Grimz101
King
.,.,.,.
Relationship Advice
- Thread starter Grimz101
- Start date
ShannonCT
Deity
Carve her name into your forehead. Self-mutilation is so in right now.
Grimz101
King
Chazumi
Trained& Motivated Killer
- Joined
- Jan 24, 2006
- Messages
- 1,254
Hormonal thread writeen by a hormonal teenager trust me. She likes the bad-boy and obviously someone who posts on this thread is not a bad-boy so you are sunk my friend. Give up, or start robbing banks. Good luck with the later. Sorry for the grim advice 
Grimz101
King
Hormonal thread writeen by a hormonal teenager trust me. She likes the bad-boy and obviously someone who posts on this thread is not a bad-boy so you are sunk my friend. Give up, or start robbing banks. Good luck with the later. Sorry for the grim advice
hormonal, meh maybe..
but do not assume i am not a bad-boy, because i post on this thread, obviously i adopt a different language and personification while i chat on these forums, since first you wouldnt understand my slang, and 2nd im no angel to put it lightly
Then you are not bad enough for her.
ShannonCT
Deity
but do not assume i am not a bad-boy, because i post on this thread, obviously i adopt a different language and personification while i chat on these forums, since first you wouldnt understand my slang, and 2nd im no angel to put it lightly
Anyone posting on CFC on a Friday night is a straight-up dork. Peace, my geeky brother.
Indeed. Being a bad boy isn't everything
ShannonCT
Deity
Is that +5 normal-cool or +5 dork-cool?
Do her in the pooper.
Abaddon
Deity
Give up on her and move on.
There is no point chasing a girl who has already lost her heart to an idiot. She is glutten for punishment and will just keep going back to him.
You will have a better life getting with someone else and just keeping in touch with the girl in case things change considerably.
There is no point chasing a girl who has already lost her heart to an idiot. She is glutten for punishment and will just keep going back to him.
You will have a better life getting with someone else and just keeping in touch with the girl in case things change considerably.
You're unlikely ever to get her. Move on. If you can't move on yourself, then tell her you love her, and she'll put some distance between you, saving you the effort.
If she doesn't, and tries to cheat with you, you have proof that actually she's not someone with whom you ought to be in love.
If she doesn't, and tries to cheat with you, you have proof that actually she's not someone with whom you ought to be in love.
philippe
FYI, I chase trains.
Situation:
The three individuals in this situation all live in south londonand are 17 going on 18.Spoiler :
Help mee
Im 17, charming, Easygoing, sociable, Idealistic, Superflirt(can be a bad thing), and confident..
would say im a player as i have dealt with 5 girls and used a durexx with each so to speak, deal with them at the same time, could be 9 by now but im picky, and i dont like girls im not attracted to obviously.. yes i have been bad, i really had no feelings for these girls, even though yes they have feelings for me..
Now here is the poetic justice part..
There is a girl I meet she is friendly, pretty(understatement) and funny, both get along with each other very well, it seems i have finally fallen for a girl, she is single..
then i find out she was just having problems with her boyfriend, and that she loves him, he is the bad kinda boyfriend though, sure he is a player.. i can tell, they have arguements all the time..
Dont think she realises my feelings, if she did im sure it would become arkward at the moment, and would distance herself since she loves him, so i need general advice on how to get her to realise he is bad, what should i do ect, and advice is appreciated as long as it does not involved standing outside her house and throwing wreastling figures at her window(see the crush thread)
and anything to sway her heart to mee
note: if i was with her i would never cheat im 100% sure of that!
With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population might think. Or, we use inferential statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in this study. Thus, we use inferential statistics to make inferences from our data to more general conditions; we use descriptive statistics simply to describe what's going on in our data.
Here, I concentrate on inferential statistics that are useful in experimental and quasi-experimental research design or in program outcome evaluation. Perhaps one of the simplest inferential test is used when you want to compare the average performance of two groups on a single measure to see if there is a difference. You might want to know whether eighth-grade boys and girls differ in math test scores or whether a program group differs on the outcome measure from a control group. Whenever you wish to compare the average performance between two groups you should consider the t-test for differences between groups.
