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Learning Sas In The Computer Lab,9780495559689
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Learning Sas In The Computer Lab



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Cengage Learning
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  • Learning SAS in the Computer Lab, 3rd Edition
    Learning SAS in the Computer Lab, 3rd Edition
  • Learning Sas in the Computer Lab
    Learning Sas in the Computer Lab


The third edition of Elliott and Morrell's innovative lab manual makes it easy to analyze all types of statistics problems and the exceptional database management techniques that SAS offers. Students will learn the basics of the SAS programming language, be able to apply computing techniques in their statistics courses, acquire an appreciation for data analysis, and gain a valuable career skill that will serve their professional activities.

Table of Contents

Introductionp. 1
The Basicsp. 3
Data Set Structurep. 3
Data Steps and Proc Stepsp. 4
The Data Stepp. 4
Proc Printp. 5
The Input Statementp. 7
Comparison of Character Formatsp. 10
Sas Program, Log, and List Filesp. 11
Problemsp. 13
More Sas Basicsp. 17
Subsetting Ifp. 17
If...Then...Else Statementsp. 18
Proc Formatp. 19
Subsetting Wherep. 20
Using Data From Outside Filesp. 20
Missover Option on Infile Statementp. 22
Proc Import for Microsoft Excel Filesp. 23
Proc Sortp. 23
Set Statementp. 27
Problemsp. 28
Data Managementp. 31
How SAS "Thinks"p. 31
Lag Functionp. 32
Drop and Keep Statementsp. 33
Combining Data Setsp. 33
Comment Linesp. 37
Limiting The Number of Observations Read From External Filesp. 38
Setting The Size of the Outputp. 39
The Put Statementp. 39
Proc Export for Microsoft Excel Filesp. 40
Problemsp. 41
SAS Functionsp. 43
Numeric Functionsp. 43
Character Functionsp. 44
Probability Functionsp. 44
Descriptive Statistics Functionsp. 45
Problemsp. 47
Descriptive Statistics Ip. 49
Label Statementsp. 49
Title Statementsp. 50
Proc Univariatep. 50
Proc Boxplotp. 61
Problemsp. 63
Proc Gchartp. 65
Proc Gchartp. 65
Problemsp. 70
Descriptive Statistics IIp. 73
Proc Meansp. 73
Proc Freqp. 74
Problemsp. 78
Generating Random Observationsp. 81
Sas Distribution Functionsp. 81
Do Loopsp. 82
Problemsp. 90
X-Y Plotsp. 93
Proc Gplotp. 93
Problemsp. 97
One-Sample Tests For , Pp. 101
One-Sample T-Testsp. 101
One-Sample Test For Pp. 103
Problemsp. 104
Two-Sample T-Testsp. 107
Proc T-Testp. 107
T-Tests: Two-Sample, Pooled, and Pairedp. 110
Problemsp. 112
One-Way Anovap. 115
Analysis of Variance-Proc Glm And Proc Anovap. 115
Problemsp. 122
Two-Way Anova and Morep. 125
Two-Way Anovap. 125
General Anova Analysisp. 130
Problemsp. 135
Model Checking In Anovap. 137
Plots For Model Checkingp. 137
More On Proc Glmp. 138
Problemsp. 144
Correlationsp. 145
Proc Corrp. 145
Problemsp. 150
Simple Linear Regressionp. 153
Proc Regp. 153
Problemsp. 161
Model Checking In Regressionp. 163
Plots For Model Checkingp. 163
More on Proc Regp. 164
Problemsp. 171
Multiple Linear Regressionp. 173
Multiple Regressionp. 173
Problemsp. 177
Multiple Regression: Aids for Selecting And Assessing Modelsp. 179
Statistics Used in Multiple Regression Model Checkingp. 180
Proc Reg Selection= Optionp. 187
Problemsp. 195
Tests for Categorical Datap. 199
Chi-Square Testsp. 199
Problemsp. 206
Nonparametric Testsp. 209
One-Sample Testsp. 209
Tests for Two or More Samplesp. 209
Problemsp. 212
Analysis of Covariancep. 215
Using Proc Glm for Ancovap. 215
Problemsp. 219
Logistic Regressionp. 221
Proc Logisticp. 221
Problemsp. 235
Matrix Computationsp. 237
Proc IMLp. 237
Problemsp. 243
Macro Variables and Programsp. 247
Macro Variablesp. 247
Macro Programsp. 248
Problemsp. 257
Description of Data Setsp. 259
Indexp. 289
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