Week 5: Identify Analysis Tools in Published Research
This week you will locate three quantitative studies addressing a topic in your area of specialization. At minimum, two different statistical tests should be represented. For example, you might search the literature for studies in transformational leadership and you may find two that used regression analysis and a third that used a t-test. For each study: 1. State the null and alternative hypotheses (Hint. The authors will note the alternative hypotheses, but you will have to infer the null as those aren’t typically stated in published research) 2. Identify the statistical test used to determine statistical significance (e.g., t-test, analysis of variance, multiple regression, etc.). 3. Identify the test statistic, note it, and explain what it means (e.g., t=3.47). 4. Identify the significance level used in each study 5. Identify whether or not the authors found support for their hypotheses. Consider sample size and Type I and Type II error. 6. Explain the implications of each finding. Identify whether or not the authors found support for their hypotheses. Consider sample size and Type I and Type II error. Explain the implications of each finding. Length: 4 pages (1,200 words) References: Get custom essay samples and course-specific study resources via course hero homework for you service – Include a minimum of 3 scholarly resources. Your paper should demonstrate thoughtful consideration of the ideas and concepts presented in the course and provide new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current Ace homework tutors – APA standards.
As an AI language model, I don’t have an area of specialization or personal knowledge to conduct this task. However, I can provide a general example to help you understand how to complete this assignment.
Example:
Topic: The effects of sleep deprivation on academic performance in college students
Study 1:
Null hypothesis: There is no significant difference in academic performance between college students who are sleep-deprived and those who are not. Alternative hypothesis: College students who are sleep-deprived have lower academic performance than those who are not.
Statistical test used: Independent t-test
Test statistic: t(98)=3.24. This means that the difference in academic performance between the sleep-deprived and non-sleep-deprived groups is significant (t-value = 3.24) with 98 degrees of freedom.
Significance level: p < 0.05
The authors found support for their hypothesis. The sleep-deprived students had significantly lower academic performance than those who were not sleep-deprived. Type I error and Type II error were not mentioned in the study.
The findings imply that sleep deprivation has a negative impact on academic performance in college students.
Study 2:
Null hypothesis: There is no correlation between the number of hours of sleep and academic performance in college students. Alternative hypothesis: There is a significant positive correlation between the number of hours of sleep and academic performance in college students.
Statistical test used: Pearson correlation coefficient
Test statistic: r(148) = 0.52. This means that there is a moderate positive correlation (r-value = 0.52) between the number of hours of sleep and academic performance in college students, with 148 degrees of freedom.
Significance level: p < 0.01
The authors found support for their hypothesis. There is a positive correlation between the number of hours of sleep and academic performance in college students. Type I error and Type II error were not mentioned in the study.
The findings imply that getting enough sleep can positively impact academic performance in college students.
Study 3:
Null hypothesis: There is no significant difference in academic performance between college students who get different amounts of sleep. Alternative hypothesis: College students who get more sleep have better academic performance than those who get less sleep.
Statistical test used: One-way analysis of variance (ANOVA)
Test statistic: F(2, 96) = 8.05. This means that there is a significant difference in academic performance among the three groups (F-value = 8.05) with 2 and 96 degrees of freedom.
Significance level: p < 0.05
The authors found support for their hypothesis. The group of students who got more sleep had significantly better academic performance than the other two groups. Type I error and Type II error were not mentioned in the study.
The findings imply that getting enough sleep is important for academic performance in college students and that the amount of sleep can make a significant difference.
Overall, these studies show that sleep deprivation has a negative impact on academic performance in college students and that getting enough sleep is important for academic success. Each study used a different statistical test to analyze the data and found support for their hypotheses. However, it is important to consider the sample sizes and potential errors in the studies when interpreting the results.
