Statistical Analysis of Earnings

This assignment involves calculating various statistical categories (mean, median, mode, range) of hourly earnings for individuals based on their age, gender, and qualification. The data spans from 2000 to 2011 and includes both men and women with and without degrees. The results are presented in a table format. The assignment also references several academic articles related to numeracy, working memory, and statistical tools.

NUMERACY 1

SECTION 1
Task 1: Skills Audit
Task 2: Class Activity
Que. 1: Reflection
From the above stated auditing of self skills it can be assessed that, I have full knowledge
about the BODMAS from definition to the calculation performance. Further, this particular
aspect reflects to the Bracket, Order, Division, Multiply, Addition as well as Subtract. In the data
set if any kind of calculation is required to perform then I am able to apply rule of BODMAS in
proper manner. When considering to the fraction, denominator, mixed number as well as
numerator then I have knowledge up to the certain extent. Therefore, to perform appropriate
calculation I need better practice which will support to make me better in this aspect as well.
Moreover, about the ratios whether they are simple or another I have adequate knowledge and I
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not need any practice in this area. However, I am not sure about add, multiply, subtract as well as
divide in the numeracy.
Que. 2: Example
Order of operations:
When a person is going to perform calculation of some data or equation then it is
mandatory to consider the order to specific rule according to order of operations. Further, in this
BODMAS rule is applied on the equation of data set (Weller and et.al., 2013). For instance:
Illustration 1:
Illustration 2:
= 7 – 6 / 3 * 2 + 5
= 7 – 2 * 2 + 5
= 7 – 4 + 7
= 3 + 7
= 10 (solution)
Operations on positive and negative number:
When there are numbers given in positive values then known under the operations on
positive number. For instance:
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= 7 + 2 – 3
= 6
While having values with negative sign in the data set then come into consideration of
operations on negative number like:
= [(-7) + (-6)] – 6
= -19
Fractions:
When data or values presented in small divisions or in form of divide then considered
under fraction (Fraction, 2017). For instance:
½, 1/3, ¼ etc.
Ratios:
When data set presented in proportion manner or format along with reflecting
relationship between two values is known as ratios (Geary and et.al., 2013). For instance:
4:3 which can be presented as 1:3
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SECTION 2
Task 1: Skills Audit
Task 2: Class Activity
Que. 1: Reflection
According to the self skills auditing of section 2 it can be said that, for interpreting
relations among three tools like fractions, percentages as well as decimals I need some practice
due to having inadequate knowledge. Apart from this, under the decimal and fractional
equivalent also there is same condition as before. In terms of determining concepts as well as
processes related to accomplish every exercise I am not totally sure that I will complete it. It can
be assessed that, when calculation is required to done with the help of some formulas, simple
index needs to construct and interpret indexes also I required huge practice. Concluding to this
section then it can be said that I have inadequate knowledge about decimals, fractions, ratios etc.
Therefore, practice is required up to the larger extent which will help to me in the future for
performing proper computation.
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Que. 2: Example
Decimals:
Values which are shown after the decimal point in the data set is considered as decimals
with reference to numeracy. Further, it denotes with tenth, hundredths, thousandths etc
(Skwarchuk, Sowinski and LeFevre, 2014). Which is shown below:
Percentages:
A method through which each hundreds of the overall data set is calculated, known as
percentage. Moreover, for performing its computation the available data multiplies with '100'
only which is stated below:
= 0.635 * 100
= 63.5%
Index numbers:
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A data which multiplied with its same digit in accordance to given power is called as
index number in context to the numeracy (Kroesbergen, van’t Noordende and Kolkman, 2014).
Its illustrations are presented below:
3^4
= 3*3*3*3
= 81
Or
2^9
= 2*2*2*2*2*2*2*2*2
= 512
SECTION 3
Task 1: Skills Audit
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Task 2: Class Activity
Que. 1: Reflection
The section three is totally related with the statistical tools and techniques of which I
have adequate and proper knowledge. Along with this, for performing solutions of these tools I
not face any kind of problems and challenges. From the auditing related to such skills it can be
ascertained that, I can do well calculations of mean, mode, median as well as range of any kind
of data set. The reason is that I have better knowledge along with it is very simple and easy to
compute. Moreover, in order to implications or implementations of these all the statistical tools
also have adequate knowledge. Due to this, for when such methods are required to apply on data
set then I not require practice. Other that these all, for I can define pie, bar and line charts very
well with constructing these using data set. For making adequate interpretation and analyse of
such graphs that what these reflect also I am very well where I not need practice and support of
any other.
Que. 2: Example
Introducing statistical tools
 Mean: A method through which average value of the whole data set is calculated in
proper manner is known as mean. Further, it can be identified as average or arithmetic
mean as well in the area of statistics (Schwämmle, León and Jensen, 2013 ).
 Mode: A specific value which occurred in the available data set frequently or again and
again then assessed using mode method. Moreover, it reflects to the most frequently
