Humidity Data of Manchester City

MAIN BODY

1. Arrangement of data in table format

In accordance of requirement of brief under this task, humidity data of 10 days of London city has been shown in table format:

2. Presentation of data in two charts

Bar chart- This can be defined as a type of diagram that presents free sample quantitative data in the form of horizontal bars. Underneath, presentation of humidity data has been done in the form of bar chart:

Column chart- This can be defined as a type of diagram that presents quantitative data in the form of vertical heights (Geiger, Goos and Forgasz, 2015). Underneath, presentation of humidity data has been done in the form of column chart:

3. Calculation of below mentioned items

(I) Mean- The value of mean is calculated by dividing total of data values from number of values. Underneath, mean is computed by applying formula that is as: Mean = ΣX/N

ΣX= 921

N = 10

Mean = 921/10

= 92.1

(ii) Mode- In simple terms, mode is a kinds of number whose frequency is higher in a particular data set. This is presented by Z. In the above data set of humidity, value of Z is 93 because this value has maximum frequency.

(iii) Median- This is defined as mid value among different range of number of a data set (Shalley and Stewart, 2017). This is denoted by M. Herein, below formula to calculate median is mentioned in such manner:

If data set is odd:

M = (N+1)/2

If data set is even:

M= (N/2^th item + N/2^th item + 1) / 2

Calculation of median as accordance of humidity data of 10 days-

Arrangement of data in ascending order:-

N= 10

Median = (N/2^th item + N/2^th item + 1)/2

= (10/2^th item + 10/2^th item + 1)/2

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

= (93+94)/2

= 93.5

(iv) Range- It is calculated by making variation between higher and lower value of a data series (Cahoon, Cassidy and Simms, 2017). Such as per the above mentioned humidity data, this can be find out that value of range is of 14.

(v) Standard-deviation- It can be defined as calculation of value of variation from a data set. In accordance of above humidity data, standard-deviation is computed below in such manner:

Variance= [∑(x – mean)² / N]

= (210.9/10)

= 21.09

Standard deviation = √variance

= √21.09

= 4.59

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

(I) Calculation of value of m:

m= (∑Y)(∑X²)- (∑X)(∑XY) / n(∑X²)-(∑X)²

= (921)(385)-(55)(5057)/10(385)-(55)²

= 354585-278135/ 3850-3025

= 76450/825

= 92.67

(ii) Calculation of value of c:

c= n(∑XY)- (∑X)(∑Y) / n(∑X²)-(∑X)²

= 10(5057)-(55)(931)/10(385)-(55)²

= 50570-51205/3850-3025

= -635/825

= -0.77

(iii) Forecasting of humidity:

For 15^th day-

Y = m+cx

= 92.67+(-0.77*15)

= 92.67- 11.55

= 81.12%

For 20^th day-

= 92.67+ (-0.77*20)

= 92.67- 15.4

= 77.27%

CONCLUSION

On the basis of above project report, this can be concluded that data analysis technique is not limited till any specific department for taking decisions. It is needed any kinds of business entity for better decision-making. The report concludes about calculation of mean-mode-median, range and standard-deviation of humidity data of Manchester city. In the end part of report, forecasting of humidity is done by help of linear regress