Data on Humidity Level of London

MAIN BODY

1. Arrangement of data in tabular format

Days	Humidity
1	91
2	96
3	90
4	93
5	83
6	90
7	87
8	82
9	85
10	81

2. Representation of data in the chart format

Column Chart:

Line Chart:

Above mention charts represent the increasing or decreasing trend in the humidity in 10 continuous days (Kus, 2018). The first day humidity was 91 and and at the end of 10 days period it was 81. It represent the fluctuation in the humidity.

3. Calculation the range of statistical value

Days	Humidity
1	91
2	96
3	90
4	93
5	83
6	90
7	87
8	82
9	85
10	81
Total	878
Mean	87.800
Mode	89 & 90
Median	86
Range	15
Maximum	96
Minimum	81
Standard deviation	4.74

Mean: It can be defined as the process where average of any of the data is calculated. For the purpose of finding the means, it is necessary that all of the given number must be added in the beginning and then in second particular stage, it becomes important that after add all of the given number it must be divided by the number of data available to find exact mean amount.

Formula - ∑X/N

= 878 / 10

= 87.8

Median: In mathematical term, median can be defined as the process of determining the average of a group of number. For the purpose of doing the calculation of median it is necessary to observe the value in smallest to largest. If the value is in odd number then the median will be of middle number and if it is not in odd number then average to middle two terms will be required to obtain.

Formula – [N+1] / 2

= [ 10 + 1 ] / 2

= 5.5^th observation that is 87 & 90.

= 88.5

Mode: It is defined as the mathematical calculation where value is decided on the basis of frequent occurrence or even the value which is used for maximum times. The major advantage of mode is that it can be used in any type of given data but on the other hand of side, it is never possible in case of mean and median.

In this case, there is only one mode, which is 90 and it is repeating two times in 10 days (MalloyWeir and Cooper, 2017).

Range: It is explained as the process where difference between the highest and lowest value is required to be obtained (Range, 2018). The main advantage in range is it is very easy to do calculation in it and on the other hand the main cons in it is one of the sensitive to outlines where it doest give focus o n all of the available observations.

Formula = Maximum Value – Minimum Value

= 96 - 81

= 15

Standard deviation: In simple words, it can be defined as the measurement of dispersement in any of the statical terms. It gives the ideas about the data which has been spread out. It is calculated as on the basis of square root of variance where it is needed to determine the variation among each data which is related to mean.

Days	Humidity (x)	x- mean	(x-m)2
1	91	3.2	10.24
2	96	8.2	67.24
3	90	2.2	4.84
4	93	5.2	27.04
5	83	-4.8	23.04
6	90	2.2	4.84
7	87	-0.8	0.64
8	82	-5.8	33.64
9	85	-2.8	7.84
10	81	-6.8	46.24
225.6

Formula = √Variance

Formula of Variance = [ ∑ (x–mean)²/N ]

= 225.6 / 10

= 22.56

Standard deviation = √ 22.56

= 4.74

4. Apply linear forecasting model and calculate y = mx = c

Forecasting can be defined as the process where it is needed to understand that predicition is required to be done on the basis of past and present data or performance. It is mainly helpful to find out the result before starting any of the project. Applying liner forecasting model and X will be consider as days and Y is humidity (Mendez-Carbajo, Jefferson and Stierholz, 2019). Further calculation mentioned below:

Step 1: Table formulation

Days (X)	Humidity (Y)	X2	XY
1	91	1	91
2	96	4	192
3	90	9	270
4	93	16	372
5	83	25	415
6	90	36	540
7	87	49	609
8	82	64	656
9	85	81	765
10	81	100	810
∑x= 55	∑y= 878	∑X2= 385	∑XY= 4720

Step 2: Calculation of the value of M:

Formula: M = [N ∑XY - ∑x ∑y]/ [N ∑X² - (∑x)²]

= [ 10 * 4720 – (55 * 878) ] / [10*385- (55)² ]

= [47200 – 48290] / [3850 – 3025]

= -1090 / 825

= -1.32

Step 3: Calculation of value of C:

Formula = { ∑y - m ∑x } / N

= {878 – (-1.32 * 55)} / 10

= 950.6 / 10

= 95.06

Step 4: Humidity on 15^th day:

Formula = Y = mx + c

= -1.32 * 15 + 95.06

= -19.8 + 95.06

= 75.26

The level of humidity on 15^th day will be 75.26.

Step 5: Humidity on 20^th Day:

Formula = Y = mx + c

= -1.32 * 20 + 95.06

= -26.4 + 95.06

= 68.66

The humidity level on 20^th day will be 68.66.

CONCLUSION

From the above discussion it has been conclusion that data analysis use to gather information and use it in appropriate way. These information further beneficial for the future forecasting. With the help of statistical analysis, individual able to forecast the humidity for the future.

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