Numeracy And Data Analysis

This study material from Desklib covers the topic of numeracy and data analysis. It includes information on representing data in tabulated form, presenting data in charts, computing mean, median, mode, range and standard deviation, and forecasting values using equations. The material also provides examples and explanations for better understanding. Suitable for students studying numeracy and data analysis in various courses.

Numeracy And
Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................1
TASK...............................................................................................................................................1
1. Representation of selected data in tabulated form..............................................................1
2. Presenting data in different charts:.....................................................................................2
3. Computation of mean, median, mode, range and standard-deviation:...............................3
4. Computing values of m, c and humidity forecast of 15th and 20th Day:...........................5
CONCLUSION................................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
Data Analysis is a continuous procedure in which examine, improving, converting and
modelling data with the purpose of disclosing all the relevant information, arriving at conclusion
and helping in the decision making procedure (Conoyer, Foegen and Lembke, 2016). From the
analysis get all the effective outcomes which is utilised to display data foe easy consideration in
context of related data trends. These data based on the research and examine this for know about
particular things. Many times it based on the hypothesis. The utilisation of the data based on the
references and cover all criteria for measure resources. This report is based on the humidity data
analysis of the Manchester about 10 days. Along with also calculate humidity for 20th and 15th
day.
TASK
1. Representation of selected data in tabulated form
There are collect all the relevant data of humidity of the Manchester city, United
kingdom. The data has been p[resented into tabular format due to easily understand from 15
December 2019 to 24 December 2019.
Time Duration : 06:00 — 12:00
Days Humidity each day percentage
1st Day: 15, December, 2019 75
2nd Day: 16, December, 2019 86
3rd Day: 17, December, 2019 95
4th Day: 18, December, 2019 91
5th Day: 19, December, 2019 87
6th Day: 20, December, 2019 93
7th Day: 21, December, 2019 90
8th Day: 22, December, 2019 93
9th Day: 23, December, 2019 82
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10th Day: 24, December, 2019 94
2. Presenting data in different charts:
Bar charts: It is a way of summarizing a set of categorical data on the continuous
manner. This chart has been displayed by using a number of bars and every representation
categorised into particular activity. The height of every bar represents proportion of particular
aggregation. These classification could be related to particular age, geographical location
(English, and Watson, 2016).
Column Charts: It is a primary excel type of chart which is used by the business for
systematic data series plotted using vertical columns. Column chart is good way to present
different changes into particular things and become easy to compare with others.
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3. Computation of mean, median, mode, range and standard-deviation:
Time: 06:00 — 12:00
Days Humidity each day percentage
15 December 2019 75
16 December 2019 86
17 December 2019 95
18 December 2019 91
19 December 2019 87
20 December 2019 93
21 December 2019 90
22 December 2019 93
23 December 2019 82
24 December 2019 94
∑ X 886
Mean 88.6
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Median 87
Mode 93
Range 17
Maximum range 95
Minimum 75
Mean: It is applied to know average of selected data from the above table. For this apply
particular method and place amount to get results (Miller and et. Al, 2017).
Mean = ∑x / N
= 886 / 10
= 88.6
Mode: It highlight on the particular amount which repeat many times in the particular
data set. From this data set identify that the frequency of 93 is two times so it takes as a mode.
Median: From the presented data set selected mid amount so for this apply two types of formula
such as:
Where no. of data is odd, then:
 M= [(N + 1)/ 2]th value
Where no. of data is even, then:
 M= [ N/2th item + N/2th item + 1]/2 th value
Humidity each day percentage
75
86
95
91
87
93
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90
93
82
94
= {10/2+ 10/2 +1} / 2
= (5th item + 6th item) / 2
= (87 + 93) / 2
= 90
Range: This method applied to analysis the gap between the lowest and highest value
from the data set (Mulders, Corneille and Klein, 2018). There is taking amount about 10 days
and calculate on the basis of percentage such as:
Range = 95 -75 = 20
Standard Deviation:
Dates Wind (km/h) x- mean (x-m)2
01 December 2019 75 -10.8 116.64
02 December 2019 86 0.2 0.04
03 December 2019 95 9.2 84.64
04 December 2019 91 5.2 27.04
05 December 2019 87 1.2 1.44
06 December 2019 93 7.2 51.84
07 December 2019 90 4.2 17.64
08 December 2019 93 7.2 51.84
09 December 2019 82 -3.8 14.44
10 December 2019 94 8.2 67.24
432.8
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Variance = [ ∑(x – mean) 2 / N ]
= 432.8/10
= 43.28
Standard deviation: √ ( variance )
= √43.28
= 6.58
4. Computing values of m, c and humidity forecast of 15th and 20th Day:
Days
Humidity each day
percentage X2 ∑xy
1 75 1 75
2 86 4 172
3 95 9 285
4 91 16 364
5 87 25 435
6 93 36 558
7 90 49 630
8 93 64 744
9 82 81 738
10 94 100 940
55 886 385 4941
∑x= 55 ∑y= 886 ∑X2=385 ∑xy=4941
As per the above calculation that presented table then follow the particular steps to
analysis the particular amount of the “m” in equation of y = mx + c , as follows:
1. Compute value of M:
M = N * ∑xy - ∑x * ∑y / N*∑x2 - ( ∑x )2
= 10 * 4941 – 55 * 886 / 10 * 385- (55) 2
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= 49410 – 48730 / 3850 - 3025
= 1040 / 825
= 1.260
2. Assessment of value of c: ∑y - m ∑x/ N
= 886 – 1.260 * (55*10)
= 886 - 693
= 193
3. Through above computed/assessed data, prediction of humidity has been done here, as follows
Forecast humidity for 15 day Y= mx+c
Y= 1.26 * 15 + 193
= 211.9
= 21.19%
Forecast humidity for 20 day Y= mx+c
= 1.26 * 20 + 193
= 218.2
= 21.82%
CONCLUSION
As per the above discussion it is analysed that data analysis is required to know about
activities of any business. These numbers are presenting of different figures in order to conduct
different activities in appropriate manner. In this report collect data and analysis by mean, mode
and median method to get correct results.
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REFERENCES
Books and Journal
Conoyer, S. J., Foegen, A. and Lembke, E. S., 2016. Early Numeracy Indicators: Examining
Predictive Utility Across Years and States. Remedial and Special Education. 37(3).
pp.159-171.
English, L. and Watson, J., 2016. Making Decisions with Data: Are We Environmentally
Friendly?. Australian Primary Mathematics Classroom. 21(2). pp.3-7.
Miller, L. M. S. and et. al, 2017. Age differences in the use of serving size information on food
labels: numeracy or attention?. Public health nutrition. 20(5). pp.786-796.
Mulders, M. D., Corneille, O. and Klein, O., 2018. Label reading, numeracy and food &
nutrition involvement. Appetite. 128. pp.214-222.
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