The principal goal of this chapter is to introduce you to the Microsoft Excel and Statistical Package for the Social Sciences (SPSS) environments. This chapter will prepare you to:
Why learn to use a spreadsheet or statistical software package? We find that nurses, especially those in advanced practice and leadership positions who are familiar with software programs for quantitative data analysis, are able to make their evidence-based practice work easier and more efficient. Consider a chief nursing officer (CNO) of a large chain of long-term-care facilities, who makes decisions about staffing ratios and staffing mix to ensure that residents receive good-quality care and to meet accrediting requirements. The CNO collects and enters data from each facility on daily resident census and absences among the nursing staff. Using visual displays such as graphs and descriptive statistics, the CNO learns that peak absenteeism coincides with night-shift duty and weekends (not a big surprise). Using these statistical findings, the CNO approaches the board of directors for approval of a significant increase in the night-shift and weekend salary differential. Having well-organized statistics allows the CNO to advocate for policy changes to promote improved staffing ratios and avoid costly fees associated with violations of accrediting or inspecting bodies. A spreadsheet or software package can be helpful in creating visual displays and calculating statistics when the volume of data may be large, and when the statistics require complex calculations. (We will address this point more in detail later in Chapters 5 and 6.)
Nurse managers, executives, advanced practice nurses, quality improvement officers, and bedside nurses may all find occasions in which statistical results generated from data are required to make important policy and patient care decisions or influence those in a decision-making role. Use of a spreadsheet or statistical software package can uncover valuable insights more quickly and easily from all types of data.
Spreadsheet and statistical software packages are used to assist researchers and clinicians in answering practice and research questions. Microsoft Excel is probably the most popular spreadsheet software that is widely used regardless of the type of business, and the Statistical Package for the Social Sciences (SPSS) is one of the most popular statistical packages available. Excel is a part of Microsoft Office and supports a variety of analytical efforts including data management and data-driven analytical techniques. SPSS originated in the social sciences, as the original acronym suggests, but it is used extensively in many fields because of its simplicity. This chapter will give you a brief overview of Microsoft Office Excel 365, as well as SPSS version 25.0 (IBM Corp., 2017) and assist you with developing the basic skills to use these soft ware packages rather than intending to be a complete tutorial. At this point, you may be asking yourself, “How do I know if I should use Excel or SPSS?” The answer is, it depends. In general, Excel has many features that are useful for describing data. However, more complex statistics, such as exploring relationships or predictive modeling, are best accomplished in SPSS. Note, however, that some statistical tests and procedures are either not available or very complicated to run in Excel. This text will only cover those that can be obtained in Data Analysis ToolPak or with minimal functions, and go straight to SPSS, where there is no streamlined approach in Excel. In later chapters, we will show you how to perform a variety of statistical techniques in both Excel and SPSS, and explain how to interpret the corresponding outputs.
CASE STUDYData from Potvin Kent, M., Pauzé, E., Roy, E. A., de Billy, N., & Czoli, C. (2019). Children and adolescents’ exposure to food and beverage marketing in social media apps. Pediatric Obesity, 14(6), e12508.
Potvin et al. (2019) published findings from an observational study on the frequency and nature of food advertisements that Canadian children and adolescents saw on social media. The researchers wanted to find the rates of weekly and annual exposure to unhealthy food products, as well as the differences in children and adolescents (ages 7μ16 years) viewing social media applications. The authors found 72% of participants (n = 101) surveyed had seen 215 instances of food marketing on their two preferred social media apps. Additionally, 44% were fast food and 9% were sugar-sweetened drinks, and exposure to these ads was higher among adolescents (Mean [SD] = 2.6 [2.7] versus 1.4 [2.1], U = 1606, z = 2.94, P = 0.003). They recommended regulatory restrictions for advertising unhealthy foods on social media apps that children and adolescents use. |
You can either double-click the Excel icon on your desktop, if available, or select Microsoft Excel from the Start menu (Figure 4-1). Once you open Excel, the opening screen should resemble Figure 4-2.
Opening Excel from the Start menu.A screenshot shows the selection of Microsoft Excel on clicking the Start button.
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Opening screen of Excel.A screenshot shows the opening screen of Excel.
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From the opening screen of Excel, you can create a new workbook or access your recent workbooks. You will locate and select “Blank Workbook” to open a new workbook, and click “Open Other Workbooks” to work on an existing workbook (Figure 4-3). Note that your recently edited workbooks will appear above “Open Other Workbooks.”
