Data Analysis and Forecasting

This assignment involves analyzing a dataset of weather indicators, including temperature, humidity, and wind speed, over a period of time. The student is required to calculate various statistical measures such as mean, median, mode, range, and standard deviation to understand the trends in the data. Additionally, the linear-forecasting model is used to predict future values of the weather indicators based on historical data. The assignment provides a clear understanding of how to apply data analysis techniques to real-world problems and forecast future outcomes.

Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................1
Main Body.......................................................................................................................................1
1. Table Format......................................................................................................................1
2. Graphical representation of weather report........................................................................2
3. Calculation..........................................................................................................................4
4. Liner-forecasting model.....................................................................................................8
CONCLUSION................................................................................................................................9
REFERENCES..............................................................................................................................10

INTRODUCTION
Data analysis can be defined as a process to organise and analysis a data with a goal, to
interpret result more accurately. For this purpose, a statistician can use multiple techniques of
central tendencies for analysing a data (Silverman, 2018). It includes mean, median, mode,
standard deviations and more. In this present assignment, data related to weather is taken to
forecast weather report of upcoming days. For this purpose, some calculations are done using
different statistical formulae.
Main Body
For analysing the concept of Data analysis techniques, 10 days of weather data of
Welwyn Garden City is taken during the period of 2017-18 that is May, 2017 (Weather of
Welwyn Garden City, Hertfordshire. 2019).
1. Table Format
Weather Report:
Days Temperature Humidity Wind
01/05/17 13°C 59.00% 20km/hr
02/05/17 15°C 48.00% 19km/hr
03/05/17 11°C 67.00% 24km/hr
04/05/17 14°C 55.00% 26km/hr
05/05/17 15°C 34.00% 35km/hr
06/05/17 14°C 63.00% 19km/hr
07/05/17 17°C 39.00% 15km/hr
08/05/17 12°C 58.00% 20km/hr
09/05/17 13°C 47.00% 11km/hr
10/05/17 18°C 37.00% 9km/hr
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2. Graphical representation of weather report
Temperature
Days Temperature (°C)
01/05/17 13
02/05/17 15
03/05/17 11
04/05/17 14
05/05/17 15
06/05/17 14
07/05/17 17
08/05/17 12
09/05/17 13
10/05/17 18
2
01/05/2017
02/05/2017
03/05/2017
04/05/2017
05/05/2017
06/05/2017
07/05/2017
08/05/2017
09/05/2017
10/05/2017
0
2
4
6
8
10
12
14
16
18
13
15
11
14 15 14
17
12 13
18
Temperature
Temperature (°C)
Days in May
Temperature in Degree Celcius

Humidity
Days Humidity
01/05/17 59.00%
02/05/17 48.00%
03/05/17 67.00%
04/05/17 55.00%
05/05/17 34.00%
06/05/17 63.00%
07/05/17 39.00%
08/05/17 58.00%
09/05/17 47.00%
10/05/17 37.00%
Wind
Days Wind
3
01/05/2017
02/05/2017
03/05/2017
04/05/2017
05/05/2017
06/05/2017
07/05/2017
08/05/2017
09/05/2017
10/05/2017
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
59.00%
48.00%
67.00%
55.00%
34.00%
63.00%
39.00%
58.00%
47.00%
37.00%
Humidity
Humidity
Days of May
Humidity in percentage

01/05/17 20km/hr
02/05/17 19km/hr
03/05/17 24km/hr
04/05/17 26km/hr
05/05/17 35km/hr
06/05/17 19km/hr
07/05/17 15km/hr
08/05/17 20km/hr
09/05/17 11km/hr
10/05/17 9km/hr
3. Calculation
For calculating the weather data in the form of central tendencies, below method has been
used:
4
01/05/2017
02/05/2017
03/05/2017
04/05/2017
05/05/2017
06/05/2017
07/05/2017
08/05/2017
09/05/2017
10/05/2017
0
5
10
15
20
25
30
35
20 19
24 26
35
19
15
20
11 9
Wind Speed
Wind
Days of May
Wind speed in km/hr

Mean: This method provides the average data of a large observation which helps in representing
entire data into single form. It can be calculated by dividing total observation with number of
observation.
Mean = ∑x / N where, ∑x shows the sum of total observation
N represents total number of observation
Median: It divides entire data into two parts equally by rearranging the data into ascending order
and then segmented into two parts.
Median = (No. of days + 1) / 2 if number is odd, otherwise
= No. of days / 2
Mode: It provides the observation which has high frequency or repeated mostly than others.
Range: It shows the difference between observations by using below formula:
Range = Maximum observation – Minimum Observation
Standard Deviations: It is calculated by taking square root of variance that shows actual
difference between expected and mean value, by using:
Standard Deviation =√ (variance)
Variance2 = {∑(x – mean) / N} 2
Calculation for Weather Report:
Temperature
Days
Temperature
(°C)
01/05/17 13
02/05/17 15
03/05/17 11
04/05/17 14
05/05/17 15
06/05/17 14
07/05/17 17
08/05/17 12
5

