Jeffreys’s Amazing Software Program ($0.00)
- JASP v19.03 available for free download
Information and data for Week 5 Analytical Assignment 1 are attached below:
Week 5 Analytical Assignment – Texas STAAR Exam Data.docx Download Week 5 Analytical Assignment – Texas STAAR Exam Data.docx
Texas STAAR Filter ANOVA Week 5 Data.csvDownload Texas STAAR Filter ANOVA Week 5 Data.csv
Load the file into JASP, quickly examine the data to ensure data and measurements appear correct and proceed to the JASP analysis environment. Note that this dataset has already been cleaned and you may assume that all significant outliers, data entry errors, and missing values have been purged from the dataset. Select the appropriate analytic techniques in the JASP statistical software to complete the following three steps.
Step 1: Descriptive Statistics
First, create a descriptive statistics module and rename the module “Frequencies – Your Name”. Create frequency tables for all nominal measures in the dataset (except for ID). List only valid, missing, and the frequencies tables. Uncheck all other default statistics for quantitative measures. Next, create a new descriptive statistics module for the three quantitative dependent variables and name it “Descriptive Statistics – Your Name.” Split the data using the Test Prep Variable. Include valid, missing, mean, median, standard deviation, min, max, skew, kurtosis, standard error, the95% confidence interval, and the Shapiro-Wilk measure. If you correctly split the data, you should not the data are normally distributed. Also, include distribution plots and boxplots with your choice color palate.
Step 2: Analyze Math Scores
Next, you will use statistical analysis to determine whether the parent’s education level significantly influences a child’s test scores in math. Open the correct module and name it ANOVA Parent-Math. Choose the appropriate analytical technique to test the following hypothesis:
Ho: μ1=μ2=μ3=μ4
Ha: μ1≠μ2≠μ3≠μ4
where populations 1-4 represent math exam scores for kids with parent’s having education levels of High School, Some College, Associates, and Bachelors, respectively.
Perform all necessary omnibus tests to ensure that the assumptions for the analysis have been met. Include the Q-Q plot as a test for normality, but you may assume that normality has been met for all three dependent variables. We will not be performing nonparametric analyses in this assignment. Ensure that homogeneity of variances has not been violated. If Levene’s test is significant (p < .05), then use the Welch correction. Use the default Type III sum of squares model if homogeneity of variances can be assumed. Include the descriptive statistics table for this analysis and use partial eta square to estimate the effect size of the model. Perform post-hoc analysis using Tukey’s test for pairwise comparisons if appropriate. For visual presentation, also include descriptive plots with 95% error bars as well as raincloud plots displayed horizontally.
Use the results from ANOVA Parent-Math to answer the following questions:
Q1p1– What is the test statistic (F-value) for the analysis?
Q1p2– What is the degrees of freedom for the treatment?
Q1p3– What is the mean squared error term (MSE) for the analysis?
Q1p4- What is the calculated effect size using partial eta-squared?
Q1p5- Based these results (alpha=.05), do parent’s education level significantly affect math scores? (yes/no)
Question 2: Analyze Reading Scores
Next, you will use statistical analysis to determine whether the parent’s education level significantly influences a child’s test scores in reading. Open the correct module and name it ANOVA Parent-Reading. Choose the appropriate analytical technique to test the following hypothesis:
Ho: μ1=μ2=μ3=μ4
Ha: μ1≠μ2≠μ3≠μ4
where populations 1-4 represent reading exam scores for kids with parent’s having education levels of High School, Some College, Associates, and Bachelors, respectively.
Perform all necessary omnibus tests to ensure that the assumptions for the analysis have been met. Include the Q-Q plot as a test for normality, but you may assume that normality has been met for all three dependent variables. We will not be performing nonparametric analyses in this assignment. Ensure that homogeneity of variances has not been violated. If Levene’s test is significant (p < .05), then use the Welch correction. Use the default Type III sum of squares model if homogeneity of variances can be assumed. Use partial eta square to estimate the effect size of the model. Perform post-hoc analysis using Tukey’s test for pairwise comparisons if appropriate. For visual presentation, also include descriptive plots with 95% error bars as well as raincloud plots displayed horizontally.
Use the results from ANOVA Parent-Writing to answer the following questions:
Q2p1– What is the test statistic (F-value) for the analysis?
Q2p2– What is the degrees of freedom for the treatment?
Q2p3– What is the p-value of Levene’s test for the analysis?
Q2p4- What is the calculated effect size using partial eta-squared?
Q2p5- Based these results (alpha=.05), do parent’s education level significantly affect reading scores? (yes/no)
Question 3: Analyze Writing Scores
Next, you will use statistical analysis to determine whether the parent’s education level significantly influences a child’s test scores in writing. Open the correct module and name it ANOVA Parent-Writing. Choose the appropriate analytical technique to test the following hypothesis:
Ho: μ1=μ2=μ3=μ4
Ha: μ1≠μ2≠μ3≠μ4
where populations 1-4 represent reading exam scores for kids with parent’s having education levels of High School, Some College, Associates, and Bachelors, respectively.
Perform all necessary omnibus tests to ensure that the assumptions for the analysis have been met. Include the Q-Q plot as a test for normality, but you may assume that normality has been met for all three dependent variables. We will not be performing nonparametric analyses in this assignment. Ensure that homogeneity of variances has not been violated. If Levene’s test is significant (p < .05), then use the Welch correction. Use the default Type III sum of squares model if homogeneity of variances can be assumed. Use partial eta square to estimate the effect size of the model. Perform post-hoc analysis using Tukey’s test for pairwise comparisons if appropriate. For visual presentation, also include descriptive plots with 95% error bars as well as raincloud plots displayed horizontally.
Use the results from ANOVA Parent-Writing to answer the following questions:
Q3p1– What is the test statistic (F-value) for the analysis?
Q3p2– What is the degrees of freedom for the treatment?
Q3p3– What is the p-value of Levene’s test for the analysis?
Q3p4- What is the calculated effect size using partial eta-squared?
Q3p5- Based these results (alpha=.05) do parent’s education level significantly affect reading scores? (yes/no)
Export the results of the entire project to pdf and upload in Question 4. Do not close or delete the previous modules as you will only upload ONE results file for this assignment.
Question 4 25 pts
Export your results for all three questions to pdf and upload the entire file here. You will want to save the JASP file in case you need ask questions later, but you should only upload the pdf in this slot.
