzing data, and presenting, and interpreting results derived from that data to gain insights and make informed decisions.

“Informed” means based on knowledge, facts, or awareness.

When we say “informed decisions,” it refers to choices made after carefully considering relevant information or data, rather than guessing or relying on assumptions.

Outline

What is statistics?

Where do we use statistics?

Why do we need statistics?

Outline

What is statistics?

Where do we use statistics?

Why do we need statistics?

Your turn

  • How often do you find yourself relying on statistics in your daily routines or decision-making processes?

  • Could you provide a few examples of how you utilize statistical information?

10:00

Applications of statistics in different fields

Terminology Field
Epidemiology The study and analysis of the patterns, causes and effects of health and disease conditions
Astrostatistics Applies statistical analysis to the understanding of astronomical data
Biostatistics Studies biological phenomena
Demography Statistical study of all populations
Social statistics Study human behavior in a social environment
Chemometrics Science of extracting information from chemical systems by data-driven means
Terminology Description
Actuarial statistics Discipline that deals with assessing the risks in insurance and finance field.
Forensic statistics Studies DNA testing results
Spatial statistics Analysis of spatial data
Econometrics Uses economic theory, mathematics, and statistical inference to quantify economic phenomena.
Jurimetrics Application of probability and statistics to law.
Psychometrics Applies statistical methods to psychological measurements

Source and Reading materials: https://en.wikipedia.org/wiki/List_of_fields_of_application_of_statistics

Outline

What is statistics?

Where do we use statistics?

Why do we need statistics?

Captured by Dr Thiyanga S. Talagala

#Learn to Travel. Travel to Learn.