Data Analysis and Interpretation

This assignment comprises a series of data analysis tasks focusing on statistical interpretation. It involves manipulating and analyzing datasets using Python or R, with tasks ranging from basic descriptive statistics to more complex inferential analyses. The goal is to enhance understanding of data-driven decision making and prepare for statistical exams.

Income Increase Happiness?

Executive Summary
In the current investigation, emphasis has been placed by the researcher on analysing the
effect of income on happiness. In addition to this, to address research questions data has been
gathered from both primary and secondary sources. By conducting survey on 20 individuals, data
have been gathered. Descriptive and regression analysis tool has been applied by the researcher
to evaluate research issue. From evaluation, it has assessed that majority of the respondents were
happy from their income. It can be depicted from evaluation that along with the income,
happiness influences from several factors such as stress, improper balance in life etc.

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
Methods of data collection...........................................................................................................1
Summary of data set....................................................................................................................1
Descriptive statistics or data analysis........................................................................................10
Simple linear regression............................................................................................................11
CONCLUSION..............................................................................................................................16
RECOMMENDATIONS...............................................................................................................16
REFERENCES..............................................................................................................................17
APPENDIX....................................................................................................................................18

Topic: To analyse the extent to which income level of individuals affect their happiness.
INTRODUCTION
In the current times, significant changes have taken in the living standard of
individuals.In this regard, individuals can fulfil their desire only when they earn enough money
or havinghigh disposable income. The main motive carry out present investigation is to analyse
the extent to which income earned by the individuals have an influence on their happiness. For
this purposes, individuals of Australia has been selected on which study will be focused. In this,
study will shed light on the techniques that undertaken by scholar for sample selection, data
collection and analysis.
Methods of data collection
By conducting survey on 20individuals or households, primary data was gathered.
Through including both qualitative and quantitative questions in the questionnaire,views of
individuals were gathered to ascertain the level of association between income and happiness. In
this, to meet research objectives 20 individuals were selected through applying simple random
sampling technique.The rationale behind considering such sampling technique is that it avoids
level of biasness to a great extent and helps in presenting suitable solution of issue (Etikan, Musa
and Alkassim, 2016).In addition to this, both thematic and quantitative evaluation was done to
discover suitable information from data set. Graphical presentation of data set was done to reflect
the views of respondents in a structured way. Hence, descriptive and regression analysis tool was
applied to assess the impact of income on happiness. Further, findings of both qualitative and
quantitative data set were also supported with the similar kind of studies.
Summary of data set
1. Age
Particulars
Views of
respondents
% of
respondents
18-30 8 40%

31-40 4 20%
41 and
older 8 40%
Total 20 100%
18-30 31-40 41 and older
0%
5%
10%
15%
20%
25%
30%
35%
40%
% of respondents
% of respondents
Interpretation: Graphical presentation shows that 20% respondents fallen within the age
group of 31-40 years. On the other side, 40% individuals having age of 18-30, whereas
remaining 40% accounted for the category of 31 and older.
2. Gender
Particulars
Views of
respondents
% of
respondents
Male 11 55%
Female 9 45%
Total 20 100%

Male Female
0%
10%
20%
30%
40%
50%
60%
% of respondents
% of respondents
Interpretation: Outcome of survey shows that majority of the respondents
(approximately 55%) were male and remaining 45% accounted for females.
3. Marital status
Particulars
Views of
respondents
% of
respondents
Single 8 40%
Married 10 50%
Divorced 8 10%
Total 20 100%
Single Married Divorced
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
% of respondents
% of respondents

Interpretation: Tabular presentation exhibits that 50% respondents were married. On the
other side, 40% respondents presented in the survey they were single and remaining 10 %
divorced.
4.Earnings weekly
Particulars
Views of
respondents
% of
respondents
0 - 500
AUD - -
500 - 1000
AUD 10 50%
More than
1000 AUD 10 50%
Total 20 100%
0 - 500 AUD 500 - 1000
AUD More than
1000 AUD
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
% of respondents
% of respondents
Interpretation: The above depicted graph entails that 50% respondents are earning 500-
1000 AUD weekly. In contrast to this, weekly income of remaining 50% individuals implied for
more than 1000 AUD. Thus, considering such aspect it can be stated that weekly income of
selected respondents were good.
5. Working hours weekly
Particulars Views of respondents % of respondents
Less than 20 - -
20-40 4 20%

