University | Singapore University of Social Science (SUSS) |
Subject | HBC203 Data Analysis for the Social and Behavioral Sciences Assignment |
HBC203 Data Analysis for the Social and Behavioral Sciences Assignment, SUSS, Singapore: In this assignment, you will apply the knowledge and skills that you learned in this subject to a) develop
Question 1
Overview
In this assignment, you will apply the knowledge and skills that you learned in this subject to a) develop research questions, b) analyze an existing data set using jamovi to answer those research questions, and c) interpret the results of your analyses.
To that end, you will submit a 2000-word report. The word count includes tables but excludes the references and appendix sections. Reports within +10% of the word limit are accepted but words in excess of this allowance will not be graded. For example, the marker will read a 2500-word report until 2,200 words and disregard the last 300 words.
Details about this assignment are described in the sections below.
Problem Scenario and Data Set
You are an English teacher in the United States whose principal has tasked you to brainstorm some ideas to raise reading literacy among students. Although you have in mind some potential factors that might influence reading literacy, as someone with a strong interest in statistics and data analysis, you know you should test out your hypotheses on actual data before proposing any interventions to the principal. So, you set out to look for some relevant data. After searching for a while on the internet, you found public-use data files on the National Center for Education Statistics website.
The data set you found (PISA2009_US.csv) comes from the 2009 Program for International Student Assessment (PISA). The PISA is administered internationally every three years to 15- year-olds to measure their reading, mathematics, or science literacy, depending on the year the PISA was administered. In 2009, the students’ reading literacy was the focus of the study. You are excited to find that together with the students’ reading scores, the data set also contains potential explanatory variables.
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