unittype | var |
---|---|
C | 84.826493 |
I | 80.783024 |
IP | 5.729663 |
P | 129.138547 |
R | 59.096925 |
S | 49.280157 |
SC | 49.923399 |
NA | 112.284569 |
Deadline Extensions
You cannot request deadline extensions for the final version of your Final Project. The assignment portal closes at 11:59pm on Sunday. Do not ride the line.
The results of each hypothesis test go directly below the test.
Theory-based Methods
Your decision & conclusion for your hypothesis test go directly below your ANOVA table.
Simulation-based Methods
Your decision & conclusion for your hypothesis test go directly below your permutation distribution and p-value.
Conclusions should be written in terms of the alternative hypothesis
Did you reject the null hypothesis?
Then you have evidence that at least one group has a different mean!
Did you fail to reject the null hypothesis?
Then you have insufficient evidence that at least one group has a different mean!
In this section you discuss the reliability of the p-values you obtained based on the model conditions.
Conditions for Each Test
Each one-way ANOVA test considers different groups. So, your conditions should be evaluated for each test separately.
\(H_0\): the condition is met
\(H_A\): the condition is violated
Just like we never say “I accept the null hypothesis,” we never say a condition is “met.” Instead, we say there is no evidence that the condition is violated.
This section summarizes your understanding of the foundational aspects of experimental design.
Based on the sampling method used, what larger population can you infer the results or your analysis onto?
Based on the design of the study, what type of statements can be made about the relationship between the explanatory and response variables?
Based on the results of your analysis what is your conclusion for the questions of interest? Connect your conclusion(s) to the relationships you saw in the visualizations you made and the results of your hypothesis tests.
Did you distributions look similar but your hypothesis test said at least one group was different?
Think about how sample size effects p-values!
Did you reject the null hypothesis for your one-way ANOVA?
Look back at your visualizations – which group(s) look the most different?
Did you fail to reject the null hypothesis for your one-way ANOVA?
Look back at your visualizations – do all of the groups look relatively similar?
Un-transformed Variances
unittype | var |
---|---|
C | 84.826493 |
I | 80.783024 |
IP | 5.729663 |
P | 129.138547 |
R | 59.096925 |
S | 49.280157 |
SC | 49.923399 |
NA | 112.284569 |
Log Transformed Variances
unittype | var |
---|---|
C | 1.6978424 |
I | 0.8788463 |
IP | 0.8990321 |
P | 1.5659500 |
R | 1.3621461 |
S | 2.1770549 |
SC | 1.6514917 |
NA | 0.7591942 |
You will give a 3-minute presentation on one aspect of your final project you found the most interesting. Notice, you need to pick one aspect, since your presentation is so short.
Here are some examples of what you could choose:
For your presentation you are allowed to make two slides:
Your slides must be submitted as a PDF.
Deadline for slides
Slides are due by 5pm the night before your final exam timeslot. If you do not submit slides by the deadline, you will not be allowed to present.
Reproducibility is a foundational aspect to scientific research.
Data visualizations tell you a story, where statistical tests only tell you a summary.
Multiple regression and ANOVA are powerful tools to explore multivariate relationships.
A well thought out study is more powerful than any statistical analysis.
The field of Statistics was developed to evaluate evidence obtained from data. Over the last century, the use of statistics has become embedded as a component of the scientific process for many disciplines.
“Significance, the new s-word, is overused and underdefined in the realm of connecting statistical results to the underlying science.” (Higgs, 2013)
“I advocate a simple solution: Replace the s-word with words describing what you actually mean by it.”
Remember to give yourself praise!