Difference between Descriptive & Inferential Statistics

CR2030 Project One

Table of Contents
INTRODUCTION...........................................................................................................................3
MAIN BODY..................................................................................................................................3
1. Explain difference between descriptive & inferential statistics along with suitable example
and explain why they constitute descriptive / inferential statistics..............................................3
2. Explain the assumption of sphericity and evaluate their own research scenario for the
assumption, also identify that how these assumption is similar or different from homogeneity
of variance assumption................................................................................................................5
3. Explain the differences between one-way and two-way experimental designs along with
suitable example and also define the two-way design advantages..............................................5
4. Explain the assumptions of parametric and provide a suitable example for this.....................6
5. Conduct a series of test or compare two groups of participants..............................................6
6. Calculation...............................................................................................................................8
7. Appropriate statistical test determines whether male or female participants are more
depressed....................................................................................................................................10
8) Appropriate statistical test to determine whether participants’ socioeconomic status impacts
on their anxiety scores...............................................................................................................12
9) Appropriate statistical test to determine whether participants’ depression and anxiety scores
significantly differ.....................................................................................................................14
10) Design of a question to the study........................................................................................15
CONCLUSION..............................................................................................................................16
REFERENCES..............................................................................................................................17

INTRODUCTION
Statistical analysis is used to arrange data or produce some results which helps for the
further analysis or formulate strategies accordingly (Cooper and Sommer, 2018). There are
various tools and techniques which is used by the individuals to find accurate results and modify
data as per the requirement. This project cover the various types of statistical methodologies and
done different types of test as per the requirement of data.
MAIN BODY
1. Explain difference between descriptive & inferential statistics along with suitable example and
explain why they constitute descriptive / inferential statistics
Descriptive statistics: In this method, data used to summarise on the graph and this
process allow to understand the set of observation. It describes the data such as sample that is
very common and they does not have uncertainly because large population data not used. There
are some common tools which is used in the descriptive statistics such as central tendency,
dispersion, skewness etc.
For example: We collect 30 sample that is test score of students and calculate the
summary statistics to produce graph.

Illustration 1: Descriptive Statistics, 2020.
A s p e r t h e r e s u l t s , m e a n o f t h e t o t a l s c o r e c l a s s i s 7 9 . 1 8 , r a n g e 6 6 . 2 1 t o 9 6 . 5 3 a n d t e s t
a c c e p t i n g m o r e t h a n 7 0 s c o r e ( Example of Descriptive Statistics, 2020). Data represent that 86.7
% of students have acceptable scores because they secure more than 70 marks in the test.
Inferential
statistics:
This data collected from huge sample such as larger population because the aim of
inferential statistics is to draw conclusions from sample of large population. There is various
methodology used to calculate inferential statistics such as hypothesis tests, confidence intervals,
and regression analysis (Galli, 2018).
For example:
Assume that we collecting test score 100 students but they are not from the same class
and they randomly collect sample. After that calculate all the required information such as mean,
median, range etc. In this method, data collected from large sample and provide final conclusion
on the basis of random selection of sample.