Most of the major inferential statistics come from a general family of statistical models known as the General Linear Model. This includes the t-test, Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA), regression analysis, and many of the multivariate methods like factor analysis, multidimensional scaling, cluster analysis, discriminant function analysis, and so on. Given the importance of the General Linear Model, it's a good idea for any serious social researcher to become familiar with its workings. The discussion of the General Linear Model here is very elementary and only considers the simplest straight-line model. However, it will get you familiar with the idea of the linear model and help prepare you for the more complex analyses described below.
One of the keys to understanding how groups are compared is embodied in the notion of the "dummy" variable. The name doesn't suggest that we are using variables that aren't very smart or, even worse, that the analyst who uses them is a "dummy"! Perhaps these variables would be better described as "proxy" variables. Essentially a dummy variable is one that uses discrete numbers, usually 0 and 1, to represent different groups in your study. Dummy variables are a simple idea that enable some pretty complicated things to happen. For instance, by including a simple dummy variable in an model, I can model two separate lines (one for each treatment group) with a single equation. To see how this works, check out the discussion on dummy variables.
One of the most important analyses in program outcome evaluations involves comparing the program and non-program group on the outcome variable or variables. How we do this depends on the research design we use. research designs are divided into two major types of designs: experimental and quasi-experimental. Because the analyses differ for each, they are presented separately.
Experimental Analysis. The simple two-group posttest-only randomized experiment is usually analyzed with the simple t-test or one-way ANOVA. The factorial experimental designs are usually analyzed with the Analysis of Variance (ANOVA) Model. Randomized Block Designs use a special form of ANOVA blocking model that uses dummy-coded variables to represent the blocks. The Analysis of Covariance Experimental Design uses, not surprisingly, the Analysis of Covariance statistical model.
Quasi-Experimental Analysis. The quasi-experimental designs differ from the experimental ones in that they don't use random assignment to assign units (e.g., people) to program groups. The lack of random assignment in these designs tends to complicate their analysis considerably. For example, to analyze the Nonequivalent Groups Design (NEGD) we have to adjust the pretest scores for measurement error in what is often called a Reliability-Corrected Analysis of Covariance model. In the Regression-Discontinuity Design, we need to be especially concerned about curvilinearity and model misspecification. Consequently, we tend to use a conservative analysis approach that is based on polynomial regression that starts by overfitting the likely true function and then reducing the model based on the results. The Regression Point Displacement Design has only a single treated unit. Nevertheless, the analysis of the RPD design is based directly on the traditional ANCOVA model.
When you've investigated these various analytic models, you'll see that they all come from the same family -- the General Linear Model. An understanding of that model will go a long way to introducing you to the intricacies of data analysis in applied and social research contexts.
You call that hardcore ??
Then what would you call sewing a ribbon of yourself into her right nipple ?
Ontopic: Grimz101: what do you want from her. Sex or a relationship? If it's just sex, then I wouldn't bother. If it was a serious relationship then you might consider approaching her.
Grimz101
King
You call that hardcore ??
Then what would you call sewing a ribbon of yourself into her right nipple ?
Ontopic: Grimz101: what do you want from her. Sex or a relationship? If it's just sex, then I wouldn't bother. If it was a serious relationship then you might consider approaching her.
relationship thats the point, before i have never actually liked a girl on an emotional way, just wanted sex before.. and i always got it really..
I have made a girl break up with her boyfriend and they were together for two years, and to why im posting the thread at 2am on a friday night its because i couldnt sleep
, and im here on a friday since i have exams all next week, lots of maths and economics, need to revise.I refuse to give up because i have never given up on a girl before, i always get what i want.
Grimz101
King
So your saying i should keep doing maths, especially statistics..
and that i need more data maybe thats not bias from my viewpoint
?
Grimz101
King
When you get stop and searched every other week thats a bad idea
i have no problem with looking cool, dont worry