More than 40 16 80%
Total 20 100%
20-40 More than 40
0%
10%
20%
30%
40%
50%
60%
70%
80%
% of respondents
% of respondents
Interpretation: In survey, 80% respondents shared their views that they work for more
than 40 hours in a week. Further, 20% respondents said that they are working 20-40 hours in a
week.
6. Weekly spending on utilities and necessities from income
Particulars Views of respondents % of respondents
Less than 10% 7 35%
10% - 25% 10 50%
25% - 50% 3 15%
More than 50% - -
Total 20 100%

Lees than 10% 10% - 25% 25% - 50%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
% of respondents
% of respondents
Interpretation:Primary data outcome entails that 50% individuals selected for
investigation spends 10-25% of their income weekly. On the other side, spending of 35%
respondents on utilities and other necessities implies for less than 10%. Further, graphexhibits
that 15% individuals prefer to spend 25-30% of their income on necessities.
7. Weekly savings from income
Particulars Views of respondents % of respondents
Less than 10% 6 30%
10% - 25% 7 35%
25% - 50% 4 20%
More than 50% 3 15%
Total 20 100%

Lees than
10% 10% - 25% 25% - 50% More than
50%
0%
5%
10%
15%
20%
25%
30%
35%
% of respondents
% of respondents
Interpretation: By doing primary investigation, it has identified that 35% respondents
tend to make focus on saving 10% to 25% weekly. Out of 20, only 3 individuals stated that their
weekly saving isgreater than 50%. Further, 6 individualsparticipated in survey entails that saving
of them isless thanpertaining to10% of income.On the other hand, weekly savings of 20%
individuals fall within the range of 25 to 50%.
8. Supporting individuals from income
Particulars Views of respondents % of respondents
Yes 10 50%
None 10 50%
Total 20 100%

Yes None
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
% of respondents
% of respondents
Interpretation: Graph presented above exhibits that 50% respondents support individuals
from their income, whereas remaining not. It shows that ratio of the outcome generated
pertaining to such question is equal.
9. Income level ensures happiness and comfortable
Particulars Views of respondents % of respondents
Agree 14 70%
Somewhat agree 4 20%
Somewhat disagree 2 10%
Disagree - -
Total 20 100%

Agree Somewhat
agree Somewhat
disagree
0%
10%
20%
30%
40%
50%
60%
70%
% of respondents
% of respondents
Interpretation:In survey, 70% agreed with the aspect that income level closely influences
their comfort and happiness. From assessment, it has identified that disposable income of
individuals increase when they earn high. Hence, high income level enables people to meet their
desires on time and live luxurious life (Latif, 2016). Considering the same, 20% respondents also
agreed with the asked statement to some extent. On the contrary to this, 10%people disagreed
with the statementpresented above. Moreover, such individuals believe that needs and wants of
individuals are never satisfied. Further, along with the income there are several other factors
which in turn impacts happiness such as stress, lack of family support etc (Ahuvia, 2018).
10. Individuals are very happy with their income
Particulars Views of respondents % of respondents
Very happy 8 40%
Somewhat happy 8 40%
Neither happy nor unhappy 2 10%
Somewhat unhappy 2 10%
Very unhappy - -
Total 20 100%

