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LabCode/lab_3.sas

+/* ----------------------------------------------------- */
+/*  AEDE 6120 */
+/*  Lab 3 */
+
+*	Importing data files from the repository;  
+*	Making plots;
+*	SQL in SAS;
+*	Descriptive statistics;                
+* 	T-test of difference in means;         
+* 	Linear regression;                     
+
+/* ----------------------------------------------------- */
+
+* SP21 AEDE6120 repository;
+* 'https://code.osu.edu/liu.6200/sp21-aede6120/-/tree/master/LabData' ;
+* 'https://code.osu.edu/liu.6200/sp21-aede6120/-/tree/master/LabCode' ;
+
+
+/* Importing data files from the repository  */
+
+* step1: set a filename for the data file;
+filename mydata url "https://code.osu.edu/liu.6200/sp21-aede6120/-/raw/master/LabData/wageEX.csv";
+
+* step2: import the data file;
+proc import
+  file=mydata
+  out=work.wagedata replace
+  dbms=csv;
+run;
+
+* step3: clear the filename;
+filename mydata clear;
+
+
+/* Making plots  */
+
+*scatter plot;
+proc sgplot data=sashelp.cars;
+	scatter x=mpg_city y=horsepower;
+run;
+
+*line plot;
+proc sgplot data=sashelp.cars;
+	vline mpg_city / response=horsepower stat=mean;
+run;
+
+*line plot for time series;
+*step 1: sort the data;
+proc sort data=sashelp.stocks out=stocks_sort;
+	by date;
+run;
+
+*step 2: make the plot;
+proc sgplot data=stocks_sort (where=(stock='IBM'));
+	series x=date y=close;
+run;
+
+*plot modification;
+proc sgplot data=stocks_sort (where=(stock='IBM'));
+	title "IMB Closing Price 1986-2006";
+	series x=Date y=Close / markers markerattrs=(color=blue symbol='asterisk') 
+		lineattrs=(color=red)
+		legendlabel="IBM";
+	xaxis grid;
+	yaxis label="Closing Price";
+	reg y=close x=date;
+run;
+
+
+/* SQL in SAS */
+
+*  SELECT - columns (variables) that you want; 
+*  FROM - tables (datasets) that you want; 
+*  ON - join conditions that must be met; 
+*  WHERE - row (observation) conditions that must be met; 
+*  GROUP BY - summarize by these columns; 
+*  HAVING - summary conditions that must be met; 
+*  ORDER BY - sort by these columns; 
+
+*example 1;
+proc sql;
+	create table sql_new as 
+	select wage, female, 
+		   educ as education, 
+		   (wage)**2 as wagesq,
+		   log(wage) as lwage
+	from wagedata
+	where female ne 0
+	order by educ;
+run;
+
+* = eq;
+* >= ge;
+* <= le;
+* ~= ne;
+
+*example 2;
+proc sql;
+	create table sql_new as 
+	select female, 
+			count(female) as countn
+	from wagedata
+	group by female;
+run;
+
+
+
+/* Descriptive statistics */
+
+*simple descriptive statistics;
+proc means data=wagedata;
+run; 
+
+*simple descriptive stats by group;
+*step 1: sort data by group;
+proc sort data=wagedata out=wagedata_sort; 
+	by female; 
+run; 
+
+*step 2: generate descriptive stats;
+proc means data=wagedata_sort;
+	class female;
+run; 
+
+*more descriptive statistics;
+proc univariate data=wagedata_sort;
+	var wage;       *can add more variables;
+	by female;      *optional;
+run; 
+
+*correlations by group;
+*step 1: sort data by group;
+proc sort data=wagedata; 
+	by female; 
+run;
+
+*step 2: generate correlation;
+proc corr data=wagedata;
+	var wage educ exper;
+	by female;
+run; 
+
+
+/* T-test of difference in means */
+ods graphics off;
+proc ttest data=wagedata; 
+	var wage educ exper;
+	class female; 
+run;
+
+
+/* Linear regression */
+ods graphics off;
+proc reg data=wagedata;
+	model wage=educ exper married;
+	output out=ols residual=resid predicted=pred;
+run;
+quit;
+
+
+