[U] User's Guide

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256 [ U ] 19 Immediate commands19.1.1 ExamplesExample 1Let’s take the example of confidence intervals. Professional papers often publish the mean, standarddeviation, and number of observations for variables used in the analysis. Those statistics are sufficientfor calculating a confidence interval. If we know that the mean mileage rating of cars in some sampleis 24, that the standard deviation is 6, and that there are 97 cars in the sample, we can calculate. cii 97 24 6Variable Obs Mean Std. Err. [95% Conf. Interval]97 24 .6092077 22.79073 25.20927We learn that the mean’s standard error is 0.61 and its 95% confidence interval is [ 22.8, 25.2 ].To obtain this, we typed cii (the immediate form of the ci command) followed by the numberof observations, the mean, and the standard deviation. We knew the order in which to specify thenumbers because we had read [R] ci.We could use the immediate form of the ttest command to test the hypothesis that the true meanis 22:. ttesti 97 24 6 22One-sample t testObs Mean Std. Err. Std. Dev. [95% Conf. Interval]x 97 24 .6092077 6 22.79073 25.20927mean = mean(x) t = 3.2830Ho: mean = 22 degrees of freedom = 96Ha: mean < 22 Ha: mean != 22 Ha: mean > 22Pr(T < t) = 0.9993 Pr(|T| > |t|) = 0.0014 Pr(T > t) = 0.0007The first three numbers were as we specified in the cii command. ttesti requires a fourth number,which is the constant against which the mean is being tested; see [R] ttest.Example 2We mentioned flipping a coin 10 times and having it come up heads twice. The 99% confidenceinterval can also be obtained from ci:. cii 10 2, level(99)Binomial ExactVariable Obs Mean Std. Err. [99% Conf. Interval]10 .2 .1264911 .0108505 .6482012In the previous example, we specified cii with three numbers following it; in this example, wespecify 2. Immediate commands often determine what to do by the number of arguments followingthe command. With two arguments, ci assumes that we are specifying the number of trials andsuccesses from a binomial experiment; see [R] ci.
[ U ] 19.1 Overview 257The immediate form of the bitest command performs exact hypothesis testing:. bitesti 10 2 .5N Observed k Expected k Assumed p Observed p10 2 5 0.50000 0.20000Pr(k >= 2) = 0.989258 (one-sided test)Pr(k
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A Stata Press PublicationStataCorp
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iTable of contentsStata basics1 Rea
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iii8.2 The return message for obtai
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v14 Matrix expressions . . . . . .
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vii18.11.6 Writing online help . .
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ix25.2.15 Treatment of empty cells
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Stata basics1 Read this—it will h
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36 [ U ] 2 A brief description of S
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38 [ U ] 2 A brief description of S
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40 [ U ] 3 Resources for learning a
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[ U ] 4.3 help: Stata’s help syst
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52 [ U ] 4 Stata’s help and searc
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58 [ U ] 5 Flavors of Stata5.2 Stat
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60 [ U ] 5 Flavors of StataThe diff
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62 [ U ] 6 Setting the size of memo
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8 Error messages and return codesCo
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[ U ] 8.2 The return message for ob
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76 [ U ] 9 The Break key9.2 Side ef
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78 [ U ] 10 Keyboard usesave is the
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80 [ U ] 10 Keyboard use10.4 Editin
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82 [ U ] 10 Keyboard useAnother met
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11 Language syntaxContents11.1 Over
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[ U ] 11.1 Overview 8711.1.2 by var
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[ U ] 11.1 Overview 89. summarize m
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[ U ] 11.1 Overview 91Example 7Nega
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11.1.7 options[ U ] 11.1 Overview 9
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[ U ] 11.1 Overview 9511.1.8 numlis
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[ U ] 11.2 Abbreviation rules 97by
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[ U ] 11.3 Naming conventions 99The
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[ U ] 11.4 varlists 101You may use
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[ U ] 11.4 varlists 103Consider a v
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[ U ] 11.4 varlists 105Here are som
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[ U ] 11.4 varlists 107You can sele
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[ U ] 11.4 varlists 109. use http:/
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[ U ] 11.5 by varlist: construct 11
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[ U ] 11.5 by varlist: construct 11
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[ U ] 11.6 File-naming conventions
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12 DataContents12.1 Data and datase
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[ U ] 12.2 Numbers 119. display 2/0
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[ U ] 12.2 Numbers 121Technical not
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[ U ] 12.4 Strings 12312.4 StringsA
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[ U ] 12.5 Formats: Controlling how
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[ U ] 12.6 Dataset, variable, and v
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[ U ] 12.8 Characteristics 139You c
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[ U ] 12.10 References 141The Varia
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144 [ U ] 13 Functions and expressi
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162 [ U ] 14 Matrix expressionsHere
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164 [ U ] 14 Matrix expressionsWe c
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166 [ U ] 14 Matrix expressions. ma
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168 [ U ] 14 Matrix expressionsRega
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170 [ U ] 14 Matrix expressionsEith
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172 [ U ] 14 Matrix expressionsThe
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174 [ U ] 14 Matrix expressions7. W
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176 [ U ] 15 Saving and printing ou
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182 [ U ] 16 Do-filesYou then enter
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184 [ U ] 16 Do-files* a sample ana
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186 [ U ] 16 Do-files16.1.4 Error h
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188 [ U ] 16 Do-filesMany users inc
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190 [ U ] 16 Do-files5. If Stata is
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192 [ U ] 16 Do-filesyou could writ
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17 Ado-filesContents17.1 Descriptio
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[ U ] 17.5 Where does Stata look fo
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17.6 How do I install an addition?A
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18 Programming StataContents18.1 De
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[ U ] 18.2 Relationship between a p
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316 [ U ] 21 Inputting data21.2 Det
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318 [ U ] 21 Inputting dataM,Joe Sm
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322 [ U ] 21 Inputting dataAnother
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22 Combining datasetsYou have two d
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23 Working with stringsContents23.1
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[ U ] 23.4 Complex strings 329The p
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24 Working with dates and timesCont
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[ U ] 24.2 Inputting dates and time
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[ U ] 24.2 Inputting dates and time
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[ U ] 24.6 Converting between date
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25 Working with categorical data an
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[ U ] 25.1 Continuous, categorical,
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[ U ] 25.2 Estimation with factor v
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26 Overview of Stata estimation com
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[ U ] 26.3 ANOVA, ANCOVA, MANOVA, a
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[ U ] 26.5 Binary-outcome qualitati
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[ U ] 26.9 Exact estimators 363In t
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[ U ] 26.14 Models with time-series
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[ U ] 26.15 Panel-data models 367xt
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[ U ] 26.21 Multivariate and cluste
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[ U ] 26.25 Reference 373should try
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376 [ U ] 27 Commands everyone shou
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378 [ U ] 28 Using the Internet to
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390 Subject and author indexcoeffic
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394 Subject and author indexPiantad
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396 Subject and author indexUnix,ke
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