SPSS INSTRUCTION CHAPTER 2 Using paper and pencil to draw frequency tables, crosstabulations, bar graphs and pie charts does not pose much difficulty with small sample sizes and minimal variables. However, in most cases, researchers have too much data to organize without the help of a statistical software program such as SPSS. Preparing Data in SPSS Obviously, before performing any sort of analysis in SPSS, the researcher must input his or her data into the Data View screen and enter relevant information into the Variable View screen as described in Chapter 1. Having done so, analyses can begin. An option in SPSS worthy of specific mention in the context of measurements of frequency is the recode function, which can separate values from a continuous variable into artificially-created categories. One would, thus, use this function to establish the salary categories used in Example 2.2 from the originally continuous salary data. Recoding data in SPSS requires the following steps. 1. Select Transform from the options as the top of the Data View screen or the Variable View screen. A pull-down menu should appear. 2. From the pull-down menu, select either Recode into Same Variables or Recode into Different Variables. The first of these options replaces the existing continuous values with codes for the user-defined categories. The second option generates a new variable that displays codes for the user-defined categories, leaving the raw data in tact. A small window, identified by the choice of recoding into the same or different variables, should appear. 3. An untitled box in the Recode into Same Variables or the Recode into Different Variables window contains the names of all variables for which data exists in the file. Indicate the variable to recode by clicking on its name and then clicking on the arrow to the right of the box. The name of the variable should disappear from its original location. a. If recoding into the same variable, the name of the variable should appear in the box labeled Numeric Variables.
FIGURE 2.11 SPSS RECODE INTO SAME VARIABLES WINDOW The placement of VAR00002 in the Numeric Variables box indicates the researchers desire to recode its values. The Old and New Values button allows the researcher to define the new categories. The codes for the will replace the original variable s values on the SPSS Data View page. (1) Click on the old and new values button below this box, to define the ranges for each category of data. In the box that appears, specify each range of raw values for each category on the left and then, on the right, assign a code to that category, clicking add after entering each code. (2) Upon competing the recoding process, click Continue to return to the Recode into Same Variable window. (3) Click OK. The newly-created variable should appear on the Data View page in place of the previously-existing variable. b. If recoding into different variables, the name of the variable, followed by a prompt for the user to supply a name for the newly-defined variable, appears in the box labeled Numeric Variable --> Output Variable. FIGURE 2.12 SPSS RECODE INTO DIFFERENT VARIABLES WINDOW
The placement of VAR00002 in the Numeric Variables box indicates the researchers desire to recode its values. The Old and New Values button allows the researcher to define the new categories. The codes for the new categories will appear in a new column on the SPSS Data View page. (1)To the right of the Numeric Variable -> Output Variable box, the user must supply a name for the newly-created variable. (2) Click on the old and new values button below this box to define the ranges for each category of data. In the box that appears, specify each range of raw values for each category on the left and then, on the right, assign a code to that category, clicking add after entering each code. (3) Upon competing the recoding process, click Continue to return to the Recode into Different Variable window. (4) Click Change. The newly-created variable should appear on the Data View page in the column farthest to the right on the page. 4. Enter the coding scheme for the newly-defined variable in the values window on the Variable View screen. After organizing data, the user instructs SPSS to perform the desired statistical calculations or create the desired table, graph, or chart. This resulting information appears on an output screen for which SPSS generates a separate file from the data file. Thus, one who wishes to save his or her output must remember to save both the data file, which generally has a.dat extension, and the output file, which generally had an.spo extension. Frequency Tables in SPSS SPSS can create tables displaying category names, frequencies, and percentages. To do so, the user must have entered the raw data into a column on the Data View screen and recoded if necessary. For coded variables, coding scheme should exist in the values window on the Variable View screen. Failure to enter the coding scheme results in output that contains numerical codes rather than category names. With data in place, the following steps instruct SPSS to create a frequency table. 1. Select Analyze from the options at the top of the Data View screen or the Variable View screen. A pull-down menu should appear. 2. From the pull-down menu, select Descriptive Statistics. A small window should appear to the right of the selection. 3. Select Frequencies from the options in the window. A new window, entitled Frequencies should appear.
