Numeracy and Data Analysis - Desklib

This report covers linear forecasting and descriptive statistics with their interpretation for understanding the data sets appropriately. Also, it computes the 11th and 12th day of the humidity value with the help of linear forecasting model. Learn about mean, mode, median, standard deviation and future humidity value using linear forecasting model.

Numeracy and Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................3
1. Arrangement of Humidity dataset of Belfast city of UK.........................................................3
2. Presentation of humidity dataset using Bar chart and scattered plot.......................................3
3. Calculation and comment on mean, mode, median and standard deviation of the dataset.....4
4. Calculation and comment on linear forecasting of the dataset................................................7
CONCLUSION................................................................................................................................9
REFERENCES................................................................................................................................1

INTRODUCTION
Data analysis is referred as the process of cleansing, modelling, inspecting and
transforming information for evaluating better results and understanding the real output of the
data (Campbell and et.al., 2020). This report covers linear forecasting and descriptive statistics
with their interpretation for understanding the data sets appropriately. Also, it computes the 11th
and 12th day of the humidity value with the help of linear forecasting model.
1. Arrangement of Humidity dataset of Belfast city of UK
Serial No. Date Humidity (%)
1 21st September 2022 68
2 22nd September 2022 83
3 23rd September 2022 94
4 24th September 2022 82
5 25th September 2022 82
6 26th September 2022 72
7 27th September 2022 88
8 28th September 2022 88
9 29th September 2022 77
10 30th September 2022 94
2. Presentation of humidity dataset using Bar chart and scattered plot
Bar Chart:

Scattered Plot:
3. Calculation and comment on mean, mode, median and standard deviation of the dataset
Descriptive statistics is referred as generation of summaries of a data set which is helpful
for the analyst to describe different features the available data. The steps of descriptive statistics
are as follows:

(I) Calculation of Mean
Formula of mean =
μ =
(68 + 83 + 94 + 82 + 82 + 72 + 88 + 88 + 77 + 94) / 10
= 828 / 10
= 82.8 or 83%
Comment: Mean provides details about the central tendency or average of a dataset. The above
results have interpretated that 82.8% or 83% is the average humidity of the Belfast city of UK
(Ali and et.al., 2019).
(II) Calculation of Median
Formula of median =
Sum of midterm (in case of more than one midterm) / number of two term
= (82 + 72) / 2
= 154 / 2
= 77%
Comment: Median is helpful in explaining the middle value of a dataset. It has been interpreted
from the above evaluation that the middle value of humidity of Belfast city is 77%
(III) Calculation of Mode
The value which occurred more than one time in a data set.
= 82% and 88%
Comment: Mode specifies the maximum number of repetitions which are made by a value in a
data set. It has been interpreted from the above calculation that 82% and 88% are the modes of
humidity in Belfast city.
(IV) Calculation of Range

Formula of range =
Maximum value – minimum value
= 94 – 68
= 26%
Comment: Range explains the difference between minimum and maximum value of a particular
dataset. The middle value of Belfast city humidity is 26%.
(V) Calculation of standard deviation
Formula of standard deviation =
σ =
Serial
No. y
Humidity
(%) x
x-
mean
x-
mean^2
1 68 -14.8 219.04
2 83 0.2 0.04
3 94 11.2 125.44
4 82 -0.8 0.64
5 82 -0.8 0.64
6 72 -10.8 116.64
7 88 5.2 27.04
8 88 5.2 27.04
9 77 -5.8 33.64
10 94 11.2 125.44
Mean 82.8
Total 675.6
σ = √675.6 / 10

= 8.21
Comment: Standard deviation is understood as the value which specifies the number of data
which differs from the mean value of the group. The above calculation has identified that 8.21 is
the standard deviation of humidity in Belfast city. This means that there is a difference of 8.21 in
the humidity of Belfast city every day (Guarnieri and et.al., 2019).
4. Calculation and comment on linear forecasting of the dataset
Formula of linear forecasting
Y = mx + c
Serial
No. x
Humidity
(%) y xy x^2
1 68 68 1
2 83 166 4
3 94 282 9
4 82 328 16
5 82 410 25
6 72 432 36
7 88 616 49
8 88 704 64
9 77 693 81
10 94 940 100
55 828 4639 385
(I) Calculation of m value
Formula =
=
= (10 * 4639) – (55 * 828) / (10 * 385) – (55)2
= (46390 – 45540) / 3850 – 3025
= 850 / 825

= 1.03
Comment: On the basis of the above result it is identified that the gradient descent is 1.03 which
specify the algorithm with the help of which best fit line for linear regression can be identified.
(II) Calculation of c value
Formula =
=
= 828 – (1.03 * 55) / 10
= 828 – 56.65 / 10
= 77.135
Comment: On the basis of the above calculation, it has been analysed that the constant value is
77.135. It means 77% is the humidity value which remain constant each day throughout the year
2022 (Liu and et.al., 2019). This is one of the best way to identify or forecast the future value of
the humidity of Belfast city of UK.
(III) Calculation of 11th and 12th day Belfast humidity value
Day 11
Y = (1.03 * 11) + 77.135
= 88.46 or 88%
Day 12
Y = (1.03 * 12) + 77.135
= 89.49 or 89%
Comment: After analysing the above result, it is interpreted that the humidity value of Belfast
city on 1st October 2022 will be 88%. While on the other hand, the humidity value of Belfast city

on 2nd October 2022 will be 89%. The linear forecasting method helps in predicating the weather
and humidity of city (Schreiber-Barsch, Curdt and Gundlach, 2020).

CONCLUSION
From the above report it has been concluded that the value of humidity of Belfast city of
UK on 1st and 2nd of October 2022. The report has appropriately concluded the various
descriptive statistics tool and its calculations such as mean, mode, median, range and standard
deviation. Further, proper comment on the ultimate result has been done in the report to predict
the future date humidity of Belfast city of UK. The report has concluded that with the help of
data gathering and analysis, various analyst of any organization able to predict its future sales
level. For this, they are required to use linear forecasting model which is an inferential statistics
type. Lastly, the report has also concluded the future humidity value of Belfast city.

REFERENCES
Books and journals
Ali, S. and et.al., 2019. E-Numeracy: Mobile Application of The Numeracy Understanding
Model for Primary School.
Campbell, L. and et.al., 2020. Literacy, numeracy and health and wellbeing across learning:
Investigating student teachers' confidence. International Journal of Educational
Research. 100. p.101532.
Guarnieri, R. and et.al., 2019. Test–Retest Reliability and Clinical Feasibility of a Motion-
Controlled Game to Enhance the Literacy and Numeracy Skills of Young Individuals
with Intellectual Disability. Cyberpsychology, Behavior, and Social Networking. 22(2).
pp.111-121.
Liu, Y. and et.al., 2019. The unique role of father–child numeracy activities in number
competence of very young Chinese children. Infant and Child Development. 28(4).
p.e2135.
Schreiber-Barsch, S., Curdt, W. and Gundlach, H., 2020. Whose voices matter? Adults with
learning difficulties and the emancipatory potential of numeracy practices. ZDM. 52(3).
pp.581-592.
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