ACC 290-Analyze and explain the significant findings and directional

ACC 290-Analyze and explain the significant findings and directional

ACC 290-Analyze and explain the significant findings and directional

Subject: Mathematics    / Statistics
Question

Analyze and explain the significant findings and directional relationships (positive versus negative coefficients).

Analyze the hypotheses based on the findings.

How are these findings similar to or different from the simple independent samples nonparametric t-test analysis from Unit 7?

What do the findings suggest about the data and the research questions?

1. Exam Anxiety in Students (Exam Anxiety.sav dataset): To what extent do gender, exam
anxiety, and time spent revising predict exam performance for students?

2. Analyze and explain the significant findings and directional relationships (positive versus
negative coefficients).

3. Analyze the hypotheses based on the findings. 4. How are these findings similar to or different from the simple independent samples
nonparametric t-test analysis from Unit 7?
a. What do the findings suggest about the data and the research questions? In the test of independence, retaining the null hypothesis indicates that the 2 factors are independent of
each other.
1. Gender and exam performance are independent of each other. Distribution of exam performance is
same across all genders.
2. Gender and exam anxiety are independent of each other. Distribution of exam anxiety is same across
all genders.
3. Gender and time spent are independent of each other. Distribution of time spent is same across all
genders.
1.
Null hypothesis:
H0: The distribution of time spend revising is the same across categories of gender.
Alternative hypothesis:
Ha: The distribution of time spend revising is not same across categories of gender. According to the
rejection rule, reject the null hypothesis if, p-value &lt; a
Here, a =0.05 From the given output, the p-value is,
Hence, p-value (= 0.0227)&gt; (=0.05) a
Thus, according to the rejection rule, the null hypothesis is not rejected at 5% level of significance.
Therefore, it can be concluded that the distribution of time spend revising is the same across categories
of gender.
2.
Null hypothesis:
Ha: The distribution of exam performance is not same across categories of gender. According to the
rejection rule, reject the null hypothesis if, p-value&lt; a
Here, a-0.05
From the given output, the p-value is,
p-value= 0.931
Hence, p-value (=0.931)&gt; (0.05) a
Thus, according the rejection rule, the null hypothesis is not rejected at 5% level of significance.
Therefore, it can be concluded that the distribution of exam performance is same across categories of
gender.
3.
Null hypothesis:
Ha: The distribution of exam anxiety is not same across categories of gender. According to the, rejection
rule, reject the null hypothesis if, p-value &lt; a
Here, a=0.05
From the given output, the p-value is,
Hence, p-value (=0.820) &gt; (=0.05) a
Thus, according to the rejection rule, the null hypothesis is not rejected at 5% level of significance.
Therefore, it can be concluded that the distribution of exam anxiety is same across categories of gender.