Very happy Somewhat
happy Neither
happy nor
unhappy
Somewhat
unhappy
0%
5%
10%
15%
20%
25%
30%
35%
40%
% of respondents
% of respondents
Interpretation: By doing evaluation, it has assessedthat80%, 40% under each category,
selected the option of very and somewhat happy.Apart from this, 10% respondents depicted that
they neither happy nor unhappy. Further, remaining 10% individuals stated that they were
somewhat unhappy from the earnings generated weekly.
Descriptive statistics or data analysis
Particulars
Ag
e
Gen
der
Mar
ital
stat
us
Earni
ngs
Ho
urs
spen
ding
level
on
utiliti
es
Savi
ngs
fro
m
inco
me
suppo
rting
indivi
duals
from
incom
e
Inco
me
suppo
rts
happi
ness
and
comfo
rt
level
of
happi
ness
Mean 2 1.45 1.7 2.5 1.8 1.8 2.2 1.5 1.4 1.9
Standard Error
0.2
1 0.11 0.15 0.11
0.0
9 0.16 0.24 0.11 0.15 0.22
Median 2 1 2 2.5 2 2 2 1.5 1 2
Mode 3 1 2 3 2 2 2 1 1 2
Standard
Deviation
0.9
2 0.51 0.66 0.51
0.4
1 0.70 1.06 0.51 0.68 0.97
Sample
Variance
0.8
4 0.26 0.43 0.26
0.1
7 0.48 1.12 0.26 0.46 0.94
Kurtosis -
1.9
-
2.18
-
0.55
-2.24 0.7
0
-0.73 -
0.89
-2.24 1.17 0.34

1
Skewness
0.0
0 0.22 0.40 0.00
-
1.6
2 0.29 0.45 0.00 1.51 0.99
Range 2 1 2 1 1 2 3 1 2 3
Minimum 1 1 1 2 1 1 1 1 1 1
Maximum 3 2 3 3 2 3 4 2 3 4
Sum 40 29 34 50 36 36 44 30 28 38
Count 20 20 20 20 20 20 20 20 20 20
Confidence
Level (95.0%)
0.4
3 0.24 0.31 0.24
0.1
9 0.33 0.49 0.24 0.32 0.45
Interpretation: Descriptive statistical evaluation presents thatmean age of the selected
respondents accounted for 31-40 years. Further, large or average respondents considered for the
investigation was male. Majority of the respondents selected were married and earning 500-1000
AUD on weekly basis.The above mentioned evaluation presents that mean weekly working
hours of individuals implied for 20-40. Statistical assessment of data set presents thataveragely
10-25% income is spent by individuals on utilities and other necessities. Results of descriptive
evaluation present thataverage 10-25% part of income is saved by the individualsfromincome.
Survey results present thataverage number of respondents laid focus on supporting individuals
from their income. From analysis, it has also found that respondents agreed that income is one of
the main factors which make or keep them happy and comfortable. Mean value presents that
respondents were somewhat happy from the income earned by them.
Simple linear regression
Dependent variable: Spending on utilities and necessities
Independent variable: Income or weekly earnings
H0 (Null hypothesis):There is no significant difference takes place in the mean value of earnings
and spending level on utilities & necessities
H1 (Alternative hypothesis): There is a significant difference takes place in the mean value of
earnings and spending level on utilities & necessities.

In order to prove such hypothesis, regression tool was applied which in turn assists in
testing the level of association or relationship takes place between the concerned variables
(Verma and et.al., 2015).
Descriptive Statistics
Mean Std. Deviation N
spendingonutilities 1.8000 .69585 20
Earnings 2.50 .513 20
Correlations
spendingonutilit
ies
Earnings
Pearson Correlation
spendingonutilities 1.000 .295
Earnings .295 1.000
Sig. (1-tailed)
spendingonutilities . .103
Earnings .103 .
N
spendingonutilities 20 20
Earnings 20 20
Variables Entered/Removeda

Model Variables
Entered
Variables
Removed
Method
1 Earningsb . Enter
a. Dependent Variable: spendingonutilities
b. All requested variables entered.
Model Summary
Model R R
Square
Adjusted R
Square
Std. Error
of the
Estimate
Change Statistics
R Square
Change
F
Change
df1 df2 Sig. F
Change
1 .295a .087 .036 .68313 .087 1.714 1 18 .207
a. Predictors: (Constant), Earnings
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression .800 1 .800 1.714 .207b
Residual 8.400 18 .467
Total 9.200 19
a. Dependent Variable: spendingonutilities
b. Predictors: (Constant), Earnings

Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. 95.0% Confidence
Interval for B
B Std. Error Beta Lower
Bound
Upper
Bound
1
(Constant) .800 .779 1.027 .318 -.836 2.436
Earnings .400 .306 .295 1.309 .207 -.242 1.042
a. Dependent Variable: spendingonutilities

Interpretation: Outcome of regression analysis shows thataverage numbers of
respondents were spending 10-25% earnings on their necessities. In addition to this, table of
descriptive statistics show that weeklyaverage income level of the selected respondents liewithin
the range of 500-1000 AUD. Tabular presentation, model summary, exhibits that R and R square
accounted for .29&.87 respectively. It shows that weekly earnings and happiness level of
individuals are correlated to the less extent. Along with this, ANOVA table presents thatp>0.05
which shows that alternative hypothesis is false and other one true. Considering this, it can be
depicted that no statistical significant difference takes place in the mean value of spending and
earnings. Findings of the study can clearly be supported with other articles which show that
income is not only the factor which impactsspending level of individuals. Moreover, there are
several factors which in turn closely influences spending of people such as marital status,
lifestyle, saving policies etc (Angeles, 2010).Hence, all such factors collectively contribute in the

spending level of people to a great extent.Usually, people feel happy whenthey have ability to
spend money on the products or services required. Thus, referring P value it can be depicted that
earnings do not have significant impact on individual’sspending and thereby happiness.
CONCLUSION
By summing up this report, it has been concluded thatlarge number of respondents are
happy from their earning level. Besides this, it can be inferred from regression analysis that mean
values of individuals spending and weekly earnings are moving in similar direction. Further, it
has been articulated thatincome level does not have high level of impact on individual’s
happiness.
RECOMMENDATIONS
Considering the outcome of study, it is recommended to the individuals that they need to
lay more focus on managing balance between personal and professional life which in turn lead
happiness. Along with this, individuals need to focus on supporting others which evolves high
level of satisfaction among them and thereby enhances the level of happiness. In the context of
future investigation, focus also needs to be placed on the factors that impact individual’s
happiness.

REFERENCES
Books and Journals:
Ahuvia, A., 2018. 10 Consumption, Income, and Happiness. The Cambridge Handbook of
Psychology and Economic Behaviour. p.307.
Etikan, I., Musa, S. A. and Alkassim, R. S., 2016. Comparison of convenience sampling and
purposive sampling. American Journal of Theoretical and Applied Statistics. 5(1). pp.1-4.
Latif, E., 2016. Happiness and comparison income: evidence from Canada. Social Indicators
Research. 128(1). pp.161-177.
Verma, N. and et.al., 2015. Prediction of Ground level ozone concentration in ambient air using
Multiple Regression analysis. Journal of Chemical, Biological and Physical Sciences. 5(4).
pp.3685-3696.
Online:
Angeles, L., 2010. Adaptation or Social Comparison? The effects of income on happiness. [pdf].
Available through: <https://www.gla.ac.uk/media/media_110443_en.pdf>.

APPENDIX
Number
of
respond
ents
Ag
e
Gend
er
Mari
tal
statu
s
Earni
ngs
Hou
rs
spendi
ng
level
on
utilitie
s
Savin
gs
from
inco
me
support
ing
individ
uals
from
income
Incom
e
suppor
ts
happin
ess and
comfor
t
level of
happin
ess
1 2 1 2 3 2 2 1 1 1 2
2 2 2 2 2 2 2 2 1 1 1
3 3 2 2 3 2 1 3 2 1 3
4 1 1 2 2 2 2 1 2 2 2
5 3 1 2 3 2 2 2 1 1 2
6 3 2 2 2 2 3 1 1 1 1
7 3 1 2 3 2 3 3 1 1 2
8 2 2 1 3 2 2 2 2 2 4
9 1 2 1 2 2 1 2 2 3 3
10 1 2 1 3 2 2 3 2 2 2
11 3 1 3 3 1 3 2 1 1 4
12 3 2 3 3 2 1 3 2 1 1
13 1 1 1 2 2 2 1 2 1 1
14 1 2 1 2 2 1 4 2 1 1
15 2 2 2 2 2 2 4 1 2 1