Guiding principles for approaching data analysis 1. This course is for those who need to perform advanced data processing and manipulation, and create a variety of outputs. This document introduces you to sas programming using version 9. Data manipulation techniques course notes sas this course is for those who need to learn data manipulation techniques using sas data and procedure steps to access, transform, and summarize sas data sets. Descriptive and inferential statistics 5 the department of statistics and data sciences, the university of texas at austin for anticipating further analyses. It also provides techniques for the analysis of multivariate data, speci. Select any cell within your data and then run the sort tool. For example, how to recode a variable into a new variable, and how to rank. Methods refer to operations that can be performed on an object. Apr 18, 2011 sarah, if the original variable is a string, you could use the substr function in a compute statement. Data manipulations and advanced topics 3 the department of statistics and data sciences, the university of texas at austin section 1.
Fundamental data manipulation techniques the examples in this section illustrate key operations in the manipulation of longitudinal data. This makes the process of manipulating, analyzing and pulling data very simple. The course builds on the concepts that are presented in the sas programming 1. Recode for the pointandclick recode command, click on transform i recode. Adding new variables, declaring missing values, recoding variables.
For the pointandclick version of split file, click on data i split file. The objective of this exercise is to introduce you to some techniques for using spss as well as some. Nov 24, 2009 this video demonstrates creating new variables, recoding, filtering and subsetting data in spss. Data management and manipulation using ibm spss statistics. The primary purpose of spss is to use data manipulation techniques to fetch good results. Examples of data manipulation include recoding data such as reverse coding survey items, computing new variables from old variables, and merging and aggregating data sets. Spss modeler also provides automatic data preparation, which optimizes data for predictive modeling with a single click. What is the age range of the sample minimum and maximum values. If you want to export your raw data we recommend exporting it to excel where you can later print to pdf or manipulate it further.
Data manipulation with excel degroote school of business. Data input and manipulation is the first step of data analysis. Students will gain an understanding of the various options for controlling the ibm spss statistics operating environment and how to. Explains graphics options from the menu and chart editor. Qualitative data analysis is a search for general statements about relationships among categories of data. We gave our spreadsheet that name to tell us it includes data on third and fourth graders in the 200304 and the 200405 school years. Often, data are entered directly into the spss data window which is a form of spreadsheet, or imported from other programs like excel and dbase.
In addition you need to give each variable a variable name, as described in chapter 2. For example, the resizecolumn method will change the width of a column in a pivot table. Methods for gis manipulation, analysis, and evaluation 146 overview this chapter details the methods that the team used to 1 evaluate lands within the study area, 2 delineate conservation focus areas cfas, and 3 prioritize individual. Start spss, choose the file menu option, followed by open suboption, followed by data suboption. Originally it was an acronym of statistical package for the social science but now it stands for statistical product and service solutions. The data editor window allows the researcher to work with spss using a method. Spss is completely about efficiently using data manipulation techniques to fetch good results and excel is about safely handling and storing the data. Data manipulations and advanced topics 4 the department of statistics and data sciences, the university of texas at austin section 2. To cater for this mode of study, for example, attendance for one or two days at a time. Jean russell, bob booth quantitative data analysis using spss 15 6 2. This type of data manipulation is called transforming or. To provide information to program staff from a variety of different. This method can be used when each raw data value is separated from the next one by one or more spaces. Essentials course and is not recommended for beginning sas software users.
This is where you define the variables you will be using. To do this, start spss, click on the open an existing data source button from the opening screen and then on more files. The sort tool can also be found on the home tab excel 2003 data sort excel 2010. Matchmerging data sets that lack a common variable if data sets dont share a common variable, you can merge them using a series of merges in separate data steps. Data management and manipulation using ibm spss statistics is a course on the use of a wide range of transformation techniques, ways to automate data preparation work, manipulate data files and analytical results. Spss have easy access to data with different variable types. Analysis and visualization platform that has toolboxes available for different disciplines, such as modeling or genomic analyses data manipulation. This handout 1 introduces several data entry and data manipulation techniques that help you save. Ibm spss statistics 23 is wellsuited for survey research, though by no means is it limited to just this topic of exploration. In these two sessions, you wont become an spss or data analysis guru, but you will learn your way. To be able to export your results to pdf you must first save your data in order to have it accessible in the spss.
Spss is the major batch processing and statistical tool whereas excel is a standard data manipulation application. Substra1,a2,a3 a1 original string name a2 begin position a3 length ed tesiny hidden emailoriginal message from. Working with data covers data manipulation and cleaning of all kinds. This book focuses on when to use the various analytic techniques and how to interpret the resulting output from the most widely used statistical packages e.
Data is structured by fixed blocks for example, var1 in columns 1 to 5, var2 in column 6 to 8, etc. This is referred to as interactive mode, because your relationship with the program. The course builds on the concepts that are presented in the sasr programming i. To illustrate the type of data manipulation that can be performed with. The procedure is found by choosing select from the data menu. Sorting data the sorting tool is an important, albeit overused tool. Below, selections of publication sas programming 2. Sas programming 2 data manipulation techniques pdf get file sas programming 2 data manipulation techniques pdf. Many people sort their data numerous times when there are often more effective ways to extract the desired output. The difference is that the rows and columns in data view are referred to as cases and variables. Note befor e using this information and the pr oduct it supports, r ead the information in notices on page 297. This form of data entry has its limitations to be sure, but let us first lay it out via an example before we pick it apart. Spss allows us to select part of the data set for further analysis, while excluding the remaining. And its fast handling tasks like data manipulation.