Selecting workbook in Excel.A screenshot shows the opening screen of Excel, and the selection of blank workbook template.
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The workbook window provides the space for a variety of workbook elements, such as the quick access toolbar and ribbon (Figure 4-4). There are many other elements that an investigator can utilize to help with data analysis, but we will discuss these as needed when we explain different types of statistical analyses.
Excel workbook elements.A screenshot of an Excel worksheet displays a variety of workbook elements.
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The Quick Access toolbar allows you to access common commands such as the Automatically Save, Save, Undo, and Redo commands by default. Other commands can be added simply by selecting the command(s) you wish to add from the drop-down menu or from “More Commands” (Figure 4-5). Note, however, the list can become too long and confusing, so we recommend you be selective.
Quick access toolbar.A screenshot of an Excel worksheet shows the list of tools of the quick access toolbar.
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The Ribbon is a toolbox at the top of the screen containing menus and commands that is designed to help you quickly access the commands you need to complete a task. Usually, the ribbons are arranged into three main parts, Tabs, Groups, and Commands (Figure 4-6). Tabs represent a general activity of area, each related to specific kinds of tasks that you perform. For example, “Home” has the tools most often used, such as Open, Save, and Print, and “Formula” has the tools to write functions to compute values. Groups are shown below Tabs and show related “Tools” together in logical groups under different Tabs. Commands are actual tools, which can be a button or expandable menu, that are organized into logical groups.
Parts of the ribbon.A screenshot of an Excel worksheet shows the parts of the ribbon of the Home menu, wherein the menu is divided into groups, namely, clipboard, font, alignment, number, and in turn each group consists of commands, namely cut, font, wrap text, autosum.
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You can directly type data into a worksheet cell or copy and paste data from another worksheet or from other programs. To enter data, you can simply designate a cell and then type the data. You can press Enter to move to a cell in the next row, or Tab to move to a cell in the next column. Note that you can also move to another cell using the arrow keys. To copy and paste the data from another worksheet or from other programs, you can use copy from the right-click or the shortcut Ctrl+C on the cell to copy and then paste onto the desired cell using paste from the right-click or the shortcut Ctrl+V.
You can also import data in other formats, such as text, CSV, DBF3, or DBF4. Although there are other types of formats you can import into Excel, only text and CSV files are discussed here, as they are the most commonly imported files. Consider a situation in which your hospital admissions department keeps patient records using Microsoft Word. As a member of the shared governance in the hospital, you have been asked to identify the top 10 admission diagnoses and the length of stay for each of those admission diagnoses. Numerical data in a Word document may be imported into Excel to calculate a range of statistics that would help identify the most common diagnoses.
Text data are composed of contents directly inputted from the computer keyboard and can be easily imported to all computer software. Figure 4-7 shows the same example data.
Text data file.A screenshot of a Notepad file titled, Import, shows five columns with headings, Age, Sex, Cholesterol, S B P, and Heart rate, and eight rows of numerical data under each column.
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To import text, first go to File > Open > Browse. A new window (Figure 4-8) will appear. (Figures 4-9 to 4-11 show the additional screens.) Once you locate where the file was saved, change “Files of Type” from All Excel Files to All Files to show your desired text file. Select TextFile.txt and click “Open.”
Locating and opening the desired file.A screenshot shows the Open command in Excel selected, and the Open dialog box displayed.
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Text import wizard, step 1.A screenshot of a window that displays the first of the three steps of the Text import wizard of an Excel file.
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Text import wizard, step 2.A screenshot of a window that displays the second of the three steps of the Text import wizard of an Excel file.
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Text import wizard, step 3.A screenshot of a window that displays the third of the three steps of the Text import wizard of an Excel file.
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Without special changes, click “Next.”
This text file contains the data values separated by Tabs, so leave all options in default mode (i.e., delimited checked) and click “Next.”
Our data display shows the delimiters that our data contains. Because data look the way they should, click “Next.”
Again, our column data format looks the way it should, so click “Finish.” You have now successfully imported a text file into Excel.
Importing a CSV file into Excel is easier than importing a text file. Assume that the same data file was saved in CSV format. To import a CSV file, go to File > Open > Data. In a new window, as presented in Figure 4-8, change “Files of Type” from All Excel Files to All Files once you locate where the file was saved. Then, select CSVFile.csv and click “Open” in order to open the file, as we did with the text file.