FIGURE 2.13 SPSS FREQUENCIES WINDOW The user creates frequency tables by selecting appropriate variables from those listed in the window above. The statistics, charts, and format buttons provide options regarding the information included in the table and alternative forms of presenting the data. 4. An untitled box in the Frequencies window contains the names of all variables for which data exists in the file. Indicate the variable for which to create the frequency table by clicking on its name and then clicking the arrow to the right of the box. The name of the variable should disappear from its original location and appear in the box labeled Variable(s). To create frequency tables for multiple variables, use the same procedure with other variable names. 5. Click OK. The output contains a small chart, entitled, Statistics as well as one frequency table for each variable placed into the Variable(s) box in the Frequencies window. The statistics chart states the number of subjects who contributed data and the number with missing data for the analysis. Along with the frequencies, themselves, the frequency tables contain three percent values. The percent, itself, refers to the proportion all subjects who fall into a particular category. However, researchers generally have the most interest in the other two percentage values. The valid percent considers only the subjects who supplied data for the relevant variable in determining the proportion of subjects within each category. The cumulative percent, expresses an ongoing sum of the valid percents. Example 2.23 Frequency Table in SPSS All of these values appear in the following output. The first frequency table uses the categorical circus act data. The second table uses the artificially categorized salary groups. Statistics Act salary
N Valid 40 40 Missing 0 0 act Cumulative Frequency Percent Valid Percent Percent Valid Stunt 6 15.0 15.0 15.0 Clown 9 22.5 22.5 37.5 acrobatics/strength 9 22.5 22.5 60.0 Animal 5 12.5 12.5 72.5 Sideshow 9 22.5 22.5 95.0 Other 2 5.0 5.0 100.0 Total 40 100.0 100.0 salaries Valid $300-$449 $450-$599 $600-$749 $750-$899 900-$1049 Total Cumulativ e Frequency Percent Valid Percent Percent 3 7.5 7.5 7.5 10 25.0 25.0 32.5 14 35.0 35.0 67.5 12 30.0 30.0 97.5 1 2.5 2.5 100.0 40 100.0 100.0 TABLE 2.19, TABLE 2.20, AND TABLE 2.21 SPSS FREQUENCY TABLE Frequency table output always includes a Statistics summary table (Table 2.19), indicating the number of values included in the analysis and the number of missing values. Table 2.20 and Table 2.21 appear as a result of the user requesting frequency tables for act and salaries. The category names, appearing in the leftmost column of these tables use the terms entered into the values box on the Variable View screen. Because of the arbitrary order of the categories in Table 2.20, pertaining to circus act, the values in the cumulative percent column have little importance. However, the ascending order of categories Table 2.21, pertaining to salaries, makes the cumulative percents noteworthy. Using the cumulative percent column, one can easily determine the percent of subjects who earn less than those in a particular salary category and, by simply subtracting that value from 100%, the percent of subject who earn more than those in that category. Crosstabulations in SPSS Crosstabulations, essentially, divide values from a frequency table according to a second variable. Not surprisingly, then, the process of creating a crosstabulation in SPSS begins with the same steps as does the process of creating a frequency table. The crosstabulation is created with the following steps.
1. Select Analyze from the options at the top of the Data View screen or the Variable View screen. A pull-down menu should appear. 2. From the pull-down menu, select Descriptive Statistics. A small window should appear to the right of the selection. 3. Select Crosstabs from the options in the window. A new window, entitled Crosstabs should appear. FIGURE 2.14 SPSS CROSSTABULATIONS WINDOW The user creates a crosstabulation by selecting appropriate variables from those listed in the box above. The statistics, cells, and format buttons provide options regarding the information included in the crosstabulation and alternative forms of presenting the data. 4. An untitled box in the Crosstabs window contains the names of all variables in the file. Indicate the variable for which the categories should appear as rows in the crosstabulation by clicking on its name and then clicking on the arrow to the left of the box marked Rows". The comparable procedure indicates the variable for which categories should appear as columns. Use the Layers option for analyses with more than two variables. For each variable identified and moved, the name of the variable disappears from its original location and appears in the appropriate box. 5. To include percentages along with frequencies in the crosstabulation, click the cells button at the bottom of the Crosstabs window. The Cell Display window that appears includes a box in which the user can indicate whether he or she desires row, column, and total percentages. 6. Click OK.
If the user designates variables only into the row and column boxes, SPSS produces a relatively uncomplicated two-variable crosstabulation. By default, each cell contains the frequency for the appropriate combination of categories. Cells do not contain percents unless the user requests these values. (See Step 5 in the preceding directions.) Example 2.24 Basