Title | summary of Stata Commands |
---|---|
Course | Introduction to Psychological Design and Statistics |
Institution | Macquarie University |
Pages | 2 |
File Size | 192.5 KB |
File Type | |
Total Downloads | 512 |
Total Views | 779 |
Download summary of Stata Commands PDF
STATA COMMANDS Numerical Summaries 1 variable Tabulate variable(s) Tab1 variable(s) Tabulation variable(s) Summarize variable, detail Tabstat variable, statistics (n mean sd median iqr range) Graphical Summaries 1 variable Graph bar (count), over (variable) Graph bar (percent), over (variable) Graph pie, over (variable) Histogram variable Graph hbox variable Numerical Summaries 2 variables Tabulate variable1 variable2 Tabulate variable1 variable, row [gives percentages] Graphical Summaries 2 variables Graph bar (percent), over (variable1) over (variable2) Graph bar (count), over (variable1) over (variable2) Scatter variable1 variable2 Correlate variable1 variable2 Graph box variable1, over (variable2) 1 Categorical 1 Numerical Variable By (cat)variable, sort: summarise (num)variable, detail TEST One-sample Z-test One- sample T-test
CAT/NUM 1 Numerical Known sd 1 Numerical Unknown sd
Chi Squared GOFT Two-sample T-tests
1 Categorical
Paired T-test
RELATED 1 Numerical 1 Categorical
INDEPENDEN T 1 Numerical 1 Categorical
COMMANDS 1. Ztest (num)variable == hypothesised age, sd(sd number) 1. Tabstat variable, stat (n, mean, sd, median, iqr, min, max) 2. Calculate t statistic & df (v = n-1) 3. Ttest variable == hypothesised mean 1. Display chi2tail(df, test-statistic) 2. Csgof variable, expperc(percentage for each category) 1. By (cat)variable, sort: summarize (num)variable 2. Histogram (num)variable, by(cat variable) freq 3. Ttest (num)variable, by (cat variable) Or 1. By (cat)variable, sort: swilk (num)variable 2. Histogram (num) variable, by (cat)variable 3. Robvar (num)variable, by (cat variable) 4. Ttest (num)variable, by (cat variable) 1. Ttest variable1 == variable2
Paired t-tests & one-sample t-tests Chisquared TOI
1. Generate Difference = variable1 – variable2 2. Ttest Difference == 0 2 Categorical
1. Tabulate variable1 variable2, row expected chi2
Shapiro-wilk test for normality Swilk variable Effect Sizes Name Tests Used On Cohen’s D One-sample T-test
Equation D = sample mean – hypothesised mean / sample sd
Cohen’s D
Two-sample T-test
D = mean 1 – mean 2 / pulled sd
Cohen’s D
Paired T-test
D = sample mean difference / sd of difference
Cohen’s W
Chi-squared Tests
W=
x2 chi-squared statistic
Size of Effect...