incurred digit from the given data set.
 Median: According to this, when data needs to divide in two sections in equal proportion
then median statistical tool is taken into account. Range: A tool which reflects to difference among two values like the highest and the
lowest in data set is identified as range (Kastner and et.al., 2014).
Presenting data through graphs
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Pie chart
340
390
440
490
540
590 640
690
740
790 2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Bar Graph
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2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
0 100 200 300 400 500 600 700 800 900
340
390
440
490
540
590
640
690
740
790
54
62
70
78
86
94
102
110
118
126
Sales or revenue
Profit or income
Line Graph
2008200920102011201220132014201520162017
0
100
200
300
400
500
600
700
800
900
340 390 440 490 540 590 640 690 740 790
54 62 70 78 86 94 102 110 118 126
Sales or revenue
Profit or income
SECTION 4
Question 1
The present question shows about people in terms of percentage change who awarded
with degree among two years i.e. 2000 to 2011. Further, calculation of this is stated below:
Individual or people awarded in 2000 = 243245
People awarded in 2011 = 350800
Formula of percentage change = (new – old) / old
i.e. = People awarded in 2011-Those awarded in 2000/People awarded in 2000
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= (350,800 – 243,246) / 243,246 * 100
= 107554 / 243246 * 100
= 44.22%
Question 2
In this part females are computed who will achieve first degree at the end of year 1990.
Further, in the year 1980 females are 25319 which will be increased by 33.76%. On the basis of
this calculation is performed below:
= 25319 * 33.76%
= 8548 females
Therefore, additional females in the next ten years will be 8548 and total who will
awarded by first degree in year 1990 are:
= 25319 + 8548
= 33867 females
Question 3
Number of students in the year 2000 were 986267 and in the year 1999 they were 4.7%
less in England and Wales University. Further, students who were admitted in this university in
period 1999 are:
= 986267 – (986267 – 4.7%)
= 939912 students
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Que. 5
Answer a)
From the above chart, it can be assessed that people who are working for part-time and
live in England are 19%.
Answer b)
Looking at the above stated graph it can be seen that students who are in the employment
of full-time along and live in the area of Royal Greenwich are 17%
Answer c)
Higher number of people who are working for the full-time in comparison to self-
employed and live in London are stated below:
People working in full-time at London are 55%
Self-employed people at London are 16%
Therefore, more people working in full-time in comparison to self-employed are 39%
(55% - 16%).
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Question 6
Students who taken degree of postgraduate in terms of part-time at the end of academic
year 2011-12 in terms of percentage are stated below:
Students of postgraduate studied in part-time / total students * 100
= 109,535 / 1,117,335 * 100
= 0.0980 * 100
= 9.80% students
Question 7
Proportion of students of two types in terms of study i.e. postgraduate studied in part-time
and undergraduate studied in full-time in academic year 2015-15 is computed below:
Postgraduate part-time students: Undergraduate full-time students
= 107,120: 525,490
= 10712: 52549
= 10712 / 52549
= 0.204:1 ratio
Question 8
Computing statistical measures like mean, median as well as range of the college students
who were studied postgraduate as part-time from academic year 2005-06 to 2010-11.
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Que. 9
Difference among earnings of those women who are qualified as well as non-qualified in
terms of percentage is computed in this part. Further, these females belong from the age 34
years. Further, calculation is performed for this question below:
(Earnings of women with degree – Earnings of women without degree) / Earnings of women
without degree * 100
= (16.50 – 9.80) / 9.80 * 100
= 6.7 / 9.80 * 100
= 68.34%
Que. 10
Calculating four statistical categories of hourly earnings of each person on the basis pf
their age, gender as well as qualification from the year 2000-2010.
Degree No Degree
Age Men Women Men Women
A) Mean 19.6 15.6 11.9 9.1
B) Median 20.8 16.5 12.5 9.2
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C) Mode 22.3 16.8 13.2 8.7
D) Range 13.7 8.2 5.4 2.7
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REFERENCES
Journals and Books
Weller, J. A. and et.al., 2013. Development and testing of an abbreviated numeracy scale: A
Rasch analysis approach. Journal of Behavioral Decision Making. 26(2). pp. 198-212.
Geary, D. C. and et.al., 2013. Adolescents’ functional numeracy is predicted by their school
entry number system knowledge. PloS one. 8(1). p. e54651.
Skwarchuk, S. L., Sowinski, C. and LeFevre, J. A., 2014. Formal and informal home learning
activities in relation to children’s early numeracy and literacy skills: The development of a
home numeracy model. Journal of experimental child psychology. 121. pp. 63-84.
Kroesbergen, E. H., van’t Noordende, J. E. and Kolkman, M. E., 2014. Training working
memory in kindergarten children: Effects on working memory and early numeracy. Child
Neuropsychology. 20(1). pp. 23-37.
Schwämmle, V., León, I. R. and Jensen, O. N., 2013. Assessment and improvement of statistical
tools for comparative proteomics analysis of sparse data sets with few experimental
replicates.Journal of proteome research. 12(9). pp. 3874-3883.
Kastner, E. and et.al., 2014. High-throughput manufacturing of size-tuned liposomes by a new
microfluidics method using enhanced statistical tools for characterization. International
journal of pharmaceutics. 477(1). pp. 361-368.
Online
Fraction. 2017. [Online]. Available through:
<https://www.merriam-webster.com/dictionary/fraction> [Accessed on 27th October 2017].
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