Statistics: Analysis of Student Performance and Learning Support

This statistics assignment analyzes the factors influencing student performance, focusing on personality traits and learning support. The solution includes defining variables, formulating null and alternative hypotheses (H1 and H2), and performing a statistical analysis using a t-test to compare male and female student performance. It also covers questionnaire design, including question types and scales (Likert and semantic differential scales) to gather data on student attitudes, beliefs, and environmental factors. The interpretation of t-test results and recommendations for motivating students differently based on gender are also provided. The assignment uses nominal, ordinal, interval, and ratio scales for questionnaire design and offers insights into effective teaching strategies.

Running head: STATISTICS 1
Name
Name of professor
Institution Affiliate
Date

STATISTICS 2
Part a
i. Choice of X and Y
X is the student's personality traits while Y is the choice of specific learning support.
All these contribute greatly on the performance of students in every learning institution. The
student’s personality traits are attitudes and behavior which is dependent of the teaching
practices which is mostly proximal to these measures that include the emotional support of
teachers and classroom organization (Blazer & Kraft, 2017). Evidence suggests that teachers
and their background characteristics contribute greatly to the performance of students which
is also attributed to the multidimensional learning of students. However, teachers who are
effective at improving test scores of students are not as well effective at bringing
improvement to their attitudes and behavior hence making learning a dimensional feature.
ii. Null and alternative hypothesis of H1 and H2
The null hypothesis is the one to be tested while alternative hypothesis is any other
hypothesis in a research. Therefore, in our research included hypothesis of H1 and H2. The
null hypothesis of H1 include good performance in class brought by positive attitude and
overwhelming behavior of the student's. However, the attitudes and behavior of students also
gives an alternative hypothesis which was not part of the research of performance in class.
The negative attitudes and bad behavior may also lead to violence between teachers and the
student’s hence poor performance. Similarly, teachers' emotional support and classroom
organization also has its null hypothesis as developing good relationship with the students
which in turn improves the attitude and behavior of the students towards learning hence
good performance in class. Likewise, it has an alternative hypothesis of misleading students
hence resulting to poor performance in class.
iii. Statistical analysis for testing H1 and H2
Null hypothesis = H1

STATISTICS 3
Alternative hypothesis = H2
X is dependent of Y
We thus use statistical hypothesis test since we are testing two variables of X for
student's personality traits and Y for choice of learning support. It enhances expressing of
confidence intervals thus every hypothesis based on significance testing can be obtained by
confidence interval. It specifies a set of statistical mode which is used to choose most
appropriate model in hypothesis analysis.
Part B
i. Questionnaire
Many students have problems in their performance in class work which is contributed
to by several factors. However, a solution to these is possible thus a questionnaire was
prepared to determine the solution of improving student performance.
a) What was your performance in the last test? (To be filled by only top 10 students in
the last test)
b) Who were among the best teachers in the last ranking of the Teachers performance?
c) Which age range of teachers are the best performers in teachers ranking?
d) Which social economic group are the top performing students?
e) What are the characters of these top performing individuals?
f) What are the beliefs of these students towards learning?
g) Are the attitudes of these students affective?
h) How do you relate the environment around you with your performance?
i) How do you relate with your fellow students?
j) Who is your mentor towards your performance in class?
k) How frequently do teachers attend to classes?
l) How is the classroom infrastructure favorable to your learning?

STATISTICS 4
m) Do you have library in the institution?
n) Do you have adequate teachers to take you through all your subjects?
o) Does the library have adequate resources for learning?
II. Likert scale and semantic differential scale
I would prefer to use semantic differential scale rather than likert scale. With semantic
differential scale, it is the people who are filling the questionnaire that decide how much traits
or quality an item has while likert scale, people decide how much they agree or disagree with
a particular statement. Since in our case we are dealing with items that result to improvement
in performance of students, we therefore use semantic differential scale that enables us to
acquire adequate response from those filling the questionnaire on the value of trait or quality
of an item suggested.
III. 5-point, 6-point and 7-point scales
I would prefer using 7-point scale. Being that we need more accurate and effective
response to evaluate the most effective item in the improvement of students' performance, we
would use this scale since it is the best solution to questionnaire with usability evaluation. It
is the most effective likert scale, it is easier to use, and it gives a better reflection of the
respondent's true evaluation.
iv. Nominal, ordinal, interval and ratio scale
The questionnaires for part i) (1) and i) (2) are nominal scale questions since they
contain variables named but not in order while part I) (3) and I) (4) are ordinal scale
questions since they contain named variables in order but not proportional interval between
the variables.
v. Comment on the questionnaire

STATISTICS 5
The questionnaire is clear to any respondent and appropriate for any approach since
the clarification of it is from other sources. Some of the illustrations on the questionnaire are
from articles from other sources. (Lame, 2001).
Part C
I. Interpretation of t-test results
Since ù< x, it is a null hypothesis and a one-tailed test
Male: α =1.595
Female: α=0.988
Male, P=(x-ù) /SE
SE = standard error
P= (4.60-1.595)/0.412
=7.294
P>α
Female, P= (3.60-0.988)/0.254
=10.28>α
Since P-value is greater than α, thus no rejection of
Null hypothesis. Therefore, no significance difference between sample data and given data.
II. Yes, I think Dr Tian should use two different ways to motivate female and male students.
This is due to differences in their hypothesis and the p-values. This means that the factors that
motivate males are different and independent of those that motivate female students. The
probability traits of female students are different to those of male students hence need of
different motivating factors by Dr Tiana.
Variables such as age enables on how to approach the students differently considering
their age difference. Environmental factors enable him to decide on which environment factor

STATISTICS 6
is favorable to all the students. The resources available give analysis on their distribution
among the students to accommodate and satisfy all.

STATISTICS 7
References
D. Lam, in International Encyclopedia of the Social & Behavioral Sciences, 2001.
David Blazer and Matthew A. Kraft (2017). "Teachers and Teaching Effects on students,
Attitudes and Behaviour ", Education evaluation policy analysis.