Weather Forecasting Analysis in Bristol

This assignment presents a weather analysis of Bristol, UK, covering ten days. It includes a table and graphs visualizing daily temperatures. The report delves into forecasting techniques, calculating key statistical measurements like mean and slope, and applying these to predict future weather conditions for day 15 and 23.

Numeracy and Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
1. Data set...............................................................................................................................3
2. Graphical presentation........................................................................................................4
3. Steps and calculation..........................................................................................................5
4. Using linear forecasting model presents y = mx +c...........................................................9
1. Steps for calculating “m value”..........................................................................................9
2. Steps for calculating “c value”...........................................................................................9
3. Forecasting of weather.....................................................................................................10
CONCLUSION..............................................................................................................................11
REFERENCES..............................................................................................................................12

INTRODUCTION
Numeracy and data analysis is considered as one of the most important statistical aspect for
every business organisation. Data gathered should be analyse in a proper and correct manner can
provide right interpretation to its end users. Every company should focus on making meaningful
and correct interpretation of its financial as well as statistical data and information in its financial
statements and books of accounts so that its end users viz. investors and other stakeholders can
make use of it. The present report is based on the arrangement and presentation of data set in a
bale form, line graph as well as column graph. The report is related to the weather conditions of
Bristol city of UK of the last 10 days i.e. from 22 December 2018 to 31 December 2018. Also,
the report will include the interpretation of weather condition of Bristol city ranging form highest
to the lowest temperature in the city. Further, the report will contain steps and calculation of
Mean, Mode, Median, Range and Standard Deviation. At last use of linear forecasting model will
be disclosed.
MAIN BODY
1. Data set
Data related to temperature (Bristol city of London) is as follows:
Date Temperature
22-Dec-18 7
23-Dec-18 6
24-Dec-18 6
25-Dec-18 9
26-Dec-18 6
27-Dec-18 7
28-Dec-18 8
29-Dec-18 9
30-Dec-18 8
31-Dec-18 7
The present data is related to the Bristol city of UK. On the basis of above table it can be
interpreted that the weather conditions in the city is keep on changing from the last 10 days.
Movement of weather conditions in Bristol is having fluctuating trend from 22 December 2018

to 31 December 2018. Within a period of 10 days, the city has observed a mixed weather
condition with the highest temperature of 9 degree Celsius and lowest temperature of the city
was 6 degree Celsius. It can be assessed that change in environment and weather conditions is
having a trend of both increase and decrease in the temperature.
2. Graphical presentation
Line graph – It is also known as the line chart which is defined as a type of chart basically used
for visualizing and monitoring the value of a given data set over a period of time.
Column graph – It is considered as one of the type of Bar graph which uses vertical bars for
displaying the given data set values.

Interpretation: From the above graph it can be interpreted, that within a period of 10
days from 22 December 2018 to 31 December 2018 there has been a drastic change in the
weather and environmental conditions of Bristol city of UK. It can be assessed easily with the
help of graphical representation that the weather conditions in Bristol is of fluctuating nature.
The highest temperature in the city was of 9 degree Celsius whereas the lowest temperature was
of 6 degree Celsius.
3. Steps and calculation.
Steps for calculating following is enumerated below :
1. Mean – First the set of values which has to be average has to determine. These
values of data set can be either of small or big number. Then, all the values of given
data set has to be added together. After adding up all the values in a given data set,
it has to be divided by the number of values in question.
Particulars Figures
Mean 7.3

2. Median – For determining the median value of a given data set, arrangement of set
of numbers has to be done in order of least to greatest. After arranging the numbers
in ascending order, if there is any even number of item given in the set of data, then
median value can be find out by taking average of this two middle numbers
(Camarillo, Dredger and Ratra, 2018).
Particulars Figures
Median 7

3. Mode – Mention all the numbers given in the data set and start ordering the
numbers from the smallest to the largest. After ordering in sequences, count the
number of times each number is repeating or coming. Identify the value which is
occurring the most, it is the mode value.
Particulars Figures
Mode 7

