0 Cart

300k+ Satisfied
Students.

Rated 4.8/5

Based On Overall
6989 Reviews.

Order Now

Amazing Features We Offer

24*7 Help Service

100% Satisfaction
No Privacy Infringement Super-fast Services
Subject Experts
Professional Documents

Total Price

# Humidity Data of Manchester City

University: LONDON SCHOOL OF COMMERCE

• Unit No: 3
• Pages: 8 / Words 1919
• Paper Type: Assignment
• Course Code: WUC116
Question :

### Briefs:

You are needed to collect humidity data for ten consecutive days from any city of your choice. This data can be easily collected with the help of online sources. Also, prepare the report on the following areas:

• Arrange the data in a table format.
• Provide the data using any two types of charts of your choice. Example: Scatter plot, line chart, pictograms, histograms etc.
• Calculate and demonstrate the following. Please produce steps for the calculation and highlight the final value:
1. Means
2. Median
3. Mode
4. Range
5. Standard Deviation
• For your data, use the linear forecasting model which is y=mx+cto calculate and discuss the followings:
• Highlight the step of calculation ofmvalue and explain the answer.
• Show the steps of calculation of c value and discuss the answer.
• Using the calculated 'm' and 'c' values, forecast the humidity for days 15 and day 20.

### Learning Outcomes

1. Analyse and use techniques for summarising and analysing data.
2. Provide reasonableness in the calculation of answers.
3. Discus and evaluate techniques used for forecasting.

## INTRODUCTION

The term data analysis is a comprehensive tool of gathering and analysing monetary by help of different kinds of techniques (Laracy, Hojnoski and Dever, 2016). By help of this analysis, it becomes easier for managerial aspect of companies to take corrective actions. The report consists calculation of mean-mode-median as per the chosen data of humidity of Manchester city, United Kingdom (Humidity data of London, 2019.). In the further part of report projection of futuristic humidity percentage is done by applying linear regression model.

## 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:

 Date S. No. Humidity (in terms of %) 1st of October, 2019 1 94 2nd of October, 2019 2 84 3rd of October, 2019 3 96 4th of October, 2019 4 91 5th of October, 2019 5 95 6th of October, 2019 6 97 7th of October, 2019 7 95 8th of October, 2019 8 93 9th of October, 2019 9 83 10th of October, 2019 10 93

### 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:

#### Get Help in Any Subject

Our intention is to help numerous students worldwide through effective and accurate work.

### 3. Calculation of below mentioned items

 Date Humidity (in terms of %) 1st of October, 2019 94 2nd of October, 2019 84 3rd of October, 2019 96 4th of October, 2019 91 5th of October, 2019 95 6th of October, 2019 97 7th of October, 2019 95 8th of October, 2019 93 9th of October, 2019 83 10th of October, 2019 93 Total 921 Mean 92.1 Mode 93 Median 93.5 Range 14 (97-83) Standard deviation 4.84

(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 = Î£X/N

Î£X= 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/2th item + N/2th item + 1) / 2

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

Arrangement of data in ascending order:-

 S. No. Humidity (In %) 1 83 2 84 3 91 4 93 5 93 6 94 7 95 8 95 9 96 10 97

N= 10

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

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

= (5th item + 6th 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:

 Days (Date) Humidity (values in %) (x- mean) (x-mean)2 1st of October, 2019 94 1.9 3.61 2nd of October, 2019 84 -8.1 65.61 3rd of October, 2019 96 3.9 15.21 4th of October, 2019 91 -1.1 1.21 5th of October, 2019 95 2.9 8.41 6th of October, 2019 97 4.9 24.01 7th of October, 2019 95 2.9 8.41 8th of October, 2019 93 0.9 0.81 9th of October, 2019 83 -9.1 82.81 10th of October, 2019 93 0.9 0.81 210.9

Variance= [âˆ‘(x â€“ mean)2 / N]

= (210.9/10)

= 21.09

Standard deviation = âˆšvariance

= âˆš21.09

= 4.59

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

 Days (X) Humidity (Y) X2 âˆ‘XY Y2 1 94 1 94 8836 2 84 4 168 7056 3 96 9 288 9216 4 91 16 364 8281 5 95 25 475 9025 6 97 36 582 9409 7 95 49 665 9025 8 93 64 744 8649 9 83 81 747 6889 10 93 100 930 8649 âˆ‘X= 55 âˆ‘Y= 921 âˆ‘X2= 385 âˆ‘XY= 5057 âˆ‘Y2 = 85035

(I) Calculation of value of m:

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

= 10(5057)-(55)(931)/10(385)-(55)2

= 50570-51205/3850-3025

= -635/825

= -0.77

(iii) Forecasting of humidity:

For 15th day-

Y = m+cx

= 92.67+(-0.77*15)

= 92.67- 11.55

= 81.12%

For 20th 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

Special Offer

UPTO50% OFF

To view this & another 50000+ FREE