Biostatistics Report: Statistical Analysis of Age and BMI Differences

This report presents a biostatistical analysis using SPSS, examining age differences between males and females via a two-tailed test and assessing aspects related to Body Mass Index (BMI). The analysis includes descriptive statistics, frequency tables, and independent samples tests to determine the significance of the differences. The study utilizes a two-tailed test to evaluate whether the age and BMI values of the sample are higher or lower than a range of values. The report concludes with a summary of the findings, highlighting the significant differences observed and emphasizing the importance of statistical evaluation in research. The report references relevant literature to support the methodology and findings.

Biostatics SPSS

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
A. Evaluating age difference among males and females by using two tailed test..................1
B. Assuming crucial aspects related with BMI......................................................................3
CONCLUSION................................................................................................................................4
REFERENCES ...............................................................................................................................5

INTRODUCTION
Biostatic is known as one of the crucial applications of statistics which is used at a wide
range of matters in biology. This will assist in analysing research questions in medicine and
public health to determine whether new aspects related with an individual can be beneficial for
people or not. The project provides crucial information about descriptive data regarding available
observation.
A. Evaluating age difference among males and females by using two tailed test
A two tailed test is known as main statistical which is more crucial for distributing two
side and test, whether a sample is having higher or less than a range of values. In case sample
test falls into any of critical areas, the alternative hypothesis will be accepted in accordance with
null hypothesis. In the mentioned case, comparison among male and female age is done to check
any impacts or changes.
Group Statistics
gender N Mean Std. Deviation Std. Error
Mean
age Male 40 50.70 7.783 1.231
Female 30 54.07 6.170 1.126
Independent Samples Test
Levene's Test
for Equality
of Variances t-test for Equality of Means
F Sig. t df
Sig.
(2-
tailed)
Mean
Differen
ce
Std.
Error
Differe
nce
95% Confidence
Interval of the
Difference
Lower Upper
age Equal
varianc
es
assume
1.919 .170 -1.952 68 .055 -3.367 1.724 -6.808 .074
1

d
Equal
varianc
es not
assume
d
-2.018 67
.7
60
.048 -3.367 1.668 -6.696 -.037
Interpretation:
From the above table, it has been seen that there is significant difference present in age of
males and females. Because the outcomes is less than 0.5 and results generated is only 0.048. If
it has been seen in the group statistics, mean value of male and female is not much of difference.
Descriptive data analysis:
Statistics
gender age
N
Valid 70 70
Missing 0 0
Mean 1.43 52.14
Median 1.00 53.00
Mode 1 60
Std. Deviation .498 7.284
Variance .248 53.052
Sum 100 3650
Frequency table:
Gender
Frequency Percent Valid Percent Cumulative
Percent
Valid
Male 40 57.1 57.1 57.1
Female 30 42.9 42.9 100.0
Total 70 100.0 100.0
2

age
Frequency Percent Valid Percent Cumulative
Percent
Valid 35 1 1.4 1.4 1.4
37 1 1.4 1.4 2.9
38 1 1.4 1.4 4.3
39 2 2.9 2.9 7.1
40 1 1.4 1.4 8.6
41 2 2.9 2.9 11.4
43 1 1.4 1.4 12.9
44 3 4.3 4.3 17.1
45 3 4.3 4.3 21.4
46 1 1.4 1.4 22.9
47 3 4.3 4.3 27.1
48 3 4.3 4.3 31.4
49 3 4.3 4.3 35.7
51 5 7.1 7.1 42.9
52 3 4.3 4.3 47.1
53 3 4.3 4.3 51.4
54 4 5.7 5.7 57.1
55 4 5.7 5.7 62.9
56 2 2.9 2.9 65.7
57 4 5.7 5.7 71.4
58 3 4.3 4.3 75.7
59 3 4.3 4.3 80.0
60 6 8.6 8.6 88.6
61 5 7.1 7.1 95.7
63 2 2.9 2.9 98.6
64 1 1.4 1.4 100.0
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Total 70 100.0 100.0
B. Assuming crucial aspects related with BMI
It is known as an appropriate measure of whether an individual is over or underweight. It is
derived from total weight and height of an individual. The BMI used to divide by making square
of body height. According to the mentioned case about BMI of 32 and higher. On the basis of
various difference those are arises among male and female on total body mass index of 32 is
being analyse by using two tailed test. The research hypothesis is designed accordingly:
a) Null hypothesis (H0): In the first case, total value of BMI 32 is lower than 32.
b) Alternative hypothesis (H1): In the next case, it is 32 or more than 32. For the further
calculation, their outcome is mentioned underneath:
One-Sample Statistics
N Mean Std. Deviation Std. Error
Mean
BMI32 70 1.10 .302 .036
One-Sample Test
Test Value = 32
t df Sig. (2-tailed) Mean
Difference
95% Confidence Interval of
the Difference
Lower Upper
BMI3
2 -855.582 69 .000 -30.900 -30.97 -30.83
Interpretation: According to the above mentioned calculation, it has been seen that there
is significant difference of .000 among BMI 32 of both males and females. There is significant
difference exist by using two tailed test. In this context, alternative hypnosis is approving in this
relationship.
CONCLUSION
From the above project, it has been concluded that there are various research aspects that
are needed to be analyse by using distinctive evaluation of variables. Further, this project would
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assist in better understanding of research sample test and their interpretation to examine curial
outcomes.
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