Discussion 2

Post ID: 3459138

Purpose

YOU are the creators and scientists for your own collaborative mini studies! In this discussion, you will design a dataset that others can analyze and also practice applying descriptive statistical techniques to a classmate's dataset. Your first thread/post will define the population, sample, and variables, and share a clearly labeled dataset of at least 30 values. Your replies will include summary statistics and a graph from Stapplet.comLinks to an external site., along with a thoughtful comparison.

Video

Tasks

Click Each to expand.

Week 6: Choose a study idea and collect data.

Your sample should be easy to collect and based on things you already have access to. Do not create surveys or depend on other people to respond to you. Instead, collect data from the world around you or from easily accessible sources like sports or world data. At least 30 datapoints are required in total so that others can make meaningful take-aways.

Your study may include:

A single variable (e.g., calories of snacks in your house)
A grouped comparison (e.g., life expectancies of two groups of countries)
A relationship between two variables (e.g., calories vs. fat for 30 food items)
An experimental comparison (clearly identify explanatory/response variables)

If comparing groups, each group must contain at least 10 subjects. If conducting an experiment, make sure to identify the variables clearly and use at least 30 experimental units.

There is nothing to submit this week so that you can spend time collecting data and consult with me to get help in brainstorming an idea. If you are stuck, please reach out to me to get help THIS week! It is essential you do not wait till next week to begin.

Week 7: Create a thread to share your concept and dataset.

In your thread, share your collected dataset using the format below:

Title: Describe your concept in a few words, like "Do organic foods have fewer calories?"
Concept/Inspiration: What is your general idea or question that inspired you to collect this data? What would be an interesting way to study it? This will help guide your classmates when they analyze it.
Population: What population is this sample meant to represent?
Sample and Method: Describe your sample and how it was gathered. AI should not be used to generate data, but could be utilized to search for viable sources and arrange the information. Cite any use of AI here.
Variable(s): List the variables you are measuring and identify whether each is qualitative or quantitative.
Table of Results: Share your collected data in a brief bulleted or tabular format. This should also include a descriptive label (e.g., "Table 1: Sample of 30 Snacks with Calories and Sugar Content").

Week 8: Reply to a classmate with descriptive statistics.

Choose a classmate’s dataset and complete a descriptive analysis using Stapplet.comLinks to an external site. with the following:

A summary table of statistics (mean, median, SD, etc.) for quantitative data OR a contingency table with conditional and marginal rates for qualitative data OR a correlation coefficient and linear regression equation for bivariate quantitative data
A relevant graph (e.g., histogram, boxplot, bar graph, stacked bar graph, or scatterplot)
Labels for variables tables and graphs to clearly explain the table/graph to the reader (e.g. "Table 2: Summary Statistics for Calorie Counts of Food Items by Type" OR "Figure 1: Stacked Bar Graph of Snack Preference by Grade Group")

If someone already completed this task in a thread, reply to a different thread or take a different approach than the first person. Consider using a different type of graph, focusing on a different variable, or changing the method of grouping.

Week 9: Reply to a different classmate with a statistical story

Choose a classmate's dataset and descriptive statistics to create a "story" from the data. In this case, your story is simply an observation from the results that connects statistical results and graphs to illustrate a concept from the homework.

Include the following:

Use summary statistics to make a comparison. For example:
- A higher mean than median, which indicates a right skew.
- A higher rate of agreement in one group over the other, which can be seen as a higher bar in one group over the other.
- A higher median in one group over the other, shown as a boxplot center shifted to the right of the other.
- A higher mean in one group over the other, shown as a histogram with a center concentration shifted to the right.
- A strong positive linear correlation compared to a critical value, shown as a scatterplot that adheres closely to the linear regression line.
Reference the graph and table directly using labels

If someone already completed this task in a thread, reply to a different thread or take a different approach than the first person. Consider focusing on a different feature or result.

Alternatively, if you don't feel confident with this task, or can't find a thread with a clear story to tell, you may repeat last week's task in a different thread.

Grading Criteria

By the end of week 10 you should...

1 point - Create a thread where you introduce a valid, easily replicated study with...
- A clearly defined population and sampling method
- Minimum 30 items (10 per group if grouped)
- Properly identified variables
- Clearly labeled dataset
1 point - Reply to a thread and provide unique descriptive statistics including...
- Correct summary statistics using Stapplet.com with a descriptive label (e.g. "Summary Statistics for")
- Labeled graph (e.g. "Boxplot of")
1 point - Reply to a thread and provide a unique visual analysis of results including...
- At least one specific statistical result (proportion, mean, SD, etc.)
- A visual element or feature of the graph that relates to this result

Note: Instead of the 3rd criterion, you may repeat the 2nd.

Policies

See policies...

This discussion spans the first five weeks and should involve multiple contributions at different times to allow for active discussion. If multiple contributions are made all during the final week of the discussion they will not earn full credit because they do not promote engaging authentic discussion.
Cite data sources with hyperlinked websites.
Use your post to account for specifics of every step of your processes. Take ownership and describe the steps that YOU took.
Do not use generative AI to create sample datasets. If your wording reflects trends of AI generated submissions, I may ask you follow-up questions about your process in order to grant full-credit.
Generative AI may be used to help organize your work, check your thinking, or create meaningful labels for tables and graphs.
If you did not meet the grading requirements for one of your contributions, you can make additional contributions within one week of receiving feedback to earn credit as long as the discussion is still open.