Numeracy and Data Analysis: Wind Speed Forecasting in Bristol City

This report explores wind speed forecasting in Bristol City using data analysis and numeracy techniques. It includes a tabular format of the data, two types of appropriate charts, and calculations for mean, mode, median, range, and standard deviation. Linear forecasting is used to determine wind speed on specific days. The report concludes that data analysis is helpful in forecasting information and taking crucial actions for coordinating with the prevailing circumstances.

Numeracy and Data Analysis

TABLE OF CONTENTS
INTRODUCTION ..........................................................................................................................1
MAIN BODY...................................................................................................................................1
Tabular format of the data of wind of the city........................................................................1
Present the data using two types of appropriate charts...........................................................2
Determination as follows:.......................................................................................................2
Using the linear forecasting for calculation............................................................................5
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................7

INTRODUCTION
Data evaluation is the related with having the significant information from the assessing
the presented raw data in turn accomplishing the objective of making strategic decision can
become possible. In the recent time, data numeracy and analysis is highly important as it offers
different form of the efficiency and effectiveness in turn attaining goal of making precise and
information based decision can become possible. The current investigation is based on 10
consecutive days from 21 to 30 march 2022 about Bristol city of UK so that that deeper insights
of the prevailing data can be evaluated. It will focus on showing data in table and having
pictorial presentation of the data set. This will comprise computation of mean, mode, median,
range and SD. Linear equation for computing m, c and wind speed of 11th and 13th days
respectively.
MAIN BODY
Tabular format of the data of wind of the city
S. No. Date
Data
related
to
Wind
speed
of
Bristol
city
1
21th march
2022 9
2
22th march
2022 11
3 23th march 2022 4
4
24th march
2022 9
5 25th march 2022 7
6 26th march 2022 10
7 27th march 2022 9
1

8 28th march 2022 2
9 29th march 2022 11
10 30th march 2022 19
Present the data using two types of appropriate charts
2

Determination as follows:
Mean
It is one of the significant part of the statistical technique which helps in evaluating the
average value of the give data set (Bădescu and O'Donnell, 2021).
S. No. Date
Data
related
to
Wind
speed
of
Bristol
city
1
21th march
2022 9
2
22th march
2022 11
3 23th march 2022 4
4 24th march 2022 9
5 25th march 2022 7
6 26th march 2022 10
7 27th march 2022 9
8 28th march 2022 2
9 29th march 2022 11
10 30th march 2022 19
sum 91
Mean 9.1
On the basis of the give table in the above tabular format it can be mentioned that sum
of the data set given for the 10 consecutive days (Bristol Weather, 2022). From the above report
it can be interpreted that mean value is 9.1. This is computed by applying the formula of having
sum of the 10 days wind speed and number of observation.
3

Mode
This is associated with having the information about the value which is repeated in the
given data set for more than 1. By referring the data set given for the wind speed of Bristol is
having the proper analysis it can be mentioned that the 9 is repeated for 3 times. This repeating
is indicating that this is the mode value of the provided information regarding the wind speed.
Median
It provides assistance in ascertaining centric value of the provided data (Dey and
Wang, 2022). The given information possessing 10 days which are even number so that below
formula will be applied for gaining result.
Formula = n/2 cell + (n/2+1)/2 cell
= 7+10/2
= 9
Range
Particular
s
Formula results
Max
value
19
min
value
2
Range Max value- min
value
17
On the basis of the given information regarding the range it can be mentioned that there
is requirement of ascertaining max and min values. From the assessment of the given
information it can be interpreted that max & min value of the wind speed of the Bristol city is 17
km/hr.
Standard Deviation
It is one of the major tool that is used for gaining the appropriate information about how
he dispersed data is relation to mean (Gong, Wang and Lin, 2021). The lower value indicates
that data is clustered around mean and high shows that data is more spread.
Date Data mean X-U (X-
4

related
to
Wind
speed
of
Bristol
city (U) U)^2
21 9 9.1 -0.1 0.01
22 11 9.1 1.9 3.61
23 4 9.1 -5.1 26.01
24 9 9.1 -0.1 0.01
25 7 9.1 -2.1 4.41
26 10 9.1 0.9 0.81
27 9 9.1 -0.1 0.01
28 2 9.1 -7.1 50.41
29 11 9.1 1.9 3.61
30 19 9.1 9.9 98.01
Total 91 186.9
Formula of standard deviation = √ Σ (X-U)^2/ 10
= √ 186.9/10
= √ 18.69
SD= 4.323
On the basis of the given information it can be mentioned that the data is more spread
out. This play significant role in wind speed forecasting so that appropriate information to
coordinate with the prevailing circumstances can become possible.
Using the linear forecasting for calculation
Date X
Data
related
to X*Y X^2
5

Wind
speed
of
Bristol
city
21 1 9 9 1
22 2 11 22 4
23 3 4 12 9
24 4 9 36 16
25 5 7 35 25
26 6 10 60 36
27 7 9 63 49
28 8 2 16 64
29 9 11 99 81
30 10 19 190 100
sum 55 91 542 385
Computing m value
m= NΣxy-ΣxΣy/(Σx^2)- (Σx)^2
= (10*542) -(55*91)/10*385- (55) ^2
= (5420-5005)/ (3850-3025)
=415 /825
= 0.50
Determination of c value
c = Σy- mΣx / n
= 91-0.50 (55)/ 10
= 91-27.66/ 10
= 63.34/ 10
= 6.334
6

forecasting wind speed on day 11 and day 13
11th day wind speed determination = mx+ c
= 0.50 (11) +6.334
= 5.5 +6.334
= 11.834
13th day wind speed determination = mx+ c
= 0.50 (13) + 6.334
= 6.5 +6.334
= 12.834
CONCLUSION
From the above report it can be summarized that data analysis is helpful in forecasting
the information in turn taking crucial actions for coordinating with the prevailing circumstances
can become possible. The current report has shown data set of the mentioned period in tabular
manner so that structure format for understanding outcomes. It has been presented in the
pictorial presentation for easy visualization of data. The particular data has mean, mode, median,
range and SD which are 9.1, 9, 9, 17 and 4.323 respectively. The wind speed for the 11th and
13th days are 11.834 & 12.834 km/h which is computed by using the linear equation into the
consideration.
REFERENCES
Books and Journals
7

Bădescu, C. and O'Donnell, R., 2021, June. Improved quantum data analysis. In Proceedings of
the 53rd Annual ACM SIGACT Symposium on Theory of Computing (pp. 1398-1411).
Dey, T.K. and Wang, Y., 2022. Computational Topology for Data Analysis. Cambridge
University Press.
Gong, X., Wang, Y. and Lin, B., 2021. Assessing dynamic China’s energy security: Based on
functional data analysis. Energy. 217. p.119324.Books and Journals
Online
Bristol Weather. 2022. [Online]. Available through :
<https://www.worldweatheronline.com/bristol-weather-history/bristol/gb.aspx>
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