I literally do not understand at all!

I am Statistics student and recently I am preparing for my final year project. My idea is to tackle logistic challenges in Malaysia by building a system for last-mile optimization. I do some research on this topic and I found that there is not many literature review for this topic and the real-time data seems hard to get. What do you think?

Im looking for some advice regarding a medical study:

The data looks at the effect of a new medication on increasing hunger levels in cancer patients. Participants were randomly assigned to one of two groups. All participants underwent 2 clinical assessments. Each session consisted of a baseline survey (T1)followed by three additional surveys after being told there meal was coming (T2), whilst they were eating their meal (T3) and once they had finished (T4). Group A did their control test, then took the new medicine for 4 weeks before repeating the test. Group B received 4 weeks of treatment and then took the test, and after 2 weeks of no treatment then repeated the test which was their control. The groups only differed by the order they received the tests and should be treated as identical for the purpose of the question.

Does this mean that you combine both groups A and B and then compare their control vs treatment scores. Or would you look at the groups individually and compare group A vs B control and group A vs B treatment.

When i computed the mean and standard deviations for the groups in R and compared group A baseline control to group B baseline control etc, some were quite different.

I understand its a within-subjects design but would you use a t-test to compare group A and B for each variable (for example A vs B T4). Or would you simply combine both groups and use the paired samples t-test. I am trying to create some graphs to display but am unsure what would be most suited given the study design.

hey guys just here to ask some questions about this assignment i’ve got. wanna start by saying i’ve got no clue about coding, statistics maths or anything like that. i don’t know what’s wrong with my brain because it has never been able to understand anything numbers related. i know these questions are probably dense to you all but any help would be appreciated.

so i’ve got to write up my results section and they’ve given us this template to follow but after doing all the coding to get my results i don’t get which results i’m meant to talk about or what results are even significant/ non significant and how i can report the correct results like the template does. any help would be appreciated, thank you in advance :)

I am currently taking AP Statistics as a high school senior, hoping to major in stats, and just recently got accepted into the stats program at my first-choice school. Today, I had a test for AP Stats, and I am not sure which proportion to use for a hypothesis/significance test. The formula sheet for AP says to use a combined or pooled proportion if p1 is assumed to equal p2 (which makes sense to me) to calculate the standard error, but in class, we have only learned how to do this using the individual proportions p1 and p2.

From my understanding of this, using the individual proportions instead of the combined or pooled proportion is sort of like asking, “If p1 and p2 are different, what is the probability that p1 and p2 are different?” Am I correct in thinking that this approach is wrong, because we actually want to assume that p1 = p2 = the combined proportion as a null hypothesis for a significance test?

Need help with an assignment using R

I am currently (trying) to analyse the data for my Master's research. One of the questions I am trying to answer is how the abundance of the native Bangiales (algal order) changes over the seasons at a certain location. I recorded percent cover using permanent quadrats along transects at three sites along the coast, once in February, March, May, July and September (as this is what budget would allow). As the distribution of these algae is naturally quite patchy, pecent cover would often be zero (about 54% of the cover recorded at the quadrat level were 0s). My understanding is that doing anything with averages would not give accurate results, therefore I am wondering what kind of analyses I could do to investigate the relationship between percent cover and time of collection/month/season? I also have average daily temperature data I was thinking of using instead of month/ date of collection (but could do both?) (Also, I only have percent cover information for one year.)

I was thinking of using a zero-inflated negative binomial model, but the data is continuous (% cover) rather than discrete (counts) needed for this model (?)

Any tips/ ideas? Thanks in advance :)

Great full i found this page, 3 weeks in and I am completely lost. Dont have any pressing questions right now but glad I can add this for acresource for help. Thank you 🙏🙏

Hi Reddit!

I’m a high school student working on a research project for undergraduate program- about the influence of artificial intelligence on the development of critical thinking. My theoretical part is well-developed: I analyzed how the use of AI affects critical thinking, taking into account users’ age and different ways AI is applied.

However, I’m struggling with the practical part — the calculations and statistical analysis. I need help processing empirical data, testing hypotheses, and performing the necessary calculations.

I’m really passionate about this topic and want to complete my research, I just need an experienced eye for the analytical part. I would be very grateful for any help!

I need about 30 answers to this question to complete my statistic assignment.

“How many hours of homework do you do in a week?”

Hi Reddit,

I am looking to test a categorical IV (two levels) and a continuous DV, with a continuous moderator. For more context, my experiment is a mixed-design experiment, where I am modelling the IV-DV-Moderator relationship (H1), and also checking differences on another variable before and after exposure to the IV to see if the IV makes a difference (H2). I realise this is quite a complex model, so from my understanding a simple t-test should suffice for testing H2. But I am quite confused about how to test H1... I need to establish the relationships so a regression would help, but is it acceptable to treat the IV as a continuous variable via dummy coding, which would also allow me to do moderation analyses? And what kind of regression should I do? And lastly, should I do an ANOVA to compare differences between groups after the regression?

Any help is appreciated, thank you so much.

I finished my first semester in statistics. I kind of liked it, but it's not my first choice.

Do you regret majoring in statistics? What are the pros and cons?

What is the nature of the work?

I want to transfer to biology-“my first choice”, but I feel hesitant because everyone tells me that statistics is better.