Questions- This assessment will cover the following questions:
- Identify and use various techniques for summarising and analysing data and its usage for making logical reasoning.
- Explain forecasting techniques to real life situation and its role in analysing the data.
INTRODUCTION
The term data analysis can be defined as a systematic process of gathering monetary data and making proper analysis by help of different types of techniques. It consists various kinds of charts and diagrams in order to make an effective presentation of analysed data (Landtblom, 2018). The project report is based on the analysis of humidity data of London city of last ten days. Along with this analysis some other calculations are also done such as mean, mode, standard-deviation and many more. In the end part of report, calculation of m & c as well as forecasting of humidity is done for upcoming time by help of proper technique.
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 22nd of December to 31st of December (Humidity data of London, 2019).
Days (Date) |
Humidity (values in %) |
22nd of December, 2019 |
96 |
23rd of December, 2019 |
91 |
24th of December, 2019 |
92 |
25th of December, 2019 |
80 |
26th of December, 2019 |
98 |
27th of December, 2019 |
89 |
28th of December, 2019 |
99 |
29th of December, 2019 |
86 |
30th of December, 2019 |
100 |
31st of December, 2019 |
100 |
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:
Days (Date) |
Humidity (values in %) |
22nd of December, 2019 |
96 |
23rd of December, 2019 |
91 |
24th of December, 2019 |
92 |
25th of December, 2019 |
80 |
26th of December, 2019 |
98 |
27th of December, 2019 |
89 |
28th of December, 2019 |
99 |
29th of December, 2019 |
86 |
30th of December, 2019 |
100 |
31st of December, 2019 |
100 |
∑ X |
931 |
Mean |
93.1 |
Median |
94 |
Mode |
100 |
Range |
20 |
Maximum range |
100 |
Minimum |
80 |
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/2th item+ N/2th item + 1}2
Herein, below calculation of median of humidity data is done below in such manner:
Humidity (in terms of %) |
80 |
86 |
89 |
91 |
92 |
96 |
98 |
99 |
100 |
100 |
= {10/2+ 10/2 +1} / 2
= (5th item + 6th 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:
Days (Date) |
Humidity (values in %) |
x- m |
(x-m)2 |
22nd of December, 2019 |
96 |
2.9 |
8.41 |
23rd of December, 2019 |
91 |
-2.1 |
4.41 |
24th of December, 2019 |
92 |
-1.1 |
1.21 |
25th of December, 2019 |
80 |
-13.1 |
171.61 |
26th of December, 2019 |
98 |
4.9 |
24.01 |
27th of December, 2019 |
89 |
-4.1 |
16.81 |
28th of December, 2019 |
99 |
5.9 |
34.81 |
29th of December, 2019 |
86 |
-7.1 |
50.41 |
30th of December, 2019 |
100 |
6.9 |
47.61 |
31st of December, 2019 |
100 |
6.9 |
47.61 |
Total |
406.9 |
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.
Days (Date) |
Humidity (values in %) |
X2 |
∑XY |
1 |
96 |
1 |
96 |
2 |
91 |
4 |
182 |
3 |
92 |
9 |
276 |
4 |
80 |
16 |
320 |
5 |
98 |
25 |
490 |
6 |
89 |
36 |
534 |
7 |
99 |
49 |
693 |
8 |
86 |
64 |
688 |
9 |
100 |
81 |
900 |
10 |
100 |
100 |
1000 |
∑X= 55 |
∑Y= 931 |
∑X2= 385 |
∑XY= 5179 |
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 20th day.
To get more details about online assignment help connect with us.