About SPSS The developers of the Statistical Package for Social Sciences (SPSS) to make every effort to make the software easier to use. This prevents you from making a mistake or forget something. That's not to say it's not possible to do anything wrong, but the software SPSS to work hard to keep you from running into the ditch. To foul things up, you almost have to work on figuring out how to do something wrong. You always start by defining a set of variables, and then you enter the data for the variables to make a number of cases. For example, if you do the analysis of the car, each car in your studies will be the case. The variables that determine the case can be things such as year of manufacture, horsepower and cubic inch displacement. Every car in this study is defined as a single case, and each case is defined as a set of values assigned to a collection of variables. Each case has a value for each variable. (Well, you could have lost value, but it is a special situation is explained later.). That is, each of the variables are defined as containing a certain type number. For example, a variable scale are numerical measurements, such as weight or miles per gallon. Categorical variables contain values that define the categories; for example, a variable called gender could be a categorical variable was defined only contains a value of 1 for female and 2 males to. Things that make sense for the types of variables does not always make sense for others. For example, it makes sense to calculate miles per gallon average, but not sex on average. Once your data is entered into SPSS - your case all determined by the values stored in variables - you can run the analysis. You've finished the hard part. Conducting data analysis much easier than entering the data. To run the analysis, you select the one you want to run from the menu, select the appropriate variable, and click the OK button. SPSS read through all your cases, perform analysis, and presents you with output. You can instruct SPSS to draw graphs and charts the same way you instruct it to perform the analysis. You select the desired graph from the menu, set a variable to it, and click OK. When preparing SPSS to perform analysis or draw a graph, the OK button is not available until you have made all the necessary options to produce the output. Not only SPSS require you to choose an adequate number of variables to produce output, it also requires that you choose the right type of variable. If the categorical variables required for a particular slot, SPSS will not allow you to select another type. Is sensible output up to you and your data, but SPSS make sure that the choice you make can be used to produce some sort of result. All output from SPSS to go to the same place - a dialog box named SPSS Viewer. It opens to display the results of whatever you do. Once you have the output, if you perform some actions that produce more output, new output is displayed in the same dialog box. And almost anything you do produce output. How SPSS (Statistical Package for the Social Sciences) Working With Arthur Griffith of SPSS For Dummies The developers of the Statistical Package for Social Sciences (SPSS) to make every effort to make the software easier to use. This prevents you from making a mistake or forget something. That's not to say it's not possible to do anything wrong, but the software SPSS to work hard to keep you from running into the ditch. To foul things up, you almost have to work on figuring out how to do something wrong. You always start by defining a set of variables, and then you enter the data for the variables to make a number of cases. For example, if you do the analysis of the car, each car in your studies will be the case. The variables that determine the case can be things such as year of manufacture, horsepower and cubic inch displacement. Every car in this study is defined as a single case, and each case is defined as a set of values assigned to a collection of variables. Each case has a value for each variable. (Well, you could have lost value, but it is a special situation is explained later.) The variable has a type. That is, each of the variables are defined as containing a certain type number. For example, a variable scale are numerical measurements, such as weight or miles per gallon. Categorical variables contain values that define the categories; for example, a variable called gender could be a categorical variable was defined only contains a value of 1 for female and 2 males to. Things that make sense for the types of variables does not always make sense for others. For example, it makes sense to calculate miles per gallon average, but not sex on average. Once your data is entered into SPSS - your case all determined by the values stored in variables - you can run the analysis. You've finished the hard part. Conducting data analysis much easier than entering the data. To run the analysis, you select the one you want to run from the menu, select the appropriate variable, and click the OK button. SPSS read through all your cases, perform analysis, and presents you with output. You can instruct SPSS to draw graphs and charts the same way you instruct it to perform the analysis. You select the desired graph from the menu, set a variable to it, and click OK. When preparing SPSS to perform analysis or draw a graph, the OK button is not available until you have made all the necessary options to produce the output. Not only SPSS require you to choose an adequate number of variables