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- Referencing Styles : APA
- Course Code: MESA746902
- Course Title: Intermediate Statistics
- University: Carnegie Mellon University
- Country: US
Each student will write a one-two page proposal (and submit to Canvas) that will identify the following:
- Data Set– indicate which of the three provided data sets you will be analyzing or share details of another data set to which you have access that you would like to explore
- Dependent Variable– you need to identify ONE continuous (i.e., ratio or interval level) dependent variable. The variable may be one that exists on the data set or you can create a new variable by combining several existing variables. Consider what you are most interested in explaining; e.g., why do some students score higher than others on a test? Why do individuals vary in how much time they spend doing certain activities? Which youth engage in more risky behaviors than others? Why are some people more motivated than others?
- Independent Variables– you need to identify at least one BUT NO MORE THAN THREE independent variables. The independent variable(s) should be a demographic variable(s) (e.g., age, gender, ethnicity, etc.). Specify the level of measurement of each independent variable. For example, do you want to look at age as a continuous variable or do you want to analyze it as a categorical variable (e.g., students aged 14 to 16 vs students aged 17 to 19)? Choose variables that you expect will predict some of the variability in your dependent variable. For example, do test score differ by gender? Does the amount of risky behavior engaged in vary by age?
- Sample– indicate whether you want to conduct your analyses on the full data set or on a subset of the cases. For example, do you want your analyses to focus on only males or only on females? Each student can choose how they want to define the sample for their paper.
- Overall Research Question– Based on the dependent and independent variables you chose, specify your overall research question. For example, to what extent do age, high school grades, and motivation explain the variation in math test scores? Also, please answer why this research question is important to explore!
- Proposed Bivariate statistical tests– Indicate how you will test the relation of each of your independent variables to your dependent variable, e.g., using a t-test, one-way ANOVA, or correlation. State a null hypothesis for each test. Choose the test that is most appropriate based on the level of measurement of each independent variable.
Submit the completed Brief Research Proposal to Canvas on or before April 15th. Feedback will be provided where needed. The paper will not be graded but each student will get full credit for turning it in on time. No credit will be received if it is not turned in. The Brief Research Proposal counts for 5% of the overall course grade.
Final Paper (due May 13th)
Write a paper that includes the following sections plus a title
- Introduction– Write a paragraph that introduces the study. Include a sentence or two on the importance of the overall research question you are addressing and some brief rationale for each of the independent variables you have selected. If you have chosen to focus on a specific sample (e.g., males only; females only), provide some support for this selection. You do not need to support your statement(s) or decisions with data or a review of the literature (but can do a literature review and offer support from there, if you choose to). Just provide a reasoned argument based on your general knowledge.
- Methods– Provide a brief description of the data set you are using for your study. Indicate if you are selecting a sample of cases from the data set and how those cases were selected. Describe the independent and dependent variables you are using in your analysis. Indicate the level of measurement for each variable.
- Create a table of descriptive statistics for the sample and variables you have selected (i.e., your dependent variable and three independent variables) as well as the other demographic variables available. Examples of this type of table will be available on Canvas. Provide some narrative that describes the findings in this table so the reader will have a sense of the characteristics of the sample for the study.
- Describe the bivariate statistical tests you will conduct. State a null hypothesis for each test and indicate the level of probability at which findings will be considered statistically significant.
- Describe the analysis you will conduct. See the description in the Data Analysis section above. Describe how the overall model will be assessed, particularly noting the change in R square statistic. State the null hypotheses associated with each independent variable in the final model and indicate the level of probability at which findings will be considered statistically significant.
- Results– Report the findings from the analyses.
- Create a table(s) to present the findings of your bivariate analyses. Examples of tables are in the articles we have read for class. In the text, state whether you are rejecting or retaining the null hypothesis and why. Be sure to describe and interpret the descriptive statistics associated with the test (e.g., if you ran a t-test make note of the means for the groups).
- Create a table to present the findings from your analyses. An example of this type of table will be provided on Canvas. In the text, describe and interpret the statistics associated with assessing the initial model (i.e., with the one demographic independent variable entered), the final model (i.e., with all independent variables entered) and the difference between the two. Based on the final model, state whether you are rejecting or retaining the null hypothesis associated with each independent variable and interpret each coefficient.
- Conclusions– Briefly summarize the key findings of the analysis and how they contribute to our understanding of the overall research question you posed. What lessons for practice or policy might be extracted from these findings. List some variables that you would include in future studies examining your research question.