This document provides an overview of basic analysis techniques in STATA. It discusses how to work with numeric, categorical, and dummy variable data, including describing, summarizing, coding, labeling, generating dummy variables, and working with categorical data using commands like codebook, tabulate, and recode. It also covers tests for unpaired dichotomous data sets using commands like tabi, prtesti, and tabplot. Finally, it discusses graphical representation of data using pie charts, box plots, histograms, and scatter plots.

1. Basic Analysis in STATA
Dr Tanveer Rehman, Senior Resident

2. NUMERIC DATA
• browse
• describe
• count
• summarize
• sum age, detail
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3. NUMERIC DATA
• mean BMI
• ameans BMI
• tabstat age, by (sex) statistics (n mean sd median iqr min max)
• tabstat age duration hours, statistics (n mean sd median iqr min
max) column (statistics)
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4. CODING & LABELLING
• rename
• recode
• label define label block
• label values variable label block
• label variable
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5. DUMMY VARIABLE
• Indicator variable
• Explanatory variables taking 2 values: Yes / No – 1 / 0
• generate & replace
• tabulate & generate (dummy var)
• browse new variable* variable
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6. CATEGORICAL DATA
• codebook
• tabulate
• tab1
• missing
• tab var var
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7. CATEGORICAL DATA
• row column cell
• tab2
• firstonly
• Three way table
• Four way table
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8. TEST FOR UNPAIRED DICHOTOMOUS DATA SETS
• Immediate form tabi: 1 2 3 4
• Options: chi2, exact, expected
• tests of proportions: prtesti freq prop
• tabplot for visual impression
• Use of “if”
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9. THANK YOU
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10. Graphical representation
1. Graph pie, over(sex)
2. Graph box age, over (sex) orelse hbox
3. Histogram age, normal by(sex)
4. Twoway (scatter var var)
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