BABS Foundation Numeracy and Data Analysis: Liverpool Humidity Report

This report presents a comprehensive analysis of Liverpool city's humidity levels from January 10th to 19th, 2020. The data is organized in a tabular format and visualized using both column and line charts to illustrate trends. The report calculates key statistical entities such as mean, median, mode, range, and standard deviation to provide a detailed understanding of the data. Furthermore, a linear forecasting model is employed to predict humidity levels for the 15th and 20th days, demonstrating the application of forecasting techniques. The report concludes with a summary of the findings and references relevant sources used in the analysis.

Humidity of Liverpool City

Table of Contents
Introduction......................................................................................................................................1
1. Arrange of Liverpool City in tabular format...........................................................................1
2. Illustrate data through two different charts.............................................................................1
3. Calculate distinct entities and illustrate final values...............................................................3
4. Make use of linear forecasting model.....................................................................................4
Conclusion.......................................................................................................................................6
References........................................................................................................................................7

Introduction
Numeracy implies abilities to reason as well as carry out simple numerical concepts. Data
analysis aids individuals within understanding of numbers as well as furnish output that will aid
within formulation of decision-making processes of the firm (Gunst, 2018). Numeracy and data
analysis are being utilised for assessment of information which will enable organisation to carry
out their business processes along with their operations. This report is based on humidity levels
of Liverpool City, UK and further analysis of data will be carried out with respect to this. This
report comprises of arrangement of data within tabular form and illustrated through different
charts. Furthermore, mean, median, mode and other entities will be calculated along with this the
linear forecasting model will be utilised for analysing humidity levels within the Liverpool City.
1. Arrange of Liverpool City in tabular format.
Below mentioned data is dependent on humidity levels of Liverpool City UK and it is
being presented from dates 10th January to 19th January 2020 (Liverpool 14 Day Extended
Forecast, 2020). 10 days consecutive data is being specified below within the table for having
better understanding.
Days Humidity
1 81
2 81
3 80
4 85
5 84
6 74
7 78
8 66
9 71
10 86
1

2. Illustrate data through two different charts.
Data is presented within column chart and is shown beneath:
The above column chart illustrates humidity levels of Liverpool City UK has slight variations. It
is observed that on 1st and 2nd day it is identical as well as 3rd is almost same. But on the 8th day
there is sudden decline within the humidity levels and on the 10th day it is maximum i.e. 86%.
Data presented in line chart format:
2
1 2 3 4 5 6 7 8 9 10
0
10
20
30
40
50
60
70
80
90 81 81 80
85 84
74 78
66
71
86
Days
Humidity Levels

The above mentioned line chart shows the trends within the humidity it is constant then
decrease, increase and again declines. Furthermore, it is inclined higher. On the initial day the
humidity was 81% and on last it is 86%.
3. Calculate distinct entities and illustrate final values.
Days Humidity
1 81
2 81
3 80
4 85
5 84
6 74
7 78
8 66
9 71
10 86
3
1 2 3 4 5 6 7 8 9 10
0
10
20
30
40
50
60
70
80
90
100
81 81 80 85 84
74 78
66 71
86
Days
Humidity Levels

Total 786
Mean 78.6
Mode 81
Median 79
Range 20
Maximum 86
Minimum
66
Standard
deviation 6.47
Mean: This denotes average value of total observation or data which is being provided
for carrying out analysis. Mean is being utilised for statistical purpose as well as calculation of
average value with respect to data (Johnston, 2017). The formula as well as calculation have
been illustrated below:
Formula: Mean = ∑X/N
= 786 / 10
= 78.6
Median: Within the statistical context, median implies the value that is being isolated
within the observation range. Here, data is isolated from upper as well as below half and is liable
for identification of middle value of the data that is being available (Kahan and Peters, 2017).
This involves two cases and each is being calculated through the usage of distinct formulas they
are specified beneath:
In case value is even: N + 1 / 2
When values are odd than: N / 2.
Formula: Median = [N+1] / 2
= [ 10 + 1 ] / 2
= 5.5th observation is 84 & 74.
= 79
4

Mode: This is one of the most recurrent value from the data series which is being
available is referred to as mode. If there exist more than one number which is being repeated
then two values will be taken into consideration as a mode (Gunst, 2018).
From the mentioned data series 81 is the number which is being repeated and is taken as
mode of the entire observation with respect to Liverpool City.
Range: Within statistics, the deviation among maximum as well as minimum values of
observation is referred to as range of specified series. This is being calculated like shown below:
Formula: Range = Maximum Value – Minimum Value
= 86 – 66
= 20
Standard deviation: This denotes measurement related with dispersion of values from
specified set of data. Lower standard deviation involves values that are closer to mean value and
on the other hand high values implies value which have wider range (Johnston, 2017). The
standard deviation for
humidity with respect to Liverpool City is 6.47.
4. Make use of linear forecasting model.
Through the assistance of linear forecasting model, people are liable for forecasting the
humidity levels with respect to future in which X is taken as number of days and Y denotes
humidity level for Liverpool City. Calculations have been illustrated beneath:
Step 1: Table formulation
Days (X)
Humidity
(Y) X2 XY
1 81 1 81
2 81 4 162
3 80 9 240
4 85 16 340
5 84 25 420
6 74 36 444
5

7 78 49 546
8 66 64 528
9 71 81 639
10 86 100 860
∑x= 55 ∑y= 786 ∑X2= 385 ∑XY= 4260
Step 2: Calculation of value of M:
Formula:
M = [N ∑XY - ∑x ∑y]/ [N ∑X2 - (∑x)2]
= [ 10 * 4260 – (55 * 786) ] / [10*385- (55)2 ]
= [42600 – 43230] / [3850 – 3025]
= 630 / 825
= 0.76
Step 3: Calculation of value of C:
Formula: C = ∑y - m ∑x / N
= (786 – 0.76 * 55) / 10)
= 744.2 / 10
= 74.42
Step 4: Humidity on 15th day:
Formula: Y = mx + c
= 0.76 * 15 + 74.42
=11.4+74.42
= 85.82
The level of humidity on 15th day will be 85.82
Step 5: Humidity on 20th Day:
Formula: Y = mx + c
= 0.76 * 20 + 74.42
= 15.2 + 89.67
= 89.62
The humidity level on 20th day will be 89.62.
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Conclusion
From above, it can be concluded that, through the assistance of data analysis business can
gather information, carry out analysis, evaluation as well as conduct measurements with respect
to future functioning. While carrying out data analysis, these factors must be taken into
consideration like mean, mode, median and other entities.
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References
Books & Journals
Gunst, R. F., 2018. Regression analysis and its application: a data-oriented approach.
Routledge.
Johnston, M. P., 2017. Secondary data analysis: A method of which the time has
come. Qualitative and quantitative methods in libraries. 3(3). pp.619-626.
Kahan, D. M. and Peters, E., 2017. Rumors of the'Nonreplication'of the'Motivated Numeracy
Effect'Are Greatly Exaggerated.
Online
Liverpool 14 Day Extended Forecast. 2020. [Online]. Available through:
<https://www.timeanddate.com/weather/uk/liverpool/ext>.
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