Downloadsas programming 2 data manipulation techniques pdf. Quantitative data analysis using spss pdf practical introduction to quantitative data analysis using the most widely. With spss for macos, you cant simply export your raw data to pdf but you can save any output to pdf. Data management and manipulation with ibm spss statistics is a two day course on the use of a wide range of transformation techniques, ways to automate data preparation work, manipulate data files and analytical results. This course is for those who need to learn data manipulation techniques using sas data and procedure steps to access, transform, and summarize sas data sets. The text includes stepbystep instructions, along with screen shots and videos, to conduct various procedures in spss to perform statistical data analysis. However, another goal is to show how spss is actually used to understand and interpret the results of research. Descriptive statistics data view when spss statistics is launched, the data editor window opens in data view which looks similar to a microsoft excel worksheet a matrix consisting of rows and columns. Spss vs excel top 8 significant differences you need to know. On the other hand, excel is a data manipulation tool.
Data analysis is the process of bringing order, structure and meaning to the mass of collected data. Introduction to quantitative research analysis and spss. Spss helps researchers to set up model easily because most of the process is automated. This includes converting text data male, female to numbers 1, 2 that can be used in statistical analyses and manipulating dates to create new variables e. This is the menu which will allow you to tailor your data before the analysis. Introduction this document is the fourth module of a four module tutorial series. You will need a codebook and to write a program either in stata, spss or sas to read the data. Using spss to understand research and data analysis. Essentials course and is not recommended for beginning sas software. This module describes the use of spss to do advanced data manipulation such as splitting files for analyses, merging two. Theres no rule in how to name a data file whatever makes sense for you.
Research proposal should address analysis, a simple. This section explains time and aggravation savers that many people miss. Navigate the spss interface using the dropdown menus or syntax. This will allow you to search through the various directories on your computer to find where you have stored your data files. Spss allows us to select part of the data set for further analysis, while excluding the remaining cases from these analyses. This method is used if the variables are recorded in the same order for each case but not necessarily.
This provides methods for data description, simple inference for continuous and categorical data and linear regression and is, therefore, suf. Sas also has advanced exploratory features such as data mining. Spss v10 has excellent facilities for data manipulation. The statistical package for the social sciences spss is a package of programs for manipulating, analyzing, and presenting data. This paper presents a variety of data analysis techniques. Opening excel files in spss spss orientation and navigation basic data management and data checking renaming variables labeling variables and values subsetting data recoding variables creating new variables missing information sorting keeping and dropping variables saving data and spss file types what we will cover today. View online this course is for those who need to learn data manipulation techniques using sas data and procedure steps to access, transform, and summarize sas data sets. Students will gain an understanding of the various options for controlling the ibm spss statistics operating environment and. There are two generally recognised methods of data selection. In this page, we will demonstrate how spss performances the following tasks using various movie. Spss is a userfriendly program that facilitates data management and statistical analyses. This tutorial covers the various screens of spss, and discusses the two ways of interacting with spss. We then have several select options within the dialogue box that comes up so we can tell spss. We then load that file into the spss statistical analysis package and perform a crosstabulation of the data.
It is a messy, ambiguous, timeconsuming, creative, and fascinating process. This course is for those who need to learn data manipulation techniques using the sas data step and procedures to access, transform, and summarize data. Course notes by sas this is not your time to commonly go to guide stores to buy a book. On the other hand, the goal of excel is for storing the data and safely handle it. The explanation of how one carries out the data analysis process is an area that is sadly neglected by many researchers. Course notes by sas as well as collections are readily available to download and install.
Spss data manipulation and advanced topics tutorial. Data is for making modifications to the dataset as a whole like merging transform is for modifcations to variables and their values analyze has most all the things you need to look at the data and do statistical analysis paste when doing anything using the dropdown menus, use paste rather than ok to complete the task. A handbook of statistical analyses using spss food and. Spss statistics excels at making sense of complex patterns and associations enabling users to draw conclusions and make predictions. Product information this edition applies to version 24, r elease 0, modification 0 of and to all subsequent r eleases and modifications until. Data management and manipulation using ibm spss statistics v24. Grouping values of a numeric variable recode age lo thru 25126 thru 30231 thru 40341 thru hi4 into agerec. Covers the mechanics of techniques ranging from basic. This playlist contains a number of short videos detailing how to manipulate variables within ibm spss statistics. Step 3analyze data using analyze menu and graphs menu. To properly use data and transform it into useful insights like analysing financial data, customer behaviour and performing trend analysis, you have to be able to work with the data in the way you need it. Data manipulation is a crucial function for business operations and optimisation.
Spss data files and exercises spss survival manual. List input reads data into a sas data set using a space delimited form of data entry. Output window in spss prints underlying syntax generated from any procedure. Spss statistics and spss modeler provide powerful data manipulation techniques, encapsulated in point and click interfaces. Spss is one of the most popular statistical packages which can perform highly complex data manipulation and analysis with simple instructions 17. Data management and manipulation with ibm spss statistics v21. Can be used to check and assure quality data options include sas, spss, r, and matlab not free sas. Using spssusing spss step 1use coded questionnaire to dfi v ibl idefine variables using viblvivariable viewer. In the first example, we select a subset of records and fields from a single file. However, it is sometimes necessary to know how to read what i call raw data numbers andor letters in a text ascii file. Intro to the spss environment is intended for new users of spss. Before you can use spss to help you calculate a frequency distribution you need to give each category of a variable a numeric code.