4. Range – List down all the data set elements. For determining the range value of a given
data set, one has to identify the highest and the lowest number from the given data set
value. After evaluating the highest and lowest number, subtraction will be done. The
Smallest number of data set is subtracted form the largest number and will be the range.
Range = Maximum – minimum value
Particulars Figures
Range 9 – 6 = 3
5. Standard Deviation – For assessing the standard deviation of the question, first mean or
the average value of the given data set has to be determined. After calculating the average
value, each number has to be subtracted from mean value (Ponton and Rovai, 2018). The
value assessed after subtraction needs to be squared and again mean of these squared
difference will be calculated. At last the square root will be done of value determined, it
will be the value if standard deviation.
Particulars Figures

Standard deviation 1.16
4. Using linear forecasting model presents y = mx +c.
1. Steps for calculating “m value”.
The m value is calculated by using formula:
m = NΣxy – Σx Σy / NΣ x^2 – (Σx)^2
Steps:
1. Multiply the value of x with the value of y. After multiplying make a summation of this value
and again multiply it with the value of number of set given. Nσxy is determined.
2. Add all the value of x and y individually to ascertain total value of x and y i.e. Σx & Σy.
After adding on individual basis, multiply the total value of x with the total value of y
(Savin, 2017).
3. Calculate the square of x value and sum it up. Multiply it with the value of number of set
given i.e. NΣ x^2
4. Square the x value after summing it up i.e. (Σx)^2.
5. Subtract the total value of step 2 by step 1.
6. Subtract the total value of step 4 by step 3.

7. Divide the value obtain from step 4 and step 5.
2. Steps for calculating “c value”.
For calculating the value of c, formula used is c = Σy - mΣx / N.
Steps:
1. Sum up the value of y
2. Multiply the summation value of x obtained with m value determined.
3. Subtract step 2 from step 1.
4. Divide the value obtain in step 3 from the number of value given.
3. Forecasting of weather.
Forecasting is a technique which helps in making future predictions and estimation for a
specified period of time. With the help of forecasting, weather of Bristol city of UK has been
indicated for 15 and 23 days.
Days
(x)
Temperature
(Y) XY X^2
1 7 7 1
2 6 12 4
3 6 18 9
4 9 36 16
5 6 30 25
6 7 42 36
7 8 56 49
8 9 72 64
9 8 72 81
10 7 70 100
55 73 415 385
m = NΣxy – Σx Σy / NΣ x^2 – (Σx)^2
= 10 (415) - (55 * 73) / (10 * 385) – (55)^2
= (4150 – 4015) / (3850 – 3025)

= 135 / 825
= .16
c = Σy - mΣx / N
= 73 – (.16 * 55) / 10
= (73 – 8.8) / 10
= 6.42
Forecasting weather of Day Y = mX + c
15 Here x = 15
Y = .16 (15) + 6.42
Y = 2.4 + 6.42
= 8.82
23
Here x = 23
Y = .16 (23) + 6.42
Y = 3.68 + 6.42
Y = 10.1
CONCLUSION
From the above report it can be concluded that by making correct and proper analysis of
data, it can help in making meaningful interpretation to its end users as well. The report has
discussed about the weather conditions of Bristol city of UK for 10 days with the help of a table
and bar graph and column graph. Also, report has defined the forecasting meaning and steps for
calculating some important statistical measurement tools.

REFERENCES
Books and Journals
Camarillo, T., Dredger, P. and Ratra, B., 2018. Median statistics estimate of the galactic
rotational velocity. Astrophysics and Space Science. 363(12). p.268.
Nemati, H. and et.al., 2015. Mean statistics of a heated turbulent pipe flow at supercritical
pressure. International Journal of Heat and Mass Transfer. 83. pp.741-752.
Ponton, M. K. and Rovai, A. P., 2018. Exact Solution for Pooled Standard Deviation.
Soler - Hampejsek, E. and et.al., 2018. Reading and numeracy skills after school leaving in
southern Malawi: A longitudinal analysis. International Journal of Educational
Development. 59. pp.86-99.
Savin, D. V., 2017. Statistics of a simple transmission mode on a lossy chaotic background.
arXiv preprint arXiv:1709.10479.
Sinhuber, M., Bewley, G. P. and Bodenschatz, E., 2017. Dissipative effects on inertial-range
statistics at high Reynolds numbers. Physical review letters. 119(13). p.134502.
Online
Mean value. 2019. [Online]. Available through:
<http://www.businessdictionary.com/definition/mean.html>.