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Data Collection and Analysis Methods in Statistics

This is an applied assignment that requires students to demonstrate their understanding of the principles and techniques taught in the course. The assignment must be submitted in WORD format and all problems must be completed in the prescribed format taught in class. The assignment is worth 30% of the final grade.

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Added on  2023-05-28

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This text discusses data collection and analysis methods in statistics, including the use of online survey method, stratified random sampling, correlation coefficient, and regression analysis. It also covers potential issues in data collection and interpretation of results.

Data Collection and Analysis Methods in Statistics

This is an applied assignment that requires students to demonstrate their understanding of the principles and techniques taught in the course. The assignment must be submitted in WORD format and all problems must be completed in the prescribed format taught in class. The assignment is worth 30% of the final grade.

   Added on 2023-05-28

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STATISTICS
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Data Collection and Analysis Methods in Statistics_1
Question 1
a) An online survey method could be used for data collection considering the fact that the
underlying questions are straight forward and also obtaining the selected random sample
through face to face or other means may be difficult. It would make sense to have a higher
sample fill in the online survey in relation to the preparation hours and the marks scored and
then through technology enabled tools, the requisite sample of 100 can be obtained (Hillier,
2016).
b) The requisite sampling method which would be used to select the sample would be
stratified random sampling. This would be preferred over simple random sampling so as to
ensure that key attributes such as gender, educational background, country of origin and other
aspects could be taken care of and a sample that is representative of the population may be
obtianed. Using a simple random sample instead could lead to the sample being non-
representative as certain attributes may be over-represented while other under-represented
(Flick, 2015).
c) The independent variable is the amount of preparation time that each student spends while
the dependent variable is the number of marks scored in exam. This is because typcially the
marks scored would be dependent on the amount of preparation that is done by the students
and not the other way around. Both the given data are numerical in nature and the
measurement scale would be ratio considering the absolute zero can be defined for both
variables (Eriksson & Kovalainen, 2015).
d) Potential issues that may be faced with regards to collection of data are highlighted below
(Medhi, 2016).
It is possible that students may not have a fair estiamte of the exact preparation time
and also the time frame over which the same has to be stated. For instance, should be
include 24 hours before the exam or a week or a month before the exam.
Also, it might be possible that students may tend to overestiamte and underestiamte
their study hours. For instance, students with good marks are likely to reportn higher
study hours as compared to those who have lower marks in exam.
e) The frequency distribution of preparation time is indicated below.
Data Collection and Analysis Methods in Statistics_2
Data Collection and Analysis Methods in Statistics_3
From the above histogram, it is apparent that the distribution is assymetric and also there is
present of skew on the left considering the fact that tail on the left seems longer than the one
on the right. As a result, it is apparent that the distribution of preparation time is not normally
distributed (Fehr & Grossman, 2013).
The frequency distribution of the marks is indicated below.
Data Collection and Analysis Methods in Statistics_4

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