to produce output, it also requires that you choose the right type of variable. If the categorical variables required for a particular slot, SPSS will not allow you to select another type. Is sensible output up to you and your data, but SPSS make sure that the choice you make can be used to produce some sort of result. All output from SPSS to go to the same place - a dialog box named SPSS Viewer. It opens to display the results of whatever you do. Once you have the output, if you perform some actions that produce more output, new output is displayed in the same dialog box. And almost anything you do produce output. The developers of the Statistical Package for Social Sciences (SPSS) to make every effort to make the software easier to use. This prevents you from making a mistake or forget something. That's not to say it's not possible to do anything wrong, but the software SPSS to work hard to keep you from running into the ditch. To foul things up, you almost have to work on figuring out how to do something wrong. You always start by defining a set of variables, and then you enter the data for the variables to make a number of cases. For example, if you do the analysis of the car, each car in your studies will be the case. The variables that determine the case can be things such as year of manufacture, horsepower and cubic inch displacement. Every car in this study is defined as a single case, and each case is defined as a set of values assigned to a collection of variables. Each case has a value for each variable. (Well, you could have lost value, but it is a special situation is explained later.) The variable has a type. That is, each of the variables are defined as containing a certain type number. For example, a variable scale are numerical measurements, such as weight or miles per gallon. Categorical variables contain values that define the categories; for example, a variable called gender could be a categorical variable was defined only contains a value of 1 for female and 2 males to. Things that make sense for the types of variables does not always make sense for others. For example, it makes sense to calculate miles per gallon average, but not sex on average. Once your data is entered into SPSS - your case all determined by the values stored in variables - you can run the analysis. You've finished the hard part. Conducting data analysis much easier than entering the data. To run the analysis, you select the one you want to run from the menu, select the appropriate variable, and click the OK button. SPSS read through all your cases, perform analysis, and presents you with output. You can instruct SPSS to draw graphs and charts the same way you instruct it to perform the analysis. You select the desired graph from the menu, set a variable to it, and click OK. When preparing SPSS to perform analysis or draw a graph, the OK button is not available until you have made all the necessary options to produce the output. Not only SPSS require you to choose an adequate number of variables to produce output, it also requires that you choose the right type of variable. If the categorical variables required for a particular slot, SPSS will not allow you to select another type. Is sensible output up to you and your data, but SPSS make sure that the choice you make can be used to produce some sort of result. All output from SPSS to go to the same place - a dialog box named SPSS Viewer. It opens to display the results of whatever you do. Once you have the output, if you perform some actions that produce more output, new output is displayed in the same dialog box. And almost anything you do produce output. Excellence SPSS While it is right that the spreadsheet program offers more control relating to the organization of data, this can also be seen as a deficiency. Conversely, you can not move the data block in SPSS as they are meant to regulate the data optimally. Line A represents the case, while columns show one variable. SPSS makes data analysis more quickly because the program knows the location of cases and variables. When using spreadsheets, users have to manually define this relationship in each analysis. SPSS is specifically made to analyze statistical data and thus offers a variety of methods, graphs and charts. General program may offer other procedures such as invoicing and accounting forms, but a special program that is more suitable for this function. SPSS also equipped with more techniques of filtering or cleaning of information in preparation for further analysis. Furthermore, a normal spreadsheet program can only support data analysis immediately after installation, with additional plug-ins required to access the more complex techniques. SPSS is designed to ensure that the output is stored separately from the data itself. In fact, it stores all the results in a separate file that is different from the data. However, in programs such as Excel, the results of the analysis are placed in a worksheet, and there is the possibility of overwriting other information by accident. Benefits of SPSS statistical analysis can be done using two main methods. One is simply by using a spreadsheet or data management general program like MS Excel or through using a special statistical packages such as SPSS. Here are the main reasons why SPSS is the best choice for use. Effective data management Although it appropriate that the spreadsheet program offers more control relating to the organization of data, this can also be seen as a deficiency. Conversely, you can