Instructions: Correlation Application and Interpretation
Complete an SPSS data analysis report to analyze correlation for assigned variables.Exploring the associations between some variables in the courseroom using correlations might provide some important information about learner success. You’ll need to pay attention to both magnitude, which is the strength of the association, and directionality, which is the direction (positive or negative) of the association. During this assessment, you’ll start learning about how to best approach correlational analyses like these and start getting some answers. You’ll explore the relationships that may or may not exist in your courseroom data.In this assessment, you’ll get a chance to run and interpret your first inferential statistics analysis: correlations. Your readings and the Course Study Guide will help you in your efforts.
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You will complete this assessment using the Data Analysis and Application Template [DOC] (also known as the DAA Template).
Refer to IBM SPSS Step-By-Step Guide: Correlations [PDF] for additional information on using SPSS for this assessment.
Review the Copy/Export Output Instructions [PDF] for help copying SPSS output into your DAA Template.
Use the Data Set Instructions [PDF] for information on the data set.
Refer to the Course Study Guide [PDF] for information on analyses and interpretation.
The grades.sav file is a sample SPSS data set. The data represent a teacher’s recording of student demographics and performance on quizzes and a final exam across three sections of the course. Each section consists of 35 students (N = 105). There are 21 variables in grades.sav.This assessment is on correlations. You will analyze the following variables in the grades.sav data set:
SPSS Variable Definition
Quiz 1 Quiz 1: number of correct answers
GPA Previous grade point average
Total Total number of points earned in class
Final Final exam: number of correct answers
The DAA Template has five sections:
The Data Analysis Plan.
Results and Interpretation.
- Step 1: The Data Analysis Plan
In Step 1:
Name the four variables used in this analysis and whether they are categorical or continuous.
- State a research question, null hypothesis, and alternate hypothesis for one X-Y pair. For example, you could articulate a research question, null hypothesis, and alternate hypothesis for quiz1 (X) and final (Y).
Step 2: Testing Assumptions
Test for one of the assumptions of correlation—normality.
- Create a descriptive statistics table in SPSS to assess normality. This table should include the four variables named above.
Paste the table in the DAA Template.
- Interpret the skewness and kurtosis values and how you determined whether the assumption of normality was met or violated.
Step 3: Results and Interpretation
In Step 3:
Paste the SPSS output of the intercorrelation matrix for all specified variables:
First, report the lowest magnitude correlation in the intercorrelation matrix, including degrees of freedom, correlation coefficient, p value, and effect size. Interpret the effect size. Specify whether or not to reject the null hypothesis for this correlation.
Second, report the highest magnitude correlation in the intercorrelation matrix, including degrees of freedom, correlation coefficient, p value, and effect size. Interpret the effect size. Specify whether or not to reject the null hypothesis for this correlation.
Third, report the correlation between GPA and final, including degrees of freedom, correlation coefficient, p value, and effect size. Interpret the effect size. Analyze the correlation in terms of the null hypothesis.
Interpret statistical results against the null hypothesis, and state whether it is accepted or rejected.
Step 4: Statistical Conclusions
In Step 4:
Provide a brief summary of your analysis and the conclusions drawn.
Analyze the limitations of the statistical test.
Provide any possible alternate explanations for the findings and potential areas for future exploration.
Step 5: Application
In Step 5:
Analyze how you might use correlations in your field of study.
Name an independent variable and dependent variable that would work for such an analysis and why studying it may be important to the field or practice.
The following statistical analysis software is required to complete your assessments in this course:
IBM SPSS Statistics Standard or Premium GradPack, version 24 or higher, for PC or Mac.
You have access to the more robust IBM SPSS Statistics Premium GradPack.Please refer to the Statistical Software page on Campus for general information on SPSS software, including the most recent version made available to Capella learners.Make sure that your SPSS software is downloaded and installed with fully activated licensing on your computer and running properly within your operating system (PC or Mac). If you need help with these steps, refer to the SPSS Installation Helper.