Table of Contents INTRODUCTION...............................................................................................................................3 MAIN BODY.......................................................................................................................................3 Ques. 1. Arrangement of data in table form.....................................................................................3 Ques. 2. Presentation of given data set with the help of bar chart and line chart............................3 Ques. 3. Calculation.........................................................................................................................4 Ques. 4. Forecasting of data set with the help of linear forecasting model.....................................7 1. Steps for calculating the m value.................................................................................................7 2. Steps for calculating the value of c..............................................................................................7 3. Forecasting the wind speed for 14 and 21 days...........................................................................7 CONCLUSION....................................................................................................................................9 REFERENCES...................................................................................................................................10
INTRODUCTION Data analysis is one of the most important process for every business organisation as it helps in deriving meaningful information from it. By analysis data in proper form with the help of different types of statistical as well as mathematical methods, it assists in decision making process of many business firms. The present report is based onBirminghamcity, which will analysis data about the wind speed of past ten consecutive days. Furthermore, it will define about steps of different types of statistical measures such as mean, range, median etc. At last, it will shed light on methods of determining the m and c value along with use of linear forecasting model for determining wind speed for 14 and 21 days ofBirmingham city. MAIN BODY Ques. 1. Arrangement of data in table form. DaysDateWind speed km/h 122/09/1915.55 223/09/1920.72 324/09/1919.51 425/09/1915.5 526/09/1925.74 627/09/1920.33 728/09/1919.67 829/09/1917.71 930/09/1922.42 1001/10/1923.27 Ques. 2. Presentation of given data set with the help of bar chart and line chart. 1.Bar chart
2.Line chart- Interpretation– From the above graph it can be interpreted that in the city of Birmingham, the wind speed in the past ten consecutive days has shown fluctuating trend. The highest speed of wind was observed on 26 September 2019 i.e. 25.74 km/h. Whereas, the city has witnesses the minimum speed on wind on 22 September 2019 i.e. 15.5 km/h. 22/09/2019 23/09/2019 24/09/2019 25/09/2019 26/09/2019 27/09/2019 28/09/2019 29/09/2019 30/09/2019 01/10/2019 051015202530 Wind speed Km/Hr 22/09/2019 23/09/2019 24/09/2019 25/09/2019 26/09/2019 27/09/2019 28/09/2019 29/09/2019 30/09/2019 01/10/2019 0 5 10 15 20 25 30 Wind speed Km/Hr
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Ques. 3. Calculation ParticularsFigure Mean20.042 Mode#VALUE! Median20 Standard deviation3.2617677552 Minimum15.5 Maximum25.74 Range10.24 Steps for calculating: 1.Mean-Collect all the data values of both the small and big numbers which average has to be determined. Add up all together so that a total can be find. After summing up, the next step is to count the number of values as falling in the data set. Now, divide the added value by total number of count determined so as to ascertain the mean value. DateWind speed km/h 22/09/1915.55 23/09/1920.72 24/09/1919.51 25/09/1915.5 26/09/1925.74 27/09/1920.33 28/09/1919.67 29/09/1917.71 30/09/1922.42 01/10/1923.27 N = 10 Total (∑X)200.42 Mean20.042 2.Mode-In order to evaluating modal value, all the numbers present in the data set needs to be sort down in order. After, sorting of number is done the next step is related with counting of each number present therein. The number which is repeating most is mode. ParticularsWind speed (in km/h) Mode#NA 3.Median-Arrange all the numbers from least to the greatest value. In case if items in the data set is even number, then median can be calculated by taking average of two middle numbers of arranged data set (Bethapudi and Desai, 2017).