Excel provides many formatting tools to make the presentation of cell values look better and easier to read. For example, if you type “Number of Medications Administered,” it will be too long to fit into a cell. Placing the mouse pointer on the thin line between columns and double-clicking would automatically adjust the column to fit the text in the cell. In another example, assume that a nurse needs to enter the price of medications, but typing a numeric value would not contain the dollar sign with no specific format. Select cell range with numeric values in, then click the small arrow next to the dollar sign, as seen in Figure 4-12, and select “English (United States).” This will show numeric values in a desired format (Figure 4-13).
Changing number format.A screenshot of an Excel worksheet displays the different currency formats.
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Result of changing number format.A screenshot of an Excel worksheet shows numerical data with the dollar currency and two decimal places. The data in the first four rows of Column A are as follows: Price; $ 105.00; $ 175.00; $ 200.00.
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Excel provides numerous formulas and functions that allow you to quickly make specific calculations. Although we cannot cover every formula and function, let us learn how to perform basic calculations. For example, an emergency department (ED) nurse might be interested in how many patient visits the ED had this past week. With the data shown in Figure 4-14, click into cell B9 and type the equal (=) sign (Note: Formulas and functions always begin with an equal sign), followed by “B2+B3+B4+B5+B6+B7+B8”, as we need to add patients over the past 7 days. You should get “60” as a resulting value in cell B9 once you hit Enter (Figure 4-15). Note that you can also get the same value by clicking the “∑Autosum” function on the top right corner of the worksheet with cell B9 selected (Figure 4-16). A variety of functions are available in the “Formulas” Tab, and clicking “Insert Functions” on the top-left corner will open a new window, as shown in Figure 4-17. You can select a function from the list that will suit your need; we will cover selected functions in later chapters.
Using formulas to calculate values.A screenshot of an Excel worksheet shows the addition formula of a random numerical list.
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Result of using formulas to calculate values.A screenshot of an Excel worksheet shows the added value of a random numerical list.
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Using the Autosum function.A screenshot of an Excel worksheet displays the Autosum function.
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Inserting different functions and formulas.A screenshot of an Excel worksheet depicts the insertion of different functions.
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Additional worksheets can be added by clicking the new sheet button next to “sheet1” (Figure 4-18), and multiple worksheets can be useful to organize a large amount of data. You can rename a worksheet by doing the following: (1) double-click on the worksheet name to be renamed, or right-click on the worksheet name to be renamed and choose “Rename” from the menu; (2) type the desired name for the worksheet to be renamed; and (3) press Enter. To delete a worksheet, you will need to click on the worksheet to remove and then choose Home→Delete→Delete Sheet on the Ribbon or right-click Tab and then choose Delete from its shortcut menu.
Adding worksheets.A screenshot of an Excel worksheet shows the name of the current sheet, Sheet 1; it is followed by a tab with a plus sign indicating addition of a worksheet.
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You can either double-click the SPSS icon on your desktop, if available, or select SPSS from the Start menu (Figure 4-19). Once you open SPSS, the opening screen should resemble Figure 4-20.
Opening SPSS from the Start menu.A screenshot shows the selection of I B M, S P S S, Statistics on clicking the Start button.
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Opening screen of SPSS.A screenshot of an Excel worksheet shows the I B M, S P S S, Statistics dialog box.
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There are three major file types in SPSS: data files, syntax files, and output files. Data files (*.sav) contain the actual data values. Data can be either directly entered into SPSS or be imported from other formats, such as Excel, dBase, and Lotus files. Beginning with version 10.0, data files may be viewed from two different windows, each with a separate purpose: data view and variable view. Data view is where the data may be directly inputted, and variable view is where the characteristics of the variables, such as variable name, type, label, and values, are defined (Figure 4-21).
Different views in SPSS.A screenshot shows the different views in S P S S, Data view and Variable view.
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Syntax files (*.sps). contain programmable SPSS commands to conduct analyses (as shown in Figure 4-22) and are a good alternative to using the interactive windows and drop-down menus. Although there are certain analyses that can only be performed with syntax files, we will not discuss these in detail here, as most of the analyses for our purposes can be conducted with interactive windows.
