PSYC FPX 4700 Assessment 5 Research Report PSYC FPX 4700 Statistics for the Behavioral Sciences
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Research Report
The process of data analysis involves the exploration, transformation, and modeling of data to extract valuable insights, draw informed conclusions, and support decision-making (Kelley, 2020). It is widely used to identify patterns and trends within datasets, providing essential information for business strategies and decision-making processes. However, to obtain meaningful insights, data must undergo cleaning, preparation, and transformation procedures (Cote, 2021). This study examines how student demographics, quiz scores, and final exam scores were recorded by instructors across three different sections of a course.
Data Analysis Plan
Name the variables and the scales of measurement.
Four variables are as follows:
| Variable | Scale of Measurement |
|---|---|
| Quiz 1 | Continuous |
| GPA | Continuous |
| Total | Continuous |
| Final | Continuous |
Variables 1 (Quiz), 3 (Total), and 4 (Final) are continuous variables because they can assume any numerical value within a specified range. For instance, Quiz scores can vary from 0 to the maximum number of questions on the quiz, while Final exam scores can range from 0 to the maximum number of questions on the final exam.
Variable 2 (GPA) is also a continuous variable, although it is often measured on a categorical scale, such as letter grades (e.g., A, B, C, D, F) or a numerical scale (e.g., 0-4.0). This is because GPA is calculated as an average of grades earned across multiple courses, which can take any numerical value within a range.
State your research question, null and alternate hypothesis.
Is there a significant difference in the mean quiz scores across the three sections of the course?
Null Hypothesis: There is no significant difference in the mean quiz scores across the three sections of the course.
Alternative Hypothesis: There is a significant difference in the mean quiz scores across the three sections of the course.
Testing Assumptions
Paste the SPSS output for the given assumption.
| Variable | N | Minimum | Maximum | Mean | Std. Deviation | Skewness | Kurtosis |
|---|---|---|---|---|---|---|---|
| quiz1 | 105 | 0 | 10 | 7.47 | 2.481 | -0.851 | 0.162 |
| gpa | 105 | 1.08 | 4.00 | 2.862 | 0.71266 | -0.220 | -0.688 |
| total | 105 | 54 | 123 | 100.09 | 13.427 | -0.757 | 1.146 |
| final | 105 | 40 | 75 | 61.84 | 7.635 | -0.341 | -0.277 |
Valid N (listwise): 105
Summarize whether or not the assumption is met.
To assess the normality of the data, we examine the skewness and kurtosis values. A perfectly normally distributed variable has a skewness of 0 and a kurtosis of 3. Therefore, data with skewness and kurtosis values close to 0 and 3, respectively, are considered to be normally distributed.
For example, the Quiz variable shows a negative skewness and a kurtosis value of 0.162, indicating a slight leftward skew and a peak that is somewhat higher than that of a perfectly normal distribution. However, the magnitude of these values is relatively small, suggesting that the assumption of normality is not significantly violated.
Results and Interpretation
Paste the SPSS output for main inferential statistic(s) as discussed in the instructions.
| quiz1 | gpa | total | final | |
|---|---|---|---|---|
| quiz1 | 1 | 0.152 | 0.797** | 0.499** |
| gpa | 0.152 | 1 | 0.318** | 0.379** |
| total | 0.797** | 0.318** | 1 | 0.875** |
| final | 0.499** | 0.379** | 0.875** | 1 |
Interpret statistical results as d