Sata Commands

Topics: Normal distribution, Regression analysis, Standard deviation Pages: 5 (1231 words) Published: April 16, 2013
Some Stata Commands
Last modified: January 2, 2006 9:51AM
General Plotting Commands
1. Plot a histogram of a variable:
histogram vname
2. Plot a histogram of a variable using frequencies:
histogram vname, freq 
histogram vname, bin(xx) norm 
where xx is the number of bins.
3. Plot a boxplot of a variable:
graph box vname
4. Plot side-by-side box plots for one variable (vone) by categories of another variable vtwo. (vtwo should be categorical)):  graph box vone, over(vtwo)
5. A scatter plot of two variables:
scatter vone vtwo
6. A matrix of scatter plots for three variables:
graph matrix vone vtwo vthree
7. A scatter plot of two variables with the values of a third variable used in place of points on the graph (vthree might contain numerical values or indicate categories, such as male ("m") and female ("f")): scatter vone vtwo, symbol([vthree])

8. Normal quantile plot:
qnorm vname
General commands
1. To compute means and standard deviations of all variables:  summarize 
or, using an abbreviation,
2. To compute means and standard deviations of select variables:  summarize vone vtwo vthree
3. Another way to compute means and standard deviations that allows the by option:  tabstat vone vtwo, statistics(mean, sd) by(vthree)
4. To get more numerical summaries for one variable: 
summ vone, detail
5. See help tabstat to see the numerical summaries available. For example:  tabstat vone, statistics(min, q, max, iqr, mean, sd)
6. Correlation between two variables: 
correlate vone vtwo
7. To see all values (all variables and all observations, not recommended for large data sets):  list 
Hit the space bar to see the next page after "-more-" or type "q" to "break" (stop/interrupt the listing). 8. To list the first 10 values for two variables: 
list vone vtwo in 1/10
9. To list the last 10 values for two variables: 
list vone vtwo in -10/l 
(The end of this command is "minus 10" / "lowercase letter L".) 10. Tabulate categorical variable vname:
tabulate vname 
or, using an abbreviation,
tab vname
11. Cross tabulate two categorical variables:
tab vone vtwo
12. Cross tabulate two variables, include one or more of the options to produce column, row or cell percents and to suppress printing of frequencies:  tab vone vtwo, column row cell 
tab vone vtwo, column row cell nofreq
Generating new variables
1. General.
a. Generate index of cases 1,2, ...,n (this may be useful if you sort the data, then want to restore the data to the original form without reloading the data): generate case= _n 
or, using an abbreviation, 
gen case=_n
b. Multiply values in vx by b and add a, store results in vy:  gen vy = a + b * vx
c. Generate a variable with values 0 unless vtwo is greater than c, then make the value 1:  gen vone=0 
replace vone=1 if vtwo>c
2. Random numbers.
e. Set numbers of observations to n: 
set obs n
f. Set random number seed to XXXX, default is 1000:
set seed XXXX
g. Generate n uniform random variables (equal chance of all outcomes between 0 and 1): gen vname=uniform()
h. Generate n uniform random variables (equal chance of all outcomes between a and b):  gen vname=a + (b - a)*uniform()
i. Generate n discrete uniform random variables (equal chance of all outcomes between 1 and 6) gen vname=1 + int(6*uniform()) 
(These commands simulate rolling a six-sided die.)
j. Generate normal data with mean 0 and standard deviation 1:  gen vname= invnorm(uniform())
k. Generate normal data with mean mu and standard deviation sigma: gen vname= mu + sigma * invnorm(uniform())
1. Compute simple regression line (vy is response, vx is explanatory variable): regress vy vx
2. Compute predictions, create new variable yhat:
predict yhat
3. Produce scatter plot with regression line added:
graph twoway lfit vy vx || scatter vy vx
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