not move the data block in SPSS as they are meant to regulate the data optimally. Line A represents the case, while columns show one variable. SPSS makes data analysis more quickly because the program knows the location of cases and variables. When using spreadsheets, users have to manually define this relationship in each analysis. Wide selection of SPSS specifically created to analyze statistical data and thus offers a variety of methods, graphs and charts. General program may offer other procedures such as invoicing and accounting forms, but a special program that is more suitable for this function. SPSS also equipped with more techniques of filtering or cleaning of information in preparation for further analysis. Furthermore, a normal spreadsheet program can only support data analysis immediately after installation, with additional plug-ins required to access the more complex techniques. Better organization of SPSS output is designed to ensure that the output is stored separately from the data itself. In fact, it stores all the results in a separate file that is different from the data. However, in programs such as Excel, the results of the analysis are placed in a worksheet, and there is the possibility of overwriting other information by accident. Although Excel still offer a good way for the organization of data, using special software such as SPSS better suited for in-depth data analysis. Share: Share on FacebookClick to this email to friendClick to share on TwitterClick to share on PinterestClick to share in Google + Click for print-related benefits SPSS. Benefits of SPSS statistical analysis can be done using two main methods. One is simply by using a spreadsheet or data management general program like MS Excel or through using a special statistical packages such as SPSS. Here are the main reasons why SPSS is the best choice for use. Effective data management Although it appropriate that the spreadsheet program offers more control relating to the organization of data, this can also be seen as a deficiency. Conversely, you can not move the data block in SPSS as they are meant to regulate the data optimally. Line A represents the case, while columns show one variable. SPSS makes data analysis more quickly because the program knows the location of cases and variables. When using spreadsheets, users have to manually define this relationship in each analysis. Wide selection of SPSS specifically created to analyze statistical data and thus offers a variety of methods, graphs and charts. General program may offer other procedures such as invoicing and accounting forms, but a special program that is more suitable for this function. SPSS also equipped with more techniques of filtering or cleaning of information in preparation for further analysis. Furthermore, a normal spreadsheet program can only support data analysis immediately after installation, with additional plug-ins required to access the more complex techniques. Better organization of SPSS output is designed to ensure that the output is stored separately from the data itself. In fact, it stores all the results in a separate file that is different from the data. However, in programs such as Excel, the results of the analysis are placed in a worksheet, and there is the possibility of overwriting other information by accident. Although Excel still offer a good way for the organization of data, using special software such as SPSS better suited for in-depth data analysis. Statistical analysis can be done using two main methods. One is simply by using a spreadsheet or data management general program like MS Excel or through using a special statistical packages such as SPSS. Here are the main reasons why SPSS is the best choice for use. Effective data management Although it appropriate that the spreadsheet program offers more control relating to the organization of data, this can also be seen as a deficiency. Conversely, you can not move the data block in SPSS as they are meant to regulate the data optimally. Line A represents the case, while columns show one variable. SPSS makes data analysis more quickly because the program knows the location of cases and variables. When using spreadsheets, users have to manually define this relationship in each analysis. Wide selection of SPSS specifically created to analyze statistical data and thus offers a variety of methods, graphs and charts. General program may offer other procedures such as invoicing and accounting forms, but a special program that is more suitable for this function. SPSS also equipped with more techniques of filtering or cleaning of information in preparation for further analysis. Furthermore, a normal spreadsheet program can only support data analysis immediately after installation, with additional plug-ins required to access the more complex techniques. Better organization of SPSS output is designed to ensure that the output is stored separately from the data itself. In fact, it stores all the results in a separate file that is different from the data. However, in programs such as Excel, the results of the analysis are placed in a worksheet, and there is the possibility of overwriting other information by accident. Although Excel still offer a good way for the organization of data, using special software such as SPSS better suited for in-depth data analysis. There are various web-based calculators are available for free, and the quality is generally quite good calculator. This is a reasonable alternative if you do the same analysis