Data Analysis and Forecasting of Wind Speed in Bristol City, UK
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Added on 2023/06/10
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This study involves the analysis and forecasting of wind speed in Bristol City, UK for the last ten consecutive days. Mean, median, mode, range, and standard deviation are calculated and discussed. Linear forecasting model is used to calculate the wind speed on the 12th and 14th day of Bristol, UK.
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Table of Contents 1. Dataset arrangement of Wind Speed of Bristol City of UK for last ten consecutive days......3 2. Presenting the above dataset using two chart types.................................................................3 3. Calculation and discussion of mean, median, mode, range and standard deviation................4 4. Calculation and discussion of m, c 12thand 14thday value of data set using linear forecasting model...........................................................................................................................................6 (I) Calculation of m value............................................................................................................8 (II) Calculation of c value............................................................................................................8 (III) Forecasting wind speed on 12thand 14thday of Bristol, UK................................................9 REFERENCES................................................................................................................................1
1. Dataset arrangement of Wind Speed of Bristol City of UK for last ten consecutive days Serial. No.Date Wind Speed (MPH) (Bristol) 130thApril, 202221 21thMay, 202222 32thMay, 20229 43thMay, 202214 54thMay, 20228 65thMay, 202216 76thMay, 202215 87thMay, 202214 98thMay, 202212 109thMay, 202211 2. Presenting the above dataset using two chart types Line Chart: Bar Chart:
3. Calculation and discussion of mean, median, mode, range and standard deviation (I) Mean = μ = Here, Σ x = Sum of the dataset N = Number of observation = (21 + 22 + 9 + 14 + 8 + 16 + 15 + 14 + 12 + 11) / 10 = 142 / 10 = 14.2 On the basis of above calculation, it has been analysed that the average wind speed in the last ten consecutive days’ in Bristol is 14.2 MPH. It means average speed of wind will remain 14.2 MPH. (II) Median Formula = Sum of mid value / Number of term (In case when more value appears in mid dataset) = (8 + 16) / 2
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= 12 On the basis of above calculation, it has been analysed that the mid value of the dataset is 12. It means the middle value of wind speed in last ten days is 12 MPH. (III) Mode The value that appear that appear frequently in dataset = 14 The mode is a statistical measure which state the value within the dataset that appear frequently that is more time. On this basis, 14 MPH is a wind speed that appear two time in the dataset thus the mode value is 14 (Bacit, 2019). (IV) Range Formula = Upper Value – Lower Value = 21 – 11 = 10 The difference between upper value and lower value of dataset is known as range. On the basis of above calculation, the range is 10 MPH. (V) Standard Deviation Formula: σ = DateWind Speed (MPH) (Bristol)(X- Mean)(X-Mean)^2
30thApril, 2022216.846.24 1thMay, 2022227.860.84 2thMay, 20229-5.227.04 3thMay, 202214-0.20.04 4thMay, 20228-6.238.44 5thMay, 2022161.83.24 6thMay, 2022150.80.64 7thMay, 202214-0.20.04 8thMay, 202212-2.24.84 9thMay, 202211-3.210.24 Mean14.2191.6 σ =√191.6 / 10 = 4.3772 Standard deviation is value that express the dispersion of the dataset relative to its mean and basically computed as a square root of the variance. The standard deviation of current dataset as per above calculation is 4.3772. This indicate that each day wind speed is 4.3772 time differ than the mean of the wind speed such as 14.2. The standard deviation helps in the study of the data and also make the interpretation of dataset easier. With the help of SD, the amount of data that is clustered around the mean value is shown (Schreiber-Barsch, Curdt and Gundlach, 2020).
4. Calculation and discussion of m, c 12thand 14thday value of data set using linear forecasting model Linear Forecasting Model Formula Y = mx + c This is one of the best model to forecast the future value of the dataset and with the help of this model, the 12thand 14thday of wind speed is easily computed. Serial. No. (X) Date Wind Speed (MPH) (Bristol) (Y) xyx^2 130thApril, 202221211 21thMay, 202222444 32thMay, 20229279 43thMay, 2022145616 54thMay, 202284025 65thMay, 2022169636 76thMay, 20221510549 87thMay, 20221411264
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98thMay, 20221210881 109thMay, 202211110100 55142719385 (I) Calculation of m value Formula = m = (10 * 719) – (55 * 142) / (10 * 385) – (55)2 m = 7190 – 7810 / 3850 – 3025 m = -620 / 825 m = -0.7515 The above calculation indicates the m value is -0.7515 which is basically the slope of linear forecasting mode (Lüssenhop and Kaiser, 2020). The slope is negative which indicate negative correlation between days and wind speed variable. (II) Calculation of c value Formula = c = 142 – (-0.7515 * 55) / 10 c = 142 – (-41.3325) / 10 c = 183.3325/ 10 c = 18.3332
According to above calculation, it has been analysed that the c value of linear forecasting model is 18.3332 which is intercept value. This is also known as constant that represent the mean value of responses variable when other predictor value is zero (Aunio and et.al., 2019). (III) Forecasting wind speed on 12thand 14thday of Bristol, UK Expected Wind speed on 12thday Formula = Y = mx + c Here, m = -0.7515 x = 12 c = 18.3332 Y = (-0.7515 * 12) + 18.3332 = -9.018 + 18.3332 = 9.3152 or 9 MPH approx. On the basis of above calculation using linear forecasting model, it has been forecasted that the wind speed on 12thday of Bristol will be 9 MPH approx. It means on 11thMay 2022, the wind speed will reduce to 9 MPH from 11 MPH on 10thday i.e., 9thMay 2022. Expected wind speed on 14thday Formula = Y = mx + c Here, m = -0.7515 x = 14 c = 18.3332 Y = (-0.7515 * 14) + 18.3332 = -10.521 + 18.3332 = 7.8122 or 8 MPH approx. Also, with the use of linear forecasting model, it has been forecasted that the wind speed will further reduce to 8 MPH on 14thday i.e., 13thMay 2022. This means that on 14thday the wind speed will reduce as per trend (Zeuner, Pabst and Benz-Gydat, 2020).
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REFERENCES Books and journals Bacit, J. K., 2019. Impact Assessment of Numeracy Assessment tools with E-games in the PerformanceinMathematicsofGrade8StudentsofBilaranNationalHigh School.Ascendens Asia Journal of Multidisciplinary Research Abstracts.3(2E). Schreiber-Barsch, S., Curdt, W. and Gundlach, H., 2020. Whose voices matter? Adults with learning difficulties and the emancipatory potential of numeracy practices.ZDM.52(3). pp.581-592. Lüssenhop, M. and Kaiser, G., 2020. Refugees and numeracy: what can we learn from international large-scale assessments, especially from TIMSS?.ZDM.52(3). pp.541-555. Zeuner, C., Pabst, A. and Benz-Gydat, M., 2020. Numeracy practices and vulnerability in old age: Interdependencies and reciprocal effects.ZDM.52(3). pp.501-513. Aunio, P. and et.al., 2019. Multi-factorial approach to early numeracy—The effects of cognitive skills, language factors and kindergarten attendance on early numeracy performance of South African first graders.International Journal of Educational Research.97. pp.65-76. 1