Syntax file in SPSS.A screenshot displays the S P S S syntax file.
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Output files (*.spv) contain the results of the analyses, as well as any error messages or warning messages (Figure 4-23). An output file can be saved, edited, printed, or pasted into other applications such as Microsoft Word and PowerPoint.
Example of output files in SPSS.A screenshot shows an output file in S P S S.
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Because SPSS uses interactive windows, it is a relatively user-friendly software package. On SPSS 25.0, there are a total of 11 drop-down menus, which are categorized into windows and general-purpose, data definition, and/or data analysis drop-down menus.
Windows and general-purpose menus include FILE, EDIT, VIEW, UTILITIES, WINDOW, and HELP menus. The FILE and EDIT menus should be familiar, as these are similar to other software packages. The FILE menu includes options to create new files, open existing files, or save and print the files or outputs. The EDIT menu allows you to find a case or variable, to cut and paste a data value, and so on. The HELP menu includes an SPSS tutorial, which we recommend, because it provides detailed explanations on important topics and serves as a reference for users. We remember that many times the HELP menu has saved us!
Data definition menus include the DATA and TRANSFORM menus. The DATA menu includes procedures for inserting new variables or cases, sorting cases, merging files, splitting the file, selecting cases, and weighting cases. The TRANSFORM menu includes procedures for recoding variables, replacing missing values, computing new variables using existing variables, and a random number generator. These two menus are useful when a researcher wants to manipulate the file to resolve issues with violated assumptions or extremely unequal sample sizes for different groups. More on this will be discussed in Chapter 7.
Data analysis menus include the ANALYZE and GRAPH menus. The ANALYZE menu includes both statistical and psychometric (reliability and validity testing) procedures, and the GRAPH menu includes various procedures for creating graphs and plots. One thing to note here is that some of these graph tools are available within statistical procedures under the ANALYZE menu. We will present how to use these functions to perform data analysis and create graphs as we discuss the corresponding analytic procedures.
There are many icons on the menu bar that are associated with some of the same procedures as the drop-down menus. However, they will not be discussed, as these icons display their functions by placing the cursor over them. Note also that we have included only 10 drop-down menus in the three types of menus noted, leaving out the EXTENSIONS menu, as these are beyond the scope of this text.
When entering data into SPSS, the first step is to complete a variable view window. This view displays the characteristics of the variables that must be defined so that the data may be entered appropriately into data view. These characteristics include variable name, type, width, decimals, label, values, missing, columns, align, measure, and role. Only the commonly defined characteristics are covered here.
The variable name should begin with a letter and only contain letters and numbers. It should not contain punctuation or spaces and cannot begin with a number. The name can be up to 64 characters in length, but we recommend using short names, approximately 8 to 10 characters, as variable names longer than this can create wordy outputs that may be difficult to read. For example, a question such as, “How many times did you smoke during the past 3 months?” should be named like “Smoke3” instead of using the entire question as a variable name. Note: the name must not begin with a number and cannot contain special characters such as @, $, space, and so on.
Type includes many different formats, but numeric and string are the most commonly used ones. When the data are quantitative, such as age, the format should be left as the default, numeric. The format should be changed to string when the data are qualitative, such as responses to explain the choice of “other” categories in racial groups.
Decimal characterizes how many decimals are to be shown for variables. The default is set to 2, or the hundredths place, but unless data will be recorded or entered with decimals, we recommend changing to 0 to view the data more clearly.
Label is a description of what a variable represents in more detail. Although we recommend using a short variable name, it may be easy to forget what the abbreviated variable name means. The label field allows up to 255 characters to describe the nature of the variable in more detail. For example, if we are entering data on wound characteristics, the variable name might be “depth,” but the label may be much more detailed, such as “wound depth as measured in millimeters to the nearest whole number.”
Values specify what numbers will be used to represent categories for categorical variables. You will need to indicate how numbers are assigned for categories, and this can be accomplished by clicking the gray square box with “…” on the right corner of a cell. Consider a case in which we are recording race. We assign a numerical value for each racial group: African American—1, Hispanic—2, Asian/Pacific Islander—3, White—4, and Multiracial—5. Values allow us to assign a number to categories of a discrete/categorical variable.
Measures represent the level of measurement. Note that interval and ratio levels of measurement are combined in the term Scale. Table 4-1 shows the characteristics that define each variable, and we recommend spending some time using the drop-down menu to get the feel of it.
