Data Analysis and Calculations of Mean, Mode, Median

MAIN BODY

1. Representation of data in tabular form:

Herein, below presentation of gathered data regards to humidity percentage in London, UK is done. This data is gathered from 22^nd of December to 31^st of December (Humidity data of London, 2019).

2. Dara representation in charts:

Bar Graph: A bar graph is being used to clearly show data using bars of different heights or distances. It contributes in a significant manner in order to understand about analysed data in most effective way. Herein, below presentation of above humidity data is done in such manner:

Column Chart: A column diagram is a chart which of data shows vertical bars horizontally around the chart, with the value axis shown on the graph's left side (Leech, Barrett and Morgan, 2013). Same as the above graph, this is also prepared in the excel sheet. Herein, below presentation of above humidity data is done in column chart which is as follows:

3. Calculations of mean, median, mode, standard deviation and range:

Mean- The term mean can be defined as an average of gathered monetary data (Beyer, 2019). This is calculated by a particular formula which is as: Mean = ∑N/ N. Herein, below calculation of mean value is done in such manner:

N= 10

∑N = 931

Mean = 931 / 10

= 93.1

Also Read:- Data Analysis and Decision Making

Median = As name assists, it can be defined as a mid value of number of data series. This calculated by a formula which is applied in accordance of number data.

If number of data is odd then, M= (N+1 / 2)th item

If number of data is even then, M= {N/2^th item+ N/2^th item + 1}2

Herein, below calculation of median of humidity data is done below in such manner:

= {10/2+ 10/2 +1} / 2

= (5^th item + 6^th item) / 2

= (92+96)/2

= 94

Mode- The term mode can be defined as set of data value which appears most of times from a group of numbers. Such as in the aspect of above data of humidity this can be find out that humidity of 100% has bee incurred with higher frequency of 2. Thus, the value of mode is of 100.

Range- This can be defined as difference between higher value and minimum value from group of numbers. Herein, below in the context of above set of data of humidity this can be find out that higher value is of 100 and lower is of 80. Hence, the range is (100-80)= 20.

Standard deviation- Standard Deviation is a quantitative term used to assess the average number of variation or diffusion (Sarkar and Rashid, 2016). Functionally, it's a kind of volatility measure. Herein, below calculation of standard-deviation is done in such manner:

Variance= [ ∑(x – mean) ² / N ]

= 406.9/10

= 40.69

Standard deviation: √ ( variance )

= √40.69

= 6.38

4. Calculating values of m, c and wind forecast of day 15 and 20.

Form above computations summarised in table, following are the steps to find out the value of “m” in equation which is y = mx + c , as follows:

1. Compute value of M:

M = N * ∑xy - ∑x * ∑y / N*∑x² - ( ∑x )²

= 10*5179-55*931/10*385-(55) ²

= 51790- 51205/3850-3025

= 585/825

= 0.71

2. Computation of value of c: ∑y- m ∑x/ N

= 931- 0.71 * 55*10

= 540.5

3. In accordance of above calculated data, forecasting of humidity is done below in such manner:

Forecast humidity for 15 day Y= mx+c

Y= 0.71*15+540.5

= 551.15

= 55%

Forecast humidity for 20 day Y= mx+c

= 0.71*20+540.5

= 554.7 or 55.4%

CONCLUSION

On the basis of above project report it has been concluded that data analysis is too crucial in order to compute any particular result from collection of wide range of data series. The report concludes about calculation of mean-mode-median as per given data set. As well as standard-deviation is also computed. In the end part of report, forecasting of humidity percentage is done of 15 and 20^th day.

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