Data Analysis and Forecasting: A Wind Speed Evaluation Report

This report focuses on analyzing wind speed data using various statistical methods, including mean, median, mode, range, and standard deviation. It also demonstrates linear forecasting to predict future wind speeds. The analysis involves data presentation using charts and detailed calculations to determine key statistical measures. By evaluating these metrics, businesses can make informed decisions, improve profitability, and mitigate risks. The report concludes by emphasizing the importance of data-driven insights for effective decision-making and strategic planning. This document is available on Desklib, a platform offering a wide range of study resources for students.

Data Analysis and
Forecasting

Contents
Contents...........................................................................................................................................2
INTRODUCTION...........................................................................................................................1
MAIN BODY..................................................................................................................................1
Evaluating data as per the wind speed.........................................................................................1
Presentation of data......................................................................................................................2
Mean............................................................................................................................................2
Mode............................................................................................................................................3
Median.........................................................................................................................................3
Range...........................................................................................................................................3
Standard Deviation......................................................................................................................4
Linear Forecasting.......................................................................................................................5
CONCLUSION................................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
In modern setting, numbers and information are valued highly, and this remark emphasises
the importance of figures and data investigation (Adekoya, 2017). In comparison, obtained data
should be handled in a way that makes it understandable, accessible, and comparable to those
other response variable. Each of the businesses in the chain is merging technological capabilities
to provide different insights on future collaborations. This information is crucial for predicting
industry and area trends. This information is essential for the establishment of financial
agreements in any sector. The capacity of a company to incorporate predictions can assist in
demonstrating methods for increasing profits while avoiding calamities. A variety of charts will
be used to explain the data, and also a technique for estimating wind speed that covered mean,
median, mode, standard deviation, and range which encompass a wide aspect and by proper
evaluation of this a company can stand well ahead of all its rivals in the longer term and that too
in a very quick period and can also gain an upper hand in the industry in which it is operating
and tends to expand in the similar sector (Bolino, Long and Turnley, 2016).
MAIN BODY
Evaluating data as per the wind speed

Presentation of data
3D column chart-
3D bar chart-
Evaluation of data for presentation
Mean
Mean: (μ) =
❑
∑ x
❑
N
Number of days: 10

Observing the wind speed: 750
Mean (μ): 750: 10 = 75 %
Therefore mean is 75 (Cong, Chen and Yang, 2016).
Mode
Number of days =10
Wind speed = 50, 65, 65, 70, 80, 85, 90, 85, 90, 70
Mode = 65%, 70%, 85% and 90%.
Therefore there are 4 modes as described above (Homburg, Jozić and Kuehnl, 2017).
Median
Formula for median = number of terms +1 divided by 2
The number of days = 10
Median = (10+ 1): 2 = 11/ 2= 5.5 %
Average median = (upper value + lower value): 2 = [70+80]: 2 = 75 %
Therefore median of the given series if 75 (North and Kumta, 2018).
Range
Range = (Largest value – smallest value)
Largest value of wind speed = 90 %
Smallest value of wind speed = 50%

Range = [90 – 50] = 40%
Therefore range of the series is 40 (Vlotman, Smedema and Rycroft, 2020).
Standard Deviation
Standard deviation (σ) =
x
❑
∑(¿−μ)
2
❑
N
❑√ ¿
Key Findings
Days Wind speed (%) Mean (μ) (x-μ) (x-μ)^2
1st 50 75 (50-75)=-25 625
2nd 65 75 (65-75)=-10 100
3rd 65 75 (65-75)-10 100
4th 70 75 (70-75)=-5 25
10th 70 75 (70-75)=-5 25
5th 80 75 (80-75)=5 25
6th 85 75 (85-75)=10 100
8th 85 75 (85-75)=10 100
7th 90 75 (90-75)=15 225
9th 90 75 (90-75)=15 225
Total Gross 750 0 1550
= √ [1550:10]
= 12.44 %

Linear Forecasting
Linear forecasting = (y = mx + c)
Value for m
Number of days= 10
m =
∑ x ¿ 2
N ∑ x2−¿ N ∑ xy−∑x ∑ y
¿

m = (10 x 4355 -55 x 750): (10 x 385 -55 x 55)
= 2300: 825
= 2.78
Linear forecasting is 2.78
Inculcating the value of c
The number of days = 10
c =
∑ y − m∑ x
N
c = [750 – 2.78x 55]: 10 = 747.22: 10 = 74.72.
Value of c is computed and it stands at 74.72.
Forecasting wind speed of 11th and 13th days
Values of m and c as per the linear forecasting
Linear forecasting formula = (y = 2.78 x + 74.72)
On the 11th day, the value of x is 11
Forecasting of wind speed of 11th day=
y = 2.78 x 11+ 74.72
y = 105.3 %

13th day, the value of x is 13
Forecasting of wind speed of 13th day=
y = 2.78 x 13+ 74.72
y = 110.86 %
CONCLUSION
This work illustrates how to calculate the mean, median, and mode, as well as anticipates
data, using progressively positive methodologies. In towns, wind speed is frequently used to
achieve such aspect which also possesses a lot of value in the market. These techniques can help
both enterprises and non-profit groups by helping them to predict earnings, compute and gather
essential data, and etc, enabling both to operate more effectively and affordably. Once it comes
to attaining corporate objectives in modern environment, insight is a valuable method for
examining and responding on historical, current, and future data. Researchers' days are jam-
packed of tasks including data processing. It's of no advantage if consumers have to browse
through numerous pages each day to get the information they want. However, in recent times, the
volumes of stuff accessible have significantly increased. It's excellent for researchers to have
more data that should presumably contribute to better examinations, but it's also a problem
because it could contribute to major employee fatigue on time, therefore it's critical to strike the
right mix among career and private activities for researchers.

REFERENCES
Books and journals