GEOG3006 Quantitative Methods

Table of Contents


Your Week 2 Assignment required you to display data that was based on both a continuous and categorical variable from a particular dataset.

To perform a descriptive analysis, you used the same variables from Week 2 as in Week 2.

This Assignment will require you to calculate a confidence interval using SPSS for one variable from Week 2 or Week 3.

This Assignment is to be prepared for:

Check out the Learning Resources that deal with probability, sampling distributions and confidence intervals.

Open the SPSS software and open either the High School Longitudinal Study or Afrobarometer datasets (whichever you prefer) starting Week 2.

Select a suitable variable from Weeks 2 or 3 and then calculate a confidence interval using SPSS.

After you have completed your confidence interval, read Chapter 5 and 11 to learn how to copy/paste your output into a Word document.


T2: The Scale of Student’s Science Self-Efficacy is the variable selected. This is a continuous variable.

The confidence interval is calculated by using Analyze in SPSS. Compare means and the one-sample t-test. This gives us the output below:

Statistics by One-Sample


What does that mean?



T2 Scale for student’s science self efficacy

One-Sample Testing

Test Value = 0



The Mean Difference

95% Confidence Interval for the Difference



T2 Scale for student’s science self efficacy

The first table shows the total observations as 19554, with mean 0.0359, standard deviation 0.99311, and standard error of 0.00710.

The second table shows the 95% confidence interval for the variable, which is (0.0219, 0.498).

The rows before show whether 0.04 is significantly different than zero. This is again significant at 1% with p-value of 0.00 and t-statistic of a value of 5.

The confidence interval’s lower bound is 0.0219, while the upper limit is 0.0498.

The 95% confidence interval means that we can be 95% certain that the student’s science self-efficacy is somewhere between 0.0219 to 0.0498.

A histogram is the appropriate visual display for the variable. It gives us a better picture of its distribution.

This chart is what you will get:

The histogram allows us to see which values are most frequent (Gun and al., 2010).

The histogram shows that the average value is 0.04, and the standard deviation 0.998. This is in addition to the 17264 total observations.

The most common value is 0.04, which is more than 4000 students.

The data also shows a close match with normal distribution (IIk and al., 2010).

You can use the variable you choose to answer a variety of social change questions.

One such question is: How can a student’s self-efficacy in science determine whether they would consider science as a career choice?

This has further implications as the consensus is that the greater the country’s number of students who choose science, technology engineering, or mathematics, the higher the skilled human capital and growth in the IT sector. This would increase the country’s economic growth and make it more advanced (Dickman and al., 2009).

It can be seen that students who believe in their ability to succeed in science will pursue higher education in science. This is because they have greater confidence in their abilities in science.

We can see that the majority of science students would score on the value of 0.04 for self-efficacy. This is the most likely number to choose science.

We can see that 0.04 falls within the confidence interval (0.0219,0.0498).

According to the STEM consensus, more students choosing science will indicate greater future economic growth. This is because they have a stronger belief in their abilities.

Preparing the workforce of the future (STEM)

Fundamentals of Statistics.

India’s Press

Education, Quality of Labor Force and Growth of Nations.

Graphical Methods to Exploratory Multivariate Longitudinal data Analysis.

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