Course Content
Introduction To Stata
installation of Stata software
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Data Entry using Stata
Introduction to coding Variable
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Descriptive Analysis
descriptive Statistics
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Inferential Analysis
Chi-square Test Pearson Correlation independent Sample T test
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Regression
OLS Regression
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Functions
introduction to AGGREGRATE functions
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Introduction to Statistical Package For Social Science
• Explain how IBM SPSS Statistics is used for basic analysis • Explain the basic steps in data analysis • Understand the primary windows in IBM SPSS Statistics • Understand the different components of dialog boxes
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Data Entry Primary Sources
• Describe and define variable properties in the Variable View window • Use the Define Variable Properties dialog box • Save variable properties with data in an IBM SPSS Statistics data file • Use the Variables utility to view variable properties interactively • Use the Display Data Dictionary facility and the Codebook procedure to view variable properties
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Reading Data
Import data from different types of file formats • Describe choices on the File menu for reading data • Read Microsoft Excel files • Read delimited text files
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Data Management
Use Visual Binning to reclassify values of an ordinal or scale variable • Use Recode into a Different Variable to reclassify values of a nominal variable • Use Automatic Recode to create a numeric variable from a string variable Describe the features of Compute Variable • Create new variables with numeric expressions • Create new variables with conditional numeric expressions
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Summarizing Individual Variables
Define levels of measurement • Use the Frequencies procedure to produce tables and charts appropriate for nominal variables • Use the Frequencies procedure to produce tables and charts appropriate for ordinal variables • Use the Frequencies and Descriptive procedure to produce tables and charts for scale variables
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Relationship Between Variables
• Select the appropriate procedure to summarize the relationship between two variables • Use the Crosstabs procedure to summarize the relationship between categorical variables • Use the Means procedure to summarize the relationship between a scale and a categorical variable
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Quantitative Data Analysis Cohort 4 (EVENING)

Data management using the following Concepts

  1. Recode
  2. Select
  3. Split file
  4. Compute
  5. Pivot Table
  6. Merge files
  7. Duplicates and missing Values
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