Is There a Correlation Between IQ Scores and GPA among Ninth Graders?

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In summary, the results of the correlation between IQ scores and GPA show a moderate, positive relationship between the two variables. The correlation is statistically significant, indicating that there is a significant relationship between IQ scores and GPA. However, the strength of the relationship is moderate, suggesting that other factors also play a role in determining a student's grades. These results support the alternative hypothesis that there is a significant relationship between IQ scores and GPA, but it cannot be concluded that IQ scores are the sole predictor of GPA.
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A school educator is interested in determining the potential relationship between grade point average (GPA) and IQ scores among ninth graders. The educator takes a random sample of 30 ninth graders aged 14 years old and administers the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV includes a Full Scale IQ (FSIQ; however, for this assignment we will just call it IQ)
answer the following questions
- Formulate null and alternative hypotheses. What do you think is the relationship between IQ scores and GPA?
Variables – Describe the scale of measurement (nominal, ordinal, interval, or ratio) for each of the variables.
Correlation – Write an overview of the results of the correlation (at least two paragraphs), including the appropriate and necessary statistical results within sentences and in proper APA formatting. Be sure to provide sufficient explanation for any numbers presented. Consider the following in your overview and conclusions:
Is there a significant correlation between IQ scores and GPA? If so, what does a significant correlation mean?
Using the correlation table and scatterplot, explain whether the relationship is positive, negative, or no correlation.
Describe the strength of the relationship (e.g. very strong, moderate, weak, etc.).
What do the results tell us about your hypotheses?
What conclusions can we draw from these results? What conclusions can we NOT make using these results
 
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?Null Hypothesis (H0): There is no significant relationship between IQ scores and GPA.Alternative Hypothesis (H1): There is a significant relationship between IQ scores and GPA.Variables: The scale of measurement for IQ scores is ratio and the scale of measurement for GPA is interval. Correlation: The results of the correlation between IQ scores and GPA show that there is a moderate, positive correlation between the two variables. The correlation coefficient (r) is 0.412 and this is statistically significant, with a p-value of 0.026. This indicates that there is a statistically significant positive relationship between IQ scores and GPA. The scatterplot also shows a clear positive relationship between IQ scores and GPA. The results support the alternative hypothesis that there is a significant relationship between IQ scores and GPA. The strength of the relationship is moderate, which suggests that while IQ scores have some influence on GPA, other factors such as study habits and motivation may play a larger role in determining a student's grades. The results tell us that there is a statistically significant relationship between IQ scores and GPA, but this relationship is not strong. This suggests that while IQ scores can be used to predict GPA to some degree, other factors such as study habits and motivation should also be taken into consideration. The conclusions that can be drawn from these results are that there is a statistically significant, moderate positive correlation between IQ scores and GPA. However, it is important to note that other factors such as study habits and motivation should also be taken into consideration when predicting a student's GPA. The conclusions that cannot be made using these results are that IQ scores are the sole predictor of GPA. While IQ scores may play a role in predicting GPA, there are other factors that should also be considered.
 

What is correlational analysis?

Correlational analysis is a statistical method used to determine the relationship between two or more variables. It measures the strength and direction of the relationship between variables, but does not establish causation.

What types of data can be analyzed using correlational analysis?

Correlational analysis can be used to analyze both quantitative and qualitative data. However, the data must be continuous, meaning that it can take on any numerical value, and must be normally distributed.

How is correlational analysis different from other statistical methods?

Correlational analysis is different from other statistical methods because it focuses on the relationship between variables rather than on a specific outcome or dependent variable. It also does not assume a cause-and-effect relationship between variables.

What is the difference between positive and negative correlation?

A positive correlation means that as one variable increases, the other variable also increases. In contrast, a negative correlation means that as one variable increases, the other variable decreases.

What are the limitations of correlational analysis?

Correlational analysis cannot establish causation between variables. It also cannot control for all potential confounding variables, and therefore, the relationship between variables may be influenced by other factors. Additionally, correlational analysis is only appropriate for linear relationships between variables, and may not accurately represent non-linear relationships.

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