Hello all, I have a lot of questions and any help would be great appreciated. I have a project to create data analysis on data from the internet. I choose YRBS 2021 data. I imported it into SAS, used their formats, and some of my own. I have SAS coding questions and statistical analysis questions. The YRBS data created all the questions into binary variables as well. Which is all i'm using essentially for my data. I'm using these: Mentalhealth Char 8 Poor Mental Health Q1 Char 1 $AGEF. How old are you Q2 Char 1 $GENDERF. What is your sex QN18 Num 8 VIOLENCEF. Ever saw someone get physically attacked, beaten, stabbed, or shot in their neighborhood QN69 Num 8 NOFRUITF. Did not eat fruit QN85 Num 8 MENTALHF. Reported that their mental health was most of the time or always not good QN86 Num 8 SLEEPF. Got 8 or more hours of sleep QNILLICT Num 8 DRUGSF. Ever used select illicit drugs QNOBESE Num 8 OBESEF. Had obesity QNPA0DAY Num 8 NOPAF. Did not participate in at least 60 minutes of physical activity on at least 1 day QNVEG0 Num 8 NOVEGF. Did not eat vegetables RACEETH Char 2 $RACEF. Race/Ethnicity Mentalhealth is the only variable I created myself, it Is created from qn85. It Is my dependent variable, which I want to be binary. Something weird is CDC coded all the binary stuff as numeric values in SAS, is that right? I was under the impression all of these variables are character variables as they are categorical? -In addition, I was doing binary logistic regression, is that right? -Do I need to recode all these variables to be character variables? -When I try to add a format to my new variable mentalhealth it doesn't stick and makes the whole column blank but all my other formats work. -What do I use to detect outliers since it is all qualitative data? -How do I perform summary statistics on all qualitative data? I would appreciate any help. I'm totally lost. We've only gone over quantitative variables in class and i'm not sure how we are expected to know how to do this. I've been research online for a week now. Thanks again!
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