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INDIVIDUAL PROJECT Table of Contents Table of Contents.............................................................................................................................2 INTRODUCTION...........................................................................................................................1 MAIN BODY..................................................................................................................................1 1. Data arrangement in table format............................................................................................1 2. Presentation of Data in Chart Format......................................................................................1
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3. Steps for calculating final value..............................................................................................2 4. Application of linear forecasting model..................................................................................4 Calculation of m value.................................................................................................................5 Calculation of c value..................................................................................................................5 Forecasting m and c value for 12thand 15thyear.........................................................................5 CONCLUSION................................................................................................................................6 REFERENCES................................................................................................................................7
INTRODUCTION Numeracy refers to presenting data in tabular format and through graphs and charts. It helps in analysing data in effective way.The present report collects Train Station Usage data for ten consecutive years of the rail station Earlswood (West Midlands). The station is a local station located in a small village in Warwickshire, England.The data will be analysed in tabular format and presented as column and line chart. In the same series, this will provide description of number of passengers with help of descriptive analysis such as mean, median, mode and standard deviation. It will represent about linear forecasting model was Y = mX + c with calculation m, c along with forecast of 12thand 15thyear. MAIN BODY 1. Data arrangement in table format 10 Years passenger entry exit Data-Collection ofEarlswood (West Midlands), England YEARDATA 200952014 201031038 2011108708 20123937 2013215541 2014217046 2015221111 20163188 20176138 20186600 2. Presentation of Data in Chart Format Column Chart 1
Line Chart 3. Steps for calculating final value Mean Mean refers to a type of average. The steps of mean are stated below: Every amount is added for the purpose of finding the sum Insert the number in tabular format (Sangeux, M. and et.al., 2016). 2
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Select black cell and enter formula of mean. Select the data for which it is to be calculated. Median Median refers to the first step of data determining which belongs to the odd or mean value as our data of exit and entry of passengers is comprised in a data set. It needs to be addressed and sorted in the ascending order from the greatest to the least. Enter the formula in blank cell and select the values. Press enter key to get result. Mode It is the value that is repeated many times in data set. The steps are described below :- List all the numbers in data Arrange it by using sort function In another cell write the formula for mode and press enter key. Identify value that comes for more than 1 time in table. Range It is the difference between highest and lowest data in data set. The steps are described below :- Identify the highest and lowest value from the data set (Ponton and Rovai, 2018) Subtract the highest from lowest and value obtained from it is known as range. Standards deviation It is known as how much does member of group differs from mean value. It can be calculated by :- First calculate mean value of data. Now, subtract mean value from each data in data set. Calculate the square value of above result and then find our aggregate of values At last aggregate is divided by 9 by N-1. Here, N refers to total number of observation. Outcome ParticularsAmount Mean86532.1 Median41526 3
ModeNA Minimum3188 Maximum221111 Range217923 Standard deviation96131.89 It can be interpreted from above table that mean value of past 10 years (that is 2009- 2018) of number of passengers at Earlswood (West Midlands) is 86532. Moreover, the median is 41526 of 10 years (Hazel and Gumbart, 2017). Also, there is no mode as no numbers are been repeated in the data. The maximum number of passenger is 221111 and minimum are 3188. Furthermore, the range is 217923 and standard deviation is 96131.89. 4. Application of linear forecasting model YearYear (x)Number of passengersXYX^2 2009152014520141 2010231038620764 201131087083261249 2012439371574816 20135215541107770525 20146217046130227636 20157221111154777749 2016831882550464 2017961385524281 201810660066000100 Total558653214530466385 Calculation of m value ParticularsDetails 4
mNΣxy – Σx Σy / NΣ x^2 – (Σx)^2 (10 *4530466 ) – (55 *865321 ) / (10 * 385) – (55)^2 (45304660 - 47592655)/(3850-3025) 2287995/ 825 -2273 Calculation of c value ParticularsDetails cΣy - mΣx / N ( 865321– (-2273 * 55))/10 865321+125015/10 877822 Forecasting m and c value for 12thand 15thyear. Forecast of 12th year Y= mX + C Y-2273(X) +877822 X12 Y-2273(12) + 877822 850546 Forecast of 15th year Y= mX + C Y-2273 (X) + 877822 X15 Y-2273 (15) + 877822 843727 5
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CONCLUSION From the above report, it could be concluded that numeracy and data analysis are very significant for analysing any details as it has shown in this with use of weather data of York. It has reflected level of humidity and for avoiding any argument there is representation of visual and tabular format. Moreover, it has provided descriptive statistics of data set and reflected application of linear forecasting model where 6