You have 2 options for this assignment. Choose 1. Write your blog and then paste the url link to your blog into the assignment on Canvas. Number 1 will be easiest for most of you, but if you already know how to use Excel well or know a little something about statistics, want to learn more about people in our class, or want to challenge yourself to learn about statistical relationships then I would encourage you to do Number 2.
Option 1: View the webinar at: https://www1.gotomeeting.com/register/950432681 about accessing and using data from the US Census Bureau’s American Community Survey and the Kids Count data center. Explore the Kids Count data center at http://datacenter.kidscount.org/. Choose a topic of interest for which you can gather data from this data center.
Write a blog entry of what the data show, using maps, charts, or tables developed from the data center. Explain what you see in the data, hypothesize why this might be, and explain why it all matters. Show, discuss, and compare the data at various (at least 3) geographic levels, such as nation, state, metro area, county, and/or community.
Option 2: Analyze the relationship between two variables in the data from the survey we took in class. An excel spreadsheet with the results of the survey we took in class is here: IntroSoc_survey data2.xlsx. Note if there are blanks, that means the data are missing for that variable. In this file, you'll find data about things from gender, schooling, grades, race/ethnicity, religion, study habits, community, and politics. You'll choose two variables to analyze and see if they are related to one another for people in our class. For instance, do females have a higher GPA than males? What you should do to analyze the data and how you should write it up for your blog post are described here: Analyzing Class Survey Data in Excel.docx
Below are links to tutorials that will help you. The YouTube video is what to follow if you choose to analyze two numerical variables. This link (http://www.kscience.co.uk/as/module5/ttest.htm) is what to follow if you choose to analyze one numerical variable and one that is categories (like gender).