![spider graph stata 13 spider graph stata 13](https://i.stack.imgur.com/mNeQp.jpg)
S456964 REGSAVE: Stata module to save regression results to a Stata-formatted dataset
![spider graph stata 13 spider graph stata 13](https://www.stata.com/new-in-stata/jupyter-notebooks/img/scatter.png)
S456965 WTPCIKR: Stata module to estimate Krinsky and Robb Confidence Intervals for Mean and Median Willingness to Pay S456966 INORM: Stata module to perform multiple imputation using Schafer's method S456967 LABGEN: Stata module to generate or replace variables with definitions in variable labels S456968 NLCHECK: Stata module to check linearity assumption after model estimation S456969 LOGITCPRPLOT: Stata module to graph component-plus-residual plot for logistic regression S456971 APPENDFILE: Stata module to append text files S456972 PSPLINE: Stata module providing a penalized spline scatterplot smoother based on linear mixed model technology S456973 ELECTOOL: Stata module containing toolkit to analyze electoral data S456974 TEXSAVE: Stata module to save a dataset in LaTeX format S456975 HOTVALUE: Stata module to generate scales with missing values conditionally imputed S456976 FMLOGIT: Stata module fitting a fractional multinomial logit model by quasi maximum likelihood S456977 TABLETUTORIAL: Stata module to provide tutorial on automated table generation and reporting with Stata S456978 SAMPICC: Stata module to compute sample size for an intra-class correlation (ICC) S456979 ICCCONF: Stata module to compute a confidence interval for an intraclass correlation (ICC) S456980 BANDPLOT: Stata module to plot summary statistics of responses for bands of predictors S456981 PANELTHIN: Stata module to identify observations for possible thinned panel dataset S456982 BYHIST: Stata module to produce interlaced histograms S456983 BIHIST: Stata module to produce bihistograms S456984 OUTFIXT: Stata module to write fixed-format text file S456985 PWCORR2: Stata module to compute pairwise correlations and return results S456986 RCSGEN: Stata module to generate restricted cubic splines and their derivatives S456987 MOL: Stata module to evaluate literacy level S456988 METADATA: Stata module to enable access to metadata Pop_c float %9.0g popcl Categorized population Marriage long %12.0gc Number of marriages > label data "1980 Census data by state: v2" * Now the three categories are presented as low, medium and high * Then we attach the value label popcl to the variable pop_c > label define popcl 1 "low" 2 "medium" 3 "high" Let’s label them as low, medium and high. * Remember we categorized pop_c into three categories: 1,2 and 3
![spider graph stata 13 spider graph stata 13](https://www.stata.com/new-in-stata/jupyter-notebooks/img/margins.png)
Poplt5 long %12.0gc Pop, label variable pop0_17 "Pop, label variable pop_c "Categorized population" Here we create another new variable called pop_c2 then do the recode in the same manner as we did for pop_c. We can use the -recode- command to recode variables as well.
![spider graph stata 13 spider graph stata 13](https://cdn-ak.f.st-hatena.com/images/fotolife/g/graySpace/20140507/20140507021745.png)
Then we create a new variable called pop_c and transform the original variable pop into three categories. Here we create the youth population variable again, but this time we make it into thousands and replace the one we just created. replace-: replace contents of existing variables > order state state2 region pop poplt5 pop0_17 * Summary statistics for the three variables Poplt5 long %12.0gc Pop, generate pop0_17 = poplt5 + pop5_17 State2 str2 %-2s Two-letter state abbreviation Variable name type format label variable label Contains data from /Applications/Stata/ado/base/c/census.dta