09/05/17 13
10/05/17 18
Total 142
Mean = (Sum of Observation) / Number of observation
= 142 / 10
= 14.2 °C
Median = 10 / 2
= 5th Observation
= 14 °C
Mode = 13°C
Range = Max – Min
= 18 – 11
= 7 °C
Standard Deviations =√ (variance)
Variance 2 = {∑(x – mean) / N}2
= {∑( x2 / N – (mean)2 }
= { 2058 / 10 – (14.2) 2 }
= { 205. 8 – 201.6 }
= 4.2
Std. Dev. = 2.04
Humidity
Days Humidity
01/05/17 59.00%
02/05/17 48.00%
03/05/17 67.00%
04/05/17 55.00%
05/05/17 34.00%
6

06/05/17 63.00%
07/05/17 39.00%
08/05/17 58.00%
09/05/17 47.00%
10/05/17 37.00%
Mean = (Sum of Observation) / Number of observation
= 507 / 10
= 50.70%
Median = 10 / 2
= 5th Observation
= 51.50%
Mode = 0
Range = Max – Min
= 67 – 34
= 33 °C
Standard Deviations =√ (variance)
Variance 2 = {∑(x – mean) / N}2
= {∑( x2 / N – (mean)2 }
= { 26887 / 10 – (50.70) 2 }
= { 2688.70 – 2570.49 }
= 118.21
Std Dev. = √118.21
= 10.87
Wind
Days Wind
01/05/17 20km/hr
7

02/05/17 19km/hr
03/05/17 24km/hr
04/05/17 26km/hr
05/05/17 35km/hr
06/05/17 19km/hr
07/05/17 15km/hr
08/05/17 20km/hr
09/05/17 11km/hr
10/05/17 9km/hr
Mean = (Sum of Observation) / Number of observation
= 198 / 10
= 19.8 km/hr
Median = 10 / 2
= 5th Observation
= 19.50 km/hr
Mode = 19 km/hr
Range = Max – Min
= 35 – 9
= 26 km/hr
Standard Deviations =√ (variance)
Variance 2 = {∑(x – mean) / N}2
= {∑( x2 / N – (mean)2 }
= { 4426 / 10 – (19.8) 2 }
= { 442.6 – 392.04 }
= 50.56
Std Dev. = √50.56
= 7.11
8

4. Liner-forecasting model
This model helps in determining the value of m in y = mx + c by taking the following
steps:-
1. m is known as slope of a line which represents the relationship between two main
variables as x and y, Steps to calculate m:-
= Change in Y / Change in X
From temperature data, y1 = 15°C
y0 = 13°C
while, Change in x = 1 day
so, m = 15 – 13 / 1
= 2
2. c in this model always remains constant therefore, changing variables doesn't effect its
value in a certain equation. Step to calculate c:
c = y – mx
= 2 – 2 / 1 = 0
3. By calculation the value of 'm' and 'c' in a certain equation, as per given case, statistician
can forecast the weather indicator for day 15 and day 23 by using FORECAST.LINEAR
(x,yknownvalues,xknownvalues) as:-
Days Temperature Humidity Wind
15/05/17 16.73 39.89 19.12
23/05/17 18.86 30.79 18.56
CONCLUSION
From this given assignment, it has been concluded that to analyse a particular
information, data analysis is considered as most effective tool that helps in forecasting the data.
For this purpose, various methods can be used such as mean, median and mode etc.
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REFERENCES
Books and Journals
Silverman, B. W., 2018. Density estimation for statistics and data analysis. Routledge.
Little, R. J. and Rubin, D. B., 2019. Statistical analysis with missing data (Vol. 793). Wiley.
Franke, D. and et. al., 2017. ATSAS 2.8: a comprehensive data analysis suite for small-angle
scattering from macromolecular solutions. Journal of applied crystallography. 50(4).
pp.1212-1225.
Taylor, M. A. and Bonsall, P. W., 2017. Understanding traffic systems: data analysis and
presentation. Routledge.
Online
Weather of Welwyn Garden City, Hertfordshire. 2019. [Online] Available Through:
<https://www.bbc.com/weather/2634552>.
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