14 May PLEASE READ THE BELOW ESSAY AND WRITE A SUBSTANTIVE 300 WORD REPLY Make Sure That You Are Adding New And Relevant Information With Each This Reply.
PLEASE READ THE BELOW ESSAY AND WRITE A SUBSTANTIVE 300 WORD REPLY Make sure that you are adding new and relevant information with each this reply.
D5.1 Interpreting Correlations.
Correlation coefficients are used in statistics to measure how strong a relationship is between two variables. There are several types of correlation coefficient: Pearson’s correlation (also called Pearson’s R) is a correlation coefficient commonly used in linear regression. Based on the correlation table, the Pearson correlation coefficient is .34, and the significance level p=.003. While the Spearman’s rho is .32, which a significance level of p=.006. The nonparametric Spearman correlation is based on ranking the scores rather than using the actual raw scores. In the effort to investigate if there was a statistically significant association between mother’s education and math achievement, a correlation was computed. In the Pearson correlation mother’s education was skewed which violated the assumption of normality. Thus, the Spearman rho statistic is more appropriate for this case. The direction of the correlation was positive, which means that the students who have highly educated mothers tends to have higher math achievement test scores. The effect size is medium for studies in the area. The r2 indicates that approximately 10% of the variance in math achievement test scores can be predicted form mother’s education
D5.2 Interpreting Regressions.
Simple regressing was conducted to investigate how well grades in high school predict math achievement scores. Based on the output, the regression coefficient is 2.142, while the standardize regression coefficient is .504. The results were statistically significant F(1,73)= 24.87, p&λτ;.001. The identified equation to understand this relationship was math achievement =.40 +2.14 x (grades in high school). The adjusted R2 value was .244. This indicates that 25% of the variance in math achievement was explained by grades in high school. This is a large size effect. In out put 9.3, the correlations between grades in high school and match achievement test is .504, with the sig p=.000. The relationship between both are significant and we should reject the null hypothesis. An addition, these variables in both 9.4 and 9.3 are the same.
Research Question 1: Is math achievement dependent on grades in high school?
Research Question 2: Can we predict students match achievement by their high school grades?
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