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4 pages/≈1100 words
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APA
Subject:
Education
Type:
Essay
Language:
English (U.S.)
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Topic:
Interpreting the Results of Research
Essay Instructions:
Interpreting the Results of Research
In this assignment, you will interpret the results of your statistical procedures. You will include the findings, as well as a table and a figure, answer the research questions, and include a discussion about post-hoc tests and reliability and validity.
Step 1. Interpret
Interpret the correlational tests and address the following:
Determine the strength of the correlation based on the calculated r- value.
Can you reject or do you fail to reject the null hypothesis? Write out your interpretation of the statistical test, stating the critical value under consideration and whether the null hypothesis could or could not be rejected.
Step 2. Interpret
Interpret the t-tests and address the following:
Inspect the generated table, including the p-value. For either one or two tailed tests (depending on your hypothesis), if p < .05, there is a statistically significant difference between the means, and the null hypothesis can be rejected.
Can you reject or do you fail to reject the null hypothesis? Write out your interpretation of the statistical test, stating the critical value under consideration and whether the null hypothesis could or could not be rejected.
Step 3. Interpret
Interpret the ANOVA tests and address the following:
An ANOVA tests the extent to which the variances of the means in more than two groups are different (μ1 = μ2 = μ3).
The F-ratio is calculated by Excel's output (Between Groups / Within Groups) and is displayed in the "F" column.
You can determine if there are equal variances among the group means by stating whether the generated F > F crit, in which case you can reject the null hypothesis.
Step 4. Include
Include at least one APA-formatted table to show the results of your statistical test.
Include at least one visual, such as a chart or graph, showing a demographic overview of participants (e.g., gender or years of experience bar graphs for each group). Ensure the figure is labeled according to APA format.
Step 5. Answer
Compose a paragraph explaining how your hypotheses were tested and how you reported the results.
Compose a paragraph about the findings: What do they reveal in relation to the research questions? Answer the research questions based on your interpretation of your findings.
Step 6. Consider
In a single paragraph, include a section discussing possible post-hoc tests that address power or effect size.
If you are able, feel free to run the procedures using Excel. If not, you can describe what they are and why they are important.
Step 7. Discuss
In a single paragraph, discuss issues related to reliability and validity of your mini-project, including known limitations, small sample size, the instrument, and the way you conducted your statistical procedures. How would post-hoc tests affect reliability and validity?
You are not expected to be extensive, but you should discuss basic issues surrounding reliability and validity mentioned in this module.
Step 8. Compile
Compile your mini-project again. It is should now include the following sections and subsections:
Introduction (no subheading, 1 pages)
Problem Statement and Problem Background
Purpose Statement
Research Questions
Theoretical Framework (one paragraph)
Research Design and Methodology (2 pages)
Design justification
Independent and dependent variables
Subgroups
Instrumentation
Scope and Delimitations
Assumptions
Limitations
Population and Sample Selection
Data Collection
Data Analysis
Research Findings
Reliability and Validity
Step 9. Submit
Use APA format for your essay, including the title and reference page, and include at least three scholarly citations. Submit your essay.
Essay Sample Content Preview:
Interpretation of Results
Student's Name
Institution
Course # and Name
Professor's Name
Submission Date
Interpretation of Results
The statistical analyses provided significant insights into the hypotheses regarding the impact of flexible start times on employee attendance rates. This study focuses on two comparable groups: employees with flexible start times and those with fixed start times (see Figs. 1 and 2). The hypotheses were tested through a series of statistical analyses: correlation tests indicated no significant relationship, while the t-test revealed substantial differences in attendance rates favoring flexible start times, allowing researchers to reject the null hypothesis. Conversely, the ANOVA test failed to demonstrate significant variance between group means, supporting a conclusion of no difference at the population level. The details of the statistical tests are explained in depth in the subsections below.
Figure 1
Flexible Start Times
Figure 2
Fixed Start Times
Correlation Tests
Table 1
Correlation Results
Flexible_Start_Times
Fixed_Start_Times
Flexible_Start_Times
1
Fixed_Start_Times
0.098834
1
The correlation test produced a Pearson correlation coefficient r= 0.09883 between the flexible start times and fixed start times. This indicated a very weak, positive correlation between flexible and fixed start times (r = 0.0988, N = 30); however, the relationship was insignificant (p = 0.348). The flexible start times were not associated with the fixed start times within the sampled population. The P-value related to this correlation was more significant than 0.05, failing to meet the typical significance threshold. Due to this, The researchers failed to reject the null hypothesis, which posits that there is no correlation between flexible start times and fixed start times. According to Lakens (2022), the critical value for rejecting the null hypothesis in correlation depends on the sample size. In this case, as the correlation coefficient did not approach the threshold of 0.4 (indicating moderate correlation according to standard interpretations), researchers concluded that the evidence does not support a significant relationship.
T-Test
Table 2
t-Test: Two-Sample Assuming Unequal Variances
Flexible_Start_Times
Fixed_Start_Times
Mean
73.11853
68.54605
Variance
81.00116
124.841
Observations
30
30
Hypothesized Mean Difference
0
df
55
t Stat
1.745603
P(T<=t) one-tail
0.043232
t Critical one-tail
1.673034
P(T<=t) two-tail
0.086464
t Critical two-tail
2.004045
The t-test aimed to compare the means of attendance rates for both flexible and fixed start times. The output demonstrated a significant P-value of 0.04323 in a one-tailed test (See Table 2 above), which is below the conventional threshold of 0.05. This indicated a statistically significant difference between the means of the two groups. In performing the t-test while assuming unequal variances, researchers calculated a t-Stat at 1.745603, while the critical value for a one-tailed test was 1.673034 and n=55 degrees of freedom. Given that the t-statistic exceeded the critical value, researche...
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