SOCI 220 Lecture Notes - Lecture 11: Statistical Significance, Pearson Product-Moment Correlation Coefficient, Statistical Inference

• School: Texas A&M University
• Department: Sociology
• Course: SOCI 220
• Professor: Judith Linneman

Document Summary

What is the difference: data processing: Formatting electronic data for easy use and interpretation: data analysis: Looking at what was found and figuring out what it means. Data definition: make the data usable, that it makes sense: variable names. Longer names will mess up format and it will be harder to interpret. Use something that makes sense and describes actual variable: variable labels. Disadvantage: unfortunate page breaks, format will be off. ** would be smart to avoid these: value labels. 8 characters or less any longer and the format will be messed up: missing values. If (cid:395)uestio(cid:374) o(cid:374) su(cid:396)(cid:448)e(cid:455) is(cid:374)"t a(cid:374)s(cid:449)e(cid:396)ed, lea(cid:448)e (cid:272)ell (cid:271)la(cid:374)k/e(cid:373)pt(cid:455) Spss program will enter a period to indicate the missing value this is okay: recode variables. Combine original answer categories to come up with simpler version: create variables. Brand new variable by manipulating other variables. Data analysis software treats blanks as missing. Change invalid responses to blanks or designate them as missing values.