Overview
You will need this part to insert it into the project: Experiment Data Collection
Topic: Does the amount of exercise affect the amount of sleep someone gets?Make sure the age category is the same, whether its age 20-25 or whatever.
1. Data Collection- describe how you obtained your data. Use kaggle.com
2 Live action pictures of your data collection in progress. (Make sure the pictures are good quality and pasted onto the doc you submit)
3. Put the data into excel from the experiment. Make sure to clearly label all the data. (Will include an example of what it should look like, but you need to add more information)
4. Find the sample mean, standard deviation, N, confidence interval and any other data.
5. Display the data of your choice of graph. Make sure the graphs are well labeled and easy to compare.
Will include an example of what it should look like, but you need to add more information.
Project Presentation
The key to a good statistical presentation is communication and organization. Make sure all components of the presentation are focused on answering the question of interest and that statistical vocabulary is used correctly. The presentation should include the following:Title (in the form of a question). Does the amount of exercise affect the amount of sleep someone gets?
Introduction. In the introduction you should discuss what question you are trying to answer, why you chose this topic, what your hypotheses are, and how you will analyze your data.
- Data Collection. In this section you will describe how you obtained your data. Be specific.
Graphs, Summary Statistics and the Raw Data (if numerical). Make sure the graphs are well labeled and easy to compare. Use the graphs and summary statistics to describe the evidence (if any) for the alternative hypothesis. Use the excel to create graphs.
- Analysis. Do the appropriate significance test AND confidence interval. Discuss how both lead you to the same conclusion. Create a t test or z test.
Conclusion. In this section, you will state your conclusion. You should also discuss any possible errors (e.g., Type I or Type II), limitations to your conclusion, what you could do to improve the study next time, and any other critical reflections.