Name | Define the variable’s name that will appear on the top row of data view. We recommend that you keep the name to eight characters or fewer, as a long variable name will not be shown well in data view. Note that you cannot include certain symbols, such as +, μ, %, or &, nor can you use spaces. |
Type | Define the types of the data. There are different data types, such as numeric, comma, date, dollar, and strings; however, you will mostly use numeric (i.e., numbers for data values) or string (i.e., letters/words). |
Width | SPSS, by default, sets this at 8 characters. You will be fine with digits for a width of the variable most of the time, but it is subject to change to fit your needs. |
Decimals | SPSS, by default, sets this at 2, or the hundredths place. You can change this to other values to fit your needs. For example, you can set it to 0 if your data value will be integers. |
Label | Here, you can describe the variable in more detail than you can in the short variable name. This will help you keep the variable name short but still remember what it represents. |
Values | For categorical variables, you can assign numbers to represent different groups of people. For example, you can assign 1 for male and 2 for female. |
Missing | You can assign numbers to missing data. Systematic missing, by default, puts a dot in the cell. You can also assign an impossible value for a certain variable to indicate missing data, such as “9” in a scale ranging 1 to 5. |
Columns | This indicates how many characters will appear in the column. You can change this to fit your needs. |
Align | This sets where the data values in data view will appear. You will choose either left, right, or center. |
Measure | This represents the level of measurement of a variable. You will choose either nominal, ordinal, or scale. |
The next step of data entry is to prepare a codebook, which summarizes the characteristics of the defined variables. The codebook guides the creation of the data file and helps minimize errors with data entry. There are other components that may appear on the codebook, but a typical codebook includes the following:
Go to Analyze > Report > Codebook to create a codebook, as shown in Figure 4-24. The variable view of the sample data set is shown in Figure 4-25. Creating a codebook as part of designing a study or evidence-based practice project is often a useful exercise for exposing flaws in measurement decisions or prompting questions about how data will be entered and analyzed.
Creating a codebook.A screenshot in S P S S shows the options selected to prepare a codebook.
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Courtesy of IBM SPSS Statistics. Variable view of a sample data set.A screenshot shows the variable view of a sample data set.
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Entering data is simple after the first two steps are complete, as it will be just a matter of typing in the collected data values according to your specifications in the variable view. Table 4-2 contains example data for you to use to practice making a codebook and entering data. Once the prior procedures are completed, you should obtain a data set similar to the one shown in Figure 4-26. Note that Figure 4-26 is not in exactly the same format as you will see in SPSS.
Smoking History | Life Satisfaction | Self-Confidence | Gender |
---|---|---|---|
4 | 40 | 86.30 | 1 |
27 | 80 | 70.18 | 1 |
5 | 80 | 61.52 | 2 |
10 | 67 | 55.51 | 2 |
9 | 58 | 70.10 | 1 |
13 | 48 | 95.52 | 2 |
A screenshot shows the codebook of a sample data.
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You can also import data from other computer applications/software, such as Excel, text, or Statistical Analysis System (SAS) files. Although there are other types of formats you can import into SPSS, only text and Excel files are discussed here, as they are the most commonly imported files. Consider a situation in which your hospital admissions department keeps patient records using Microsoft Excel, a spreadsheet application used to collect, organize, and conduct arithmetic calculations. As a member of the shared governance in the hospital, you have been asked to identify the top 10 admission diagnoses and the associated risk factors for each of those admission diagnoses. Excel data may be imported into SPSS to calculate a range of more advanced statistics that would help identify the significant risk factors for those common diagnoses.
Text data are composed of contents directly inputted from the computer keyboard and can be easily imported into SPSS. Figure 4-27 shows the same example data we used in creating a codebook.
Text data file.A screenshot shows a notepad file with four columns and six rows of numerical data, shown as follows. Row 1: 4, 40, 86.30, 1. Row 2: 27, 80, 70.18, 1. Row 3: 5, 80, 61.52, 2. Row 4: 10, 67, 55.51, 2. Row 5: 9, 58, 70.10, 1. Row 6: 13, 48, 95.52, 2.
Courtesy of Windows Notepad © Microsoft 2020.
