in class

there is no function as to how I write and what I write, I just assume you all want to read my articles since it is my blog.

I don’t really know what I’m posting online, but for the most part it’s jibberish anyways.

I recognize the fear in posting writing and how fearful you can be misinterpreted, but that is bound to happen regardless of if I post or don’t post. So I minus well maintain autonomy by creating what I want on this platform.

I would rather have my own blog like megan markle where she had her own page, photos and stuff but right now that’s not my priority.

My priorities are:

1. pay rent, food, and exercise when I can
2. finishing my last class, coping with how to maintain balance with work and life
3. find my happy
4. make time for my friends and family

also questions I have from being in class right now:

what is covariance, with covariate and independence and error term what does this all have to do with eachother?

no bias with error term when covarience could be independent from error term

• if this is all gargain then that’s fine* I don’t understand it too.

what is the difference in bias and bias point estimator

heteroskedasticity homoskedasticity

it’s like sexuality and econ double confusing… mannnn

Notes to self: heteroskedasticity

it means that the plot is fanning, and that it’s spreading more becausecause there’s different values of independent variable

homo skedasticity === doesn’t fan out, remains uniform

is the united states homo? like they watn everyone to be the same or does it want to have to embrace uniqueness, pls don’t come after me, I’m just a student with genuine question. I know I’m publically posting this, oh god.

lol anyways back to class, heteroskedasticity is especially ubquitous when money is involved, eg. income by educational level, wealth by income, GDP per US state, etc. Spread of education level is higher when you have more opportunities I suppose.

Some fixes that can be applied to some things…

error term of individual (5th assumption) s

dajfeljfle shit man I didn’t know we were making assumptions to begin with, this is probably confusing as hell for yall becausecause it is for me.

5. the error term is independently and identically distributed.

<this is when I came into consciousness and I’m realizing it’s a list of something in this class, now I have to go back and start from the top, but now i can see the bigger picture I guess. … >

if my firends are a good student, then I am a likely

if my friends are __ then I’m more likely to do __

spacial law is like people in your group will refelct what type of person you are. tell tell sign

6. there’s no perfect multicollinearity among covariates

• covariate that is. amultiple of another.
• I don’t know what I’m doing but typing feels nice and productive.
• he’s talking about some dummy trap where all mutually exclusive and exhaustive (deadly, this means it ends, or it’s really long idk) categories are included as dummy variables
• covariate is a multiple of another
• including income, savings, and expenditure all as covariates.

this is all confusing to me.

Dummy Variable:

we use to model multiple variables:

Male & Female

obs 1,2,3

male, female, nonbinary

respectively

coding these categories, m/f as predictors, holdign them as variables female column and nonbinary column

each observation coat for male, mutually exclusive — only one can exist.

Coated 0, 0, 1

dummy variable including all three of the variables then this is where it’s considered

including all of those catecories

yi = b0+b1male_i+b2female_i+b3nonbinary_i+error_term_i

this results in dummy trial if you know one of them then youre gonna know the other ones.

being perfect perdictors for the other things.

ffkafjeajfjifewfewj

type type type

multicolinearity is still confusing for me. I’m sorry if this wasn’t helpful. this isn’t made to help you, it’s to keep me awake in class and makes me feel good about posting a blog lol.

I try to entertain myself which in turn entertains you.

please don’t sue me, I own nothing.

I know this is all learnng stuff but it’s also so confusing I’m surprised it’s coming out of my keyboard too. This education is powerful. I just am a sponge and I absorb everything. I know that

#6 error term is normal distrubiuted if met then there’s OLS nice property, best linear unbiased estimator(BLUE)

probelmes: having dummy varibale, error temr can be wrong, it’s not a neccessary error or redisdual not normally sdistributed.

I think to make this cohesive I need to have a look at this again, otherwise this is junk for you and me.

if you found this useful, why are you here, what are you llooking for and what’s happening. okay bye class is over …