Entry tags:
nng?
Somehow I lost the last five hours in a haze of icons. And most of last night in a haze of downloading like 8 albums' worth of Kpop. It's all artists I already really liked: Lena Park, Chae Yeon, Bada, and BoA, but I'm most excited about Lena Park ("The Korean Utada Hikaru").
aeslis, one of my very most beloved music pimps, sent me three tracks last fall, but she didn't have any more. Last night I found eleventy billion tons of Kpop and took the opportunity to download all but one of her albums.
Not that there's any danger of my not passing statistics or anything, but I had a kind of hilarious brain malfunction at the computer exam today where I forgot completely about the existence of the crosstabs function in SPSS because the question didn't actually have anything to do with χ2.
So I had two Likert-scale variables for which level of government people think should be responsible for foreign aid and immigration decisions respectively and a third variable for gender, and was supposed to calculate separately what percentage of women and what percentage of men favoured decision-making at the national level. All I had to do was transform the first two variables from 5 to two categories, national and not-national, and then make two crosstabs tables with gender. But since I forgot about the existence of the percentage functionality in crosstabs I instead went through this reluctant, hour-long song and dance and constructed four new variables: one for men's preferences with the female cases excluded and one of the reverse for each type of decision. I had started trying to combine them when I remembered about crosstabs.
...Yeah, I blame all of that on my lack of breakfast. Let this be a lesson to me.
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Not that there's any danger of my not passing statistics or anything, but I had a kind of hilarious brain malfunction at the computer exam today where I forgot completely about the existence of the crosstabs function in SPSS because the question didn't actually have anything to do with χ2.
So I had two Likert-scale variables for which level of government people think should be responsible for foreign aid and immigration decisions respectively and a third variable for gender, and was supposed to calculate separately what percentage of women and what percentage of men favoured decision-making at the national level. All I had to do was transform the first two variables from 5 to two categories, national and not-national, and then make two crosstabs tables with gender. But since I forgot about the existence of the percentage functionality in crosstabs I instead went through this reluctant, hour-long song and dance and constructed four new variables: one for men's preferences with the female cases excluded and one of the reverse for each type of decision. I had started trying to combine them when I remembered about crosstabs.
...Yeah, I blame all of that on my lack of breakfast. Let this be a lesson to me.