again and again and you rarely deviate from the routine. This web-based calculators, however, rarely provide graphical summaries of your data. Also, if you switch to a different type of analysis, you have to find a web-based calculators are different. If your primary concern is with accurate data entry, especially for complex research projects, such as multi-center trial, you should use database software, such as Microsoft Access or MySQL. Unfortunately, the database software will not provide anything except for the most basic summary statistics, so you have to pair your database with different programs for data analysis. R, SAS, and Stata. I only list three programs here, but at least a dozen programs out there that is a serious competitor to IBM SPSS. These are all very good programs with a lot of the same advantages of IBM SPSS. If you are already familiar with one of these programs, you should stick with it. The only serious drawback of these programs is that they are difficult to learn for beginners. Comprehensive data management tool. The most important part of any data analysis initial data entry. If you enter data in the wrong way, you will not be able to analyze it properly. Although you can use a variety of options for data entry, often entering data into IBM SPSS is the best choice. IBM SPSS offers a simple spreadsheet format for data entry that is intuitive and easy to start with. More importantly, IBM SPSS provides a variety of data documentation (mainly label value) which will help you to ensure consistency in your data entry. Good graphic display options. Before you begin to analyze your data, you need to understand how your data behaves. This is best done graphically. IBM SPSS presents scatterplots, boxplots, and a histogram that help you to see patterns in your data. You do not have to publish findings based only on an intuitive graphical interpretation, of course. Instead, this graphic will provide you with a general framework to understand your data, so you will be better able to interpret the complex following the procedure concluded. A variety of statistical models. Often you will not know at the start what the research project statistical model will be most suitable for a particular project. Sometimes you will have a general idea, but often a statistical model will change once you start checking your data. Or you'll want to run the analysis of alternatives as a quality check for the analysis originally planned. IBM SPSS offers a wide range of statistical models are very versatile: mainly generalized linear models and logistic regression models. This allows you to have one program that would meet almost all your needs of data analysis. Although some people may need to supplement IBM SPSS with other programs such as R, for most of the people I worked with, IBM SPSS will be the only software package statitical they need. Its easy to learn menu driven interface. Many software programs competing statistics, such as R, SAS, and Stata, run primarily as a programming language. While the programming language offers several important advantages, it takes longer to learn. Furthermore, the complexity often reluctant to you from trying new and different approaches. While Excel is a business tool that is very useful, it has its limitations â € "and now can handle large datasets, you also need help to manage this data. IBM SPSS Advantage for Microsoft Excel provides advanced tools to more efficiently and effectively manage and analyze business dataset. This means you can find the information in your data even if you donâ € ™ t have a detailed knowledge of statistics. IBM SPSS Advantage for Microsoft Excel including 10 special procedures have to allow business users to use advanced data preparation and analysis tools in Excel. In particular, he has a procedure to perform recency, frequency and monetary value (RFM) analysis. Wizards guide you through the steps to help you manage and explore the data, find value in large datasets and perform analysis. IBM SPSS Advantage for Microsoft Excel allows you to create highly visual classification trees that help you identify market segments. For example, using the classification tree to identify the characteristics of customers likely to buy a particular product type. Because you display results visually, you can more clearly see the relationships in your data. Classification tree analysis is a sophisticated, yet easy to use allows you to explore results and find specific subgroups and relationships in your data that you may not find the use of statistics in Excel. Now that Excel datasets can be much larger than before, itâ € ™ s no longer possible to â € œeyeballâ € ?? your data to make sure nothing is wrong. Additionally, more data means a higher risk of bad data. IBM SPSS Advantage for Microsoft Excel provides you with a procedure that allows you to prepare and transform data. Use this procedure to reset the data and put them in a format to aid analysis. In addition, you get more options to explore data, which makes it easier to find value in larger datasets. For decades, analysts have relied on IBM SPSS Statistics to help them guide decision making through data analysis. IBM SPSS Advantage for Excel 2007 provides for techniques IBM SPSS Statistics, plus the ability to access, manage and analyze large amounts of data. This means you can find the information in your data even if you donâ € ™ t have a detailed knowledge of statistics. IBM SPSS Advantage for Microsoft Excel including 10 special