Data Analysis and Visualisation

Analysis and Visualisation

INTRODUCTION
Data analysis is a process which is used for inspecting, cleansing as well as modelling the
selected data so that effective outcomes can be generated. Through this, company can make
effective decisions so that they can attain further level of success. Similarly, the present report
also helps to develop an understanding pertaining to data analysis by using different software and
tools. Through this, researcher get an appropriate answer without any loophole. The study is
based upon a dataset of different patients whose age is in between 20 and 100 years in which 50
different White and BAME patients have been selected. Thus, the report will present the
meaning of t-Test and describe how to develop null and alternative hypothesis. Also, at different
significant level, hypothesis can be checked.
Meaning of t-Test
t-Test is that type of inferential statistics which in turn helps to determine the significant
difference between mean of two groups that is related to each other. These groups will somehow
related to each other in certain features so that effective outcome can be generated. Moreover,
the scholar also uses this test in order to determine the average of both groups so that hypothesis
can be tested accordingly (Liu and Wang, 2021). In the case of presented data, it has been
identified that there are two groups whose man is determined through this test. This is also
preferred overs because the mean can only be identified in this test in a comparative manner so
that effective outcome can be determined.

What is hypothesis and how to develop null and alternative hypothesis
A hypothesis is an assumption or an idea which is proposed for the sake of argument so
that it can determine which result is true or false. Also, it can be stated that it is a statement of
prediction which is tested by the researcher by using an appropriate tool (Scanlan and et.al.,
2021). In the research study, it can be stated that hypothesis is a statement which entails the
purpose or research question and this can be attained by applying effective tool. This is mainly
constructed before conducting any statistical test.
Null hypothesis is presented as H0 and determine no relationship between the variable
whereas alternative hypothesis is H1 which reflected a significant relationship between both
variable. Also, as per the defined question, these hypothesis will be proved at different
significant level and if the value is lower than the standard criteria then alternative hypothesis is
accepted and vice versa (Galaj and Xi, 2021). Thus, these statements prove that there is a
relationship between the variables and examine the pattern which is followed by the data set and
accordingly interpreted the values as well.
Presenting a set of testable hypothesis for an experiment
Null hypothesis (H0): There is no significant change identified between the infection rate of
Covid-19 with white people and BAME.
Alternative hypothesis (H1): There is a significant change identified between the infection rate of
Covid-19 with white people and BAME
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1
White patient 36.5800 50 11.97973 1.69419
BAME 60.0400 50 23.39192 3.30812
Paired Samples Correlations

N Correlation Sig.
Pair 1 White patient & BAME 50 -.045 .757
Paired Samples Test
Paired Differences t df Sig. (2-
tailed)
Mean Std.
Deviation
Std. Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Pair
1
White patient
- BAME
-
23.4600026.75529 3.78377 -31.06377 -15.85623 -6.200 49 .000
Interpretation: By applying paired sample t-test, it has been identified that the average of
white people is 36.58, whereas BAME people is 60.04. This in turn reflected that BAME people
have high value and the value of significant different is 0.00 which in turn reflected that there is
a difference between both variables and that is why, null hypothesis is rejected over other. The
same has been also investigated by Breakwell, Fino and Jaspal (2021) that due to change in
working environment, most of the people actually affected due to pandemic. In this, BAME
people are highly affected from the pandemic because the rate of infection of Covid-19 is high in
this area. The major difference identified in this area involves their behaviour which shows the
differences between the people. It is so because BAME people do not get any appropriate
medical facilities and this in turn cause adverse impact over their performance. Thus, it has been
identified that as compared to BAME, White people actually do not affected highly, as they have
enough medical facility which assists to reduce the chances of infection.
Testing the hypothesis at different significance level
At P = 0.10