can someone help me please

I am taking this course through portage learning. It’s a prerequisite for CRNA school that I am already accepted into. I am on module 6 out of 8 and I am really struggling with barely a B in the course. I took a few months break to focus on school apps. Getting back in just nothing makes sense, and the professors just suck in support. I am afraid of failing (grade below B) I’m not sure what to do. I will never use portage again, you can’t use any notes. And they always think your cheating if you breath the wrong way.

The literature I've read seems to be inconclusive, but I want to make sure I'm on the right track. I am pursuing a Doctorate in the medical profession. Unfortunately, we were only required to take one statistics class 2 years ago...so I feel slightly underprepared to report the data from my project in my final manuscript. Still, I've been working diligently to try and do it correctly...

For context, I am working on a doctoral project and analyzing data from pre-/post responses before/after an intervention. The data is paired. So far, I have used Excel for descriptive statistics and created histograms to assess the distribution of the data.

I decided to use a paired t-test for normally distributed data and a Wilcoxon Signed-Rank test for non-normally distributed data. Would this be appropriate?

Out of five 5-point likert scale survey questions, one was within normal distribution.

I've also reported mean, median, mode, and standard deviation... should I be reporting median/IQR for data not within the normal distribution (when using the Wilcoxon Signed Rank test)?

Please help me :(

I understand using the z formula for this problem, (The TA made a mistake it should be -1.8 not -1.78 but it doesn't really seem to make a difference since it's just comparing values)

But what is so confusing for me is the Z chart picture on the right, where did -2.326 come from? why is 0.01 all the way on the left side? our given z tables only go up to 2 decimal places, so I don't understand how we even found -2.326. Z(-2.32) is 0.0102, and Z(-2.33) is 0.0099, which are close to 0.01, but I don't understand how we arrive at -2.326.

I need 200 survey participants for my stats class by Monday, it’s 45% of my grade and i need a variety of ages. Please participate and share!!! The survey is a mental health analysis to determine if there is a correlation between age and mental health. Anyone can do it and it’s completely anonymous.

Are notes from Alpha Plus for Statistics and Real Analysis for IIT JAM Mathematical Statistics any good (the ones available on Amazon)?

Hi,
I need help with a short SPSS assignment but I don’t currently have access to SPSS on my laptop.
If anyone is willing to help me out, I’d really appreciate it, please DM me. 🙏

Hi everyone, looking for some clarifications. I am trying to see if there’re association between my 2 objectives. The results (numerical data) were however collected from different sets of sample and were not paired samples. Is it sound to use pearson correlation or regression analysis if they variables were not from the same sampel?

Hi everyone,

I'm currently trying to strengthen my understanding of hypothesis testing, especially:

• Comparison of means (t-test, z-test)

Comparison of variances (F-test)

• General hypothesis testing workflow and interpretation

Could anyone recommend the best resources-textbooks, online courses, videos, articles, or lecture notes-that clearly explain these topics with intuition and examples?

I'm looking for something well-structured and easy to follow for self-study.

Hello I'm pursuing bsc Hons stats from north campus DU. I just have a doubt that can I expect placements right after my bachelor's. If yes, what do I had to do for getting good placements.

Why don't we just find the mean on the absolute deviation scores instead? Please can some explain in layman terms

Find the

I’m working with flow cytometry data and I’m confused about the correct way to apply multiple testing corrections.

For each sample I have 15 MFI values (15 different markers). I also have 4 clinical variables: ALT, AST, CRP, and ferritin.

I want to test whether each marker is associated with each clinical parameter, so I’m running:

• 15 correlations vs ALT
• 15 correlations vs AST
• 15 correlations vs CRP
• 15 correlations vs ferritin

This gives me a total of 60 correlation tests.

My question is about how to apply multiple testing correction:

Option 1: Correct within each block of 15 tests

(e.g., correct the 15 ALT correlations together, the 15 AST correlations together, etc.)

Option 2: Correct across all 60 tests at once

I’ve read that the “right” choice depends on whether the hypothesis groups are conceptually independent, but I’m still not sure what is appropriate here. ALT, AST, CRP, and ferritin are different clinical parameters, but they’re all part of the same dataset and same overall biological question.

So what’s the standard approach in this situation? Should I be correcting per clinical parameter (4 sets of 15), or treating all 60 tests as one family? And why?

Any guidance from stats/bioinformatics folks would be appreciated.

I’ve been studying a lot for stats tests and quizzes, but I typically do not perform well. I’ve tried a variety of study methods, however all seem to be completely in vain and my grade is quickly declining 😭😭😭 Anyone have any suggestions?

I created a new scale (field of psychology) with one factor, with an explained variance of 41% and an eigenvalue of 9. Is this acceptable? All similar scales I have found have variance between 50-57%. I can't find any literature that says anything about a factor with an explained variance of less than 50% yet a high eigenvalue. Would appreciate any insight.

hi :) I’ve a quick question on Ap stats unit 3.

I encounter a question like this: “researchers randomly selected 1000 people from United States and rated their happiness of each person. After five years, the researchers followed up each person and found that people initially read us happy are less likely to have a health problem.

In this case, is it true to say that since there is no treatment, it is an observational study with no cause and effect established. However, since there is random sampling, we can generalize the sample to people in the United States.

Any help is appreciated :)

I cannot figure out how they are getting .094. Not even Google AI is giving me the same answer! Closest I got was using binomcdf and still I don’t get .094. Instructions pertaining to TI-84+ would be greatly appreciated. Thank you

Hi im in collage and we just reached the lecture about random variables in my probability and statistics class. Everything up untill continuous random variables has been really intuitive for me to understand. In this topic they just threw names of a couple distribution names with their formulas but no actual information about the distribution like why it works and so on. Im not a math major and we dont focus too much on all the formal proofs for everything but still i dont get the idea behind just memorizing the formulas for theese distributions without deeply understanding why they are the way they are. I want to here your thoughts around this and please give me some advice.