Happy Monday team, 

You are most welcome!! I'm sorry to hear your project is wrapping up but I had a wonderful time trying to help you all! I hope you enjoyed growing some crops and will consider growing more plants as a career or as a hobby in the future! It is very fun and rewarding and teaches you a lot about nature and enjoying the outdoors. 
Best wishes in your education and future endeavors,

John

Hey Prince Team,

Hey team,

Sorry for being away this week, I was at a statistics workshop (so fun!). Awesome work, glad to hear you are seeing improvements in plant growth--that is so exciting!
Great work on making observations. Recording any thing that stands out as different (or expected!) is critical for running a good experiment. Small things can become much bigger given time, and you want to have a record to track the progress and figure out what may have caused a given phenomenon. 

Let's talk about the experiment a bit! For any experiment you want to write a clear hypothesis that you can test with the data/results you get. An example in writing is "Plants treated with/placed in ______ will show a significant increase in __(measurements you are taking)__ compared to the control treatment _____. Then, when we get to data analysis, we test the null hypothesis (the opposite of the hypothesis, essentially expecting no change in this case). If the two groups of data are far enough apart, we can report the numerical averages for all the treatments, "reject the null hypothesis," and because of that say our results support the hypothesis. And even if they are not significantly different that is also an informative outcome and we can report the averages as well and discuss why we think we got the outcome we did. Talk together about what you expect to happen, then take a try at writing a hypothesis and what you are seeing so far in your results! Looking forward to hearing back from you,

John

Hey team,

Sorry for being away this week, I was at a statistics workshop (so fun!). Awesome work, glad you hear you have multiple types of measurements and regular times to record them. 
Great work on recording the two soil types and their differences! I admit I'm a little confused on what the percents are. Soils typically have NPK percents (for nitrogen, phosphorous, potassium) and I cannot find "MPKA" on websites anywhere associated with potting soils. 
There are a number of possible causes making some plants larger and healthier than others, but I would venture to guess most of the problems come from transplanting shock. Corn in my hands never handles transplanting well. It likely disrupts the roots' ability to take up water consistently and they can get drought-stressed if not kept constantly well watered each day until the roots get established in the new soil. I lost plenty of plants after transplanting them outdoors! They also are looking a bit yellow-ish green, indicating a nutrient deficiency (a few grams of miracle-gro mixed into the watering can would help that!).

Let's talk about the experiment a bit! For any experiment you want to write a clear hypothesis that you can test with the data/results you get. An example in writing is "Plants treated with/grown in _(soil type)__ will show a significant increase in __(measurements you are taking)__ compared to the control (or the other soil type). Then, when we get to data analysis, we test the null hypothesis (the opposite of the hypothesis, essentially expecting no change in this case). If the two groups of data are far enough apart, we can "reject the null hypothesis" and say our results support the hypothesis. Talk together about what you expect to happen, then take a try at writing a hypothesis! Looking forward to hearing back from you,

John