DateWind speed km/h 22/09/1915.5 23/09/1915.55 24/09/1917.71 25/09/1919.51 26/09/1919.67 27/09/1920.33 28/09/1920.72 29/09/1922.42 30/09/1923.27 01/10/1925.74 Median (N + 1) / 25.5 item Median (Value of 5th item + value of 6th item) / 2 = (19.67 +20.33) / 2 = 20 4.Range-For calculating the range value of given data set, first the highest as well as lowest value in such set of data has to be determined. After identification of highest and lowest value, the value having lower degree will be subtracted from the highest number of the data set which will be called as range of that data set (Dickie, Feldman and Meyers, 2017). ParticularsFigures Maximum wind speed25.74 Minimum wind speed15.5 Range = Maximum – Minimum value10.24 5.Standard Deviation-First step is to find out the average value of present data. Then from each number present, mean has to be subtracted and result obtained needs to be square of. After, that mean of squared differences needs to evaluate (Massmann, Woods and Wagener, 2018). At last, square root of value obtained will be done for determining standard deviation value. DateWind Speed km/hX^2 22/09/1915.55241.8025 23/09/1920.72429.3184 24/09/1919.51380.6401 25/09/1915.5240.25 26/09/1925.74662.5476 27/09/1920.33413.3089
28/09/1919.67386.9089 29/09/1917.71313.6441 30/09/1922.42502.6564 01/10/1923.27541.4929 Total200.424112.5698 Standard deviation= SQRT of∑x^2 / N – (∑x / n) ^ 2 =SQRT of (4112.5698/ 10) – (200.42/ 10) ^ 2 = SQRT of411.25698– 401.681764 = SQRT of = 9.575216 = 3.094384591 Ques. 4. Forecasting of data set with the help of linear forecasting model. 1. Steps for calculating the m value. Formula for calculating m value ism = N Σxy – Σx Σy / N Σ x^2 – (Σx)^2.Steps includes following: 1.Value of x and y should be multiplied and summed up. 2.Then, value obtained in step 1 needs to be multiplied with total number of observation. 3.Summation of x and y values done on individual basis should be multiplied. 4.Square of x value needs to be done which will be added together and multiplied later on with total number of observation (Tracy, 2019). 5.Total number of observation should be squared up. 6.Step 4 – step 5 will be done 7.Step 2 – step 3 will be done. 8.Step 7 divided by step 6 will give value of m. 2. Steps for calculating the value of c. For evaluating the value of c, formula isc = Σy - mΣx / Nwith steps: 1.Sum total of y value needs to find out. 2.Value of x will be added up and multiplied with value of m as determined. 3.Value obtained in step 2 will be divided by total number of observation. 4.Step 1- step 3 will give value of c.
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3. Forecasting the wind speed for 14 and 21 days. DateNumber of days (X)Total wind speed (Y)XYX^2 22/09/19115.5515.551 23/09/19220.7241.444 24/09/19319.5158.539 25/09/19415.56216 26/09/19525.74128.725 27/09/19620.33121.9836 28/09/19719.67137.6949 29/09/19817.71141.6864 30/09/19922.42201.7881 01/10/191023.27232.7100 Total55200.421142.05385 ParticularsFormulaY = mX + c mNΣxy – Σx Σy / NΣ x^2 – (Σx)^2 M = 10 (1142.05) - (55 *200.42) / (10 * 385) – (55)^2 m = (11420.5 – 11023.1) / (3850 – 3025) m = 397.4 / 825 m = 0.48169697 cΣy - mΣx / N c =200.42– (0.48169697 * 55) / 10 c = (200.42–26.49333335) / 10 c = 173.92666665 / 10 c =17.392666665 Forecasting wind speed for 14 days Y = mX + cHere x = 14 days Y = 0.48169697(14) + 17.392666665 Y = 6.74375758 + 17.392666665 Y = 24.136424245 Forecasting wind speed for 21 days Y = mX + c Here x = 21 days Y = 0.48169697 (21) + 17.392666665 Y = 10.11563637 + 17.392666665 Y = 27.508303035
CONCLUSION From the above report it can be concluded that the wind speed of Birmingham city was showing fluctuating trend with the highest speed on 26 September 2019 i.e. 25.74 km/h and lowest on 22 September 2019 i.e. 15.5 km/h . Also, as per forecasting done for 14 and 21 days, speed of wind can be 24.136424245 km/h and 27.508303035 km/h respectively.
REFERENCES Books and Journals Bethapudi,S.andDesai,S.,2017.MedianstatisticsestimatesofHubbleandNewton's constants.The European Physical Journal Plus.132(2). p.78. Dickie,G. A.,Feldman,D.J.andMeyers,D.L.,InternationalBusinessMachinesCorp, 2017.Merging metadata for database storage regions based on overlapping range values. U.S. Patent 9,588,978. Iooss, B. and Lemaître, P., 2015. A review on global sensitivity analysis methods. InUncertainty management in simulation-optimization of complex systems(pp. 101-122). Springer, Boston, MA. Massmann, C., Woods, R. and Wagener, T., 2018, April. Reducing equifinality by carrying out a multi-objective evaluation based on the bias, correlation and standard deviation errors. InEGU General Assembly Conference Abstracts(Vol. 20, p. 11457). Schabenberger, O. and Gotway, C. A., 2017.Statistical methods for spatial data analysis. Chapman and Hall/CRC. Tracy,S.J.,2019.Qualitativeresearchmethods:Collectingevidence,craftinganalysis, communicating impact. John Wiley & Sons. Online Stepsforcalculatingstandarddeviation.2019.[Online].Availablethrough: <https://www.thoughtco.com/calculate-a-sample-standard-deviation-3126345>.