Education and training in learning institutions quantitative research: Summary of SPSS Output

Education and training in learning institutions quantitative research: Summary of SPSS Output – A school educator is interested in determining the relationships between grade point average (GPA) and IQ scores among ninth graders…

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Education and training in learning institutions quantitative research: Summary of SPSS Output

Paper details

Study Description: A school educator is interested in determining the relationships between grade point average (GPA) and IQ scores among ninth graders. The educator takes a random sample of 40 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) that comprises verbal comprehension, perceptual reasoning, working memory, and processing speed skills. 

Output file:  See  Week_2_SPSS_Output.pdf

Answer the following questions:

a.      Hypothesis – Formulate a hypothesis about the two variables. What do you think is the relationship between IQ scores and GPA?

b.      Variables – Identify the variables and each of their attributes: discrete or continuous, quantitative or categorical, the scale of measurement (nominal, ordinal, interval, or ratio), and independent or dependent.

c.       Descriptive statistics – Write an overview of the descriptive statistics (at least two paragraphs), including the appropriate and necessary statistical results within sentences and in proper APA formatting.  Be sure to provide a sufficient explanation for any numbers presented.  Include the following in your discussion:

  • How do the measures of central tendency and variability provide us with an overview of the characteristics and shape of the distribution of each variable?  What are these statistic
  • Keeping in mind that the WISC-IV has a mean of 100 and a Standard Deviation of 15, what assumptions could you make about the IQ scores and suitability of this IQ test for the group of students sampled?
  • Keeping in mind that the WISC-IV has a mean of 100 and a Standard Deviation of 15, how many students’ IQ scores in this sample are within one standard deviation below the test’s mean? Two standard deviations below the test’s mean? What percentage of students in this sample had an IQ score of less than or equal to 70? An IQ score greater or equal to 100?

d.      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 a 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 our hypotheses?
  • What conclusions can we draw from these results?  What conclusions can we NOT make using these results?
  • What issues regarding the sample used or how the data was collected should be considered in the interpretation of the data?

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e.      Regression – Write an overview of the results of the regression (1 paragraph), including the appropriate and necessary statistical results within sentences and in proper APA formatting.  Be sure to provide a sufficient explanation for any numbers presented.  Consider the following in your overview and conclusions:

  • In the regression, what variable is the dependent variable, and what variable is the independent variable?
  • What do the regression results tell us about IQ scores and GPA?

Solution

Education and training in learning institutions quantitative research: Summary of SPSS Output – : Descriptive Statistics, Correlation, and Regression

Education and training in learning institutions take different forms, not to mention individual capabilities encompassing thinking and reasoning. In contemporary classroom settings, inclusivity ensures that students with certain learning disparities, such as fast learning, get the best of every teaching session. This brings forth a discussion around an individual’s cognitive abilities, especially for learners seeking knowledge to aid the transition from one level to another. A

child’s intellectual ability is measured by using the Wechsler Intelligence Scale for Children- Fourth Edition (WISC-IV). Administering WISC allows observers to establish a participant’s IQ based on verbal comprehension skills, perceptual reasoning, processing speed, and working memory.

Therefore, tutors and instructors ought to conduct follow-ups on student class and field activities to ensure uniformity among peers; this is achieved through therapeutic interventions. This study provides hypotheses, regression results, and descriptive statistics to establish the relationship between IQ and GPA using a representative sample of forty, 14-year-old ninth-graders subjected to the WISC.

Hypothesis

Research studies show that children with higher thinking and reasoning capabilities, ceteris paribus, perform exceptionally well compared to their peers who can either be average or dismal performers academically.
H1: there is a direct and positive relationship between a child’s IQ and GPA

Variables

For this study, GPA represents the dependent variable while the IQ is an independent variable. IQ and GPA are interrelated, given that a child’s IQ determines their GPA. Consequently, these variables depict an infinite number of values hence continuous in nature. The variables are both quantitative as they are expressed in significant numeric measures.

Theoretically, IQ is a quantitative interval variable since higher numerical measures would delineate extremely high smartness levels, while a value of zero would be meaningless. Comparatively, the GPA value is a quantitative ratio value; higher values depict profound academic achievement whilst a value of zero, in this case, is significant as it implies a child gained no points in a specific field.

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Descriptive Statistics

The study acknowledges that the dependent variable (GPA) projects a mean index of 2.73, a median of 2.85, and a modal score of 2.90, while the independent variable (IQ) yields a mean of 85.1; a median score of 82.0; and a modal value of 66.0. Nonetheless, Thorndike and Thorndike-Christ exemplify the dependency of the degree of skewness to the difference in values of the three measures; mean, median, and mode.

Correlation

A study by Jackson (2011) depicts that correlation exemplifies the strength and direction of the relationship between two variables. He further states that direction is determined by the sign preceding the correlation index, which can be either positive or negative. The strength of the relationship is shown by the value of the correlation coefficient, where a value of 1 is positive, while that of -1 is negative.

For the results in this research, there is a strong positive correlation, r, of 0.608 between IQ and GPA. This is conclusive of hypothesis H1, which demonstrates that children with higher thinking and reasoning capabilities perform exceptionally well compared to their peers with lower IQ levels who can either be average or dismal performers academically.

Regression

As we can see from the table, that p-value of IQ is less than the level of significance (0.05), i.e., the variable IQ has a statistically significant effect on GPA. The model explains a 70% variation in the GPA of high school students. This is in sync with the prior expectation because a student’s IQ is an important factor that affects the Grade Point Average.

References

  • Christanti, A., & Tejo P., Y. (2014). Correlation Between Ability on Playing Tetris and GPA. SISFORMA, 1(1), 9. doi: 10.24167/sisforma.v1i1.87
  • Jackson, S. (2009). Know your corporate IQ. Journal Of Business Strategy, 30(5), 60-62. doi: 10.1108/02756660910987635
  • Thorndike, R. M., & Thorndike-Christ, T. M. (2010). Measurement and evaluation in psychology and education. Pearson. One Lake Street, Upper Saddle River, New Jersey 07458.

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