procedures have to allow business users to use advanced data preparation and analysis tools in Excel. In particular, he has a procedure to perform recency, frequency and monetary value (RFM) analysis. Wizards guide you through the steps to help you manage and explore the data, find value in large datasets and perform analysis. Preparation IBM SPSS Advantage for Microsoft Excel interface seamlessly integrates into Excel. Simply click on â € œIBM SPSS Advantageâ € ?? from the Excel menu, and select a procedure from tape to start. Each IBM SPSS Statistics function is operated through a wizard or dialog tab, making it easy for you to get results. You donâ € ™ t need scripting or programming skills often required to utilize complex statistical products. Perform RFM analysis of load, frequency and monetary value (RFM) analysis is a technique often used in direct marketing for identifying your most profitable customers. Experience shows that novelty (the latest time you have interaction with customers), frequency (number of interactions you have you been with your customers), and the monetary value (the amount of money you've received from customers) is the best predictor of the propensity to buy from you in the future front. With IBM SPSS Advantage for Microsoft Excel, you can easily perform RFM analysis to identify this customer. Wizards help you create RFM scores for customer or transaction data by stepping you through RFM analysis. IBM SPSS Advantage for Excel 2007 also produces charts for diagnostic tests, which helps you understand your data distribution. Once you have the results, youâ € ™ ll be ready to market to existing customers who are most likely to respond to a new offer. Easy to identify groups of IBM SPSS Advantage for Microsoft Excel allows you to create highly visual classification trees that help you identify market segments. For example, using the classification tree to identify the characteristics of customers likely to buy a particular product type. Because you display results visually, you can more clearly see the relationships in your data. Classification tree analysis is a sophisticated, yet easy to use allows you to explore results and find specific subgroups and relationships in your data that you may not find the use of statistics in Excel. Find unusual data Now that Excel datasets can be much larger than before, itâ € ™ s no longer possible to â € œeyeballâ € ?? your data to make sure nothing is wrong. Additionally, more data means a higher risk of bad data. A specific procedures in IBM SPSS Advantage for Microsoft Excel allows you to capture data that problem so that you can remove or correct them before analysis. Use this procedure to detect invalid values caused by data entry errors and to detect cases that really do not ordinary suitable for analysis. IBM SPSS Advantage for Microsoft Excel will highlight the cells of data and provide a short explanation why it finds anomalies. Prepare and transform data IBM SPSS Advantage for Microsoft Excel provides you with a procedure that allows you to prepare and transform data. Use this procedure to reset the data and put them in a format to aid analysis. In addition, you get more options to explore data, which makes it easier to find value in larger datasets. Join the table â € "With IBM SPSS Advantage for Microsoft Excel, you can combine two Excel tables based on criteria corresponding rows in a table with rows in the other table. Restructure Data â €" You can restructure tables to combine information from multiple lines. For example, use this procedure to restructure transactional data. You can create a row for each customer, with each transaction is recorded in a separate column â € "provides a new way to view the data. Line Aggregate â €" Combine groups of rows in the selected table into a single line to easily create a new, table which contains aggregate data summaries for each group. For example, if you have a table that records every purchase made by a customer on a separate line and identify each customer with a unique ID value, you can group records by ID value. IBM SPSS Advantage for Microsoft Excel allows you to create tables are collected with one row for each customer, using selected summary values for the other columns of the original table. Data group in the range â € "Sometimes you want â € € ?? œbinâ data so you can see his range. For example, you might want to age groups with a range (less than 20, 20-29, 30-39, 40- 49, and so on) to examine the buying habits of different age groups. Values bin procedures IBM SPSS advantage for Microsoft Excel provides a convenient interface to build a range of data. IBM SPSS advantage for Microsoft Excel presents you with cutpoints automatically set that you can customize according best distribution of your data. When you store the values binned, IBM SPSS advantage for Microsoft Excel creates a new column that contains data grouped into ranges. you can also create a column that contains the values of a new text that describes each range, as well as columns containing the sequential integer values assigned to each category range in the order. Optimize trash for models â € "With IBM SPSS Advantage for Microsoft Excel, you can change the scale-type data by distributing value- value to the trash. You can then use the data binned instead of the original data values for further analysis. For example, you might want to optimize data into bins to maintain the privacy of the data source. |

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