To import text, first, go to File > Open > Data. A new window (Figure 4-28) will appear. (Figures 4-29 to 4-35 show the additional screens.) Once you locate where the file was saved, change “Files of Type” from *.sav to *.txt to show your desired text file. Select TextFile2.txt and click “Open.”
Locating and opening the desired file.A screenshot shows the Open dialog box of the I B M, S P S S, Statistics Editor.
Courtesy of IBM SPSS Statistics.
Text import wizard, step 1.A screenshot of a window that displays the first of the six steps of the Text import wizard of the I B M, S P S S, Statistics Editor.
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Text import wizard, step 2.A screenshot of a window that displays the second of the six steps of the Text import wizard of the I B M, S P S S, Statistics Editor.
Reprint Courtesy of International Business Machines Corporation, © International Business Machines Corporation. “IBM SPSS Statistics software (“SPSS”)”. IBM®, the IBM logo, ibm.com, and SPSS are trademarks or registered trademarks of International Business Machines Corporation.
Text import wizard, step 3.A screenshot of a window that displays the third of the six steps of the Text import wizard of the I B M, S P S S, Statistics Editor.
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Text import wizard, step 4.A screenshot of a window that displays the fourth of the six steps of the Text import wizard of the I B M, S P S S, Statistics Editor.
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Text import wizard, step 5.A screenshot of a window that displays the fifth of the six steps of the Text import wizard of the I B M, S P S S, Statistics Editor.
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Text import wizard, step 6.A screenshot of a window that displays the sixth of the six steps of the Text import wizard of the I B M, S P S S, Statistics Editor.
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End product of text import wizard.A screenshot shows the final result of the text import wizard of the I B M, S P S S, Statistics Editor.
Reprint Courtesy of International Business Machines Corporation, © International Business Machines Corporation. “IBM SPSS Statistics software (“SPSS”)”. IBM®, the IBM logo, ibm.com, and SPSS are trademarks or registered trademarks of International Business Machines Corporation.
Without special changes, click “Next.”
This text file contains the data values separated by Tabs, so leave all options in default mode (i.e., delimited and “No” checked) and click “Next.”
Our data display shows the first case on line number 1, and that each line represents a case. Because we want all of the cases to be imported, do not apply changes and click “Next.”
Our data values are separated by Tabs, so click “Next.”
Here, you can specify the variable name and format by clicking each variable at the bottom of the window. Once you are done, click “Next” and then “Finish.” You have now successfully imported a text file into SPSS.
Importing an Excel file into SPSS is easier than importing a text file. Assume that the same data file was saved in Excel (Figure 4-36).
An Excel data file.A screenshot of an Excel file with an output displayed.
Courtesy of Microsoft Excel © Microsoft 2020.
Again, go to File > Open > Data. A new window, as presented in Figure 4-28, will appear. Once you locate where the file was saved, change “Files of Type” from *.sav to *.xls, *.xlsx, or *.xlsm to show all Excel files. Select ExcelFile.xlsx and click “Open” to open the file as we did with the text file. A new window, as presented in Figure 4-37, will appear. Click “OK” with the default option if the first row of the Excel file represents the variable name. It should successfully import the Excel file into the SPSS software. You may change to variable view as needed.
Opening an Excel file.A screenshot shows the opening of an Excel file in an I B M, S P S S, Statistics Editor.
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There are many other functions that a researcher can utilize to help with data analysis, but we will discuss these as needed when we explain different types of statistical analyses.
Excel is a part of Microsoft Office, and the most widely used spreadsheet software that supports a variety of analytical efforts, including data management and data-driven analytical techniques.
Using the Quick Access toolbar and Ribbon at the top of the screen, you can use various menus and commands that are designed to help you quickly access the commands you need to complete a task. Additionally, Excel provides numerous formulas and functions that allow you to quickly make specific calculations. Data can be directly entered into Excel, or different types of data files, such as text or CSV files, can be imported into Excel.
SPSS is a statistical software package that assists us in efficiently analyzing data to answer evidence-based practice and research questions, and it is one of the most widely used statistical software packages available.
There are three major file types in SPSS: data files, syntax files, and output files. Menus in SPSS are categorized into windows and general-purpose, data definition, and/or data analysis drop-down menus.
Entering data begins with defining variables in variable view. Then, a researcher creates a codebook that provides information about the variables in a data set. This should help a researcher with data entry.
Data can be either directly entered into SPSS, or different types of data files such as text or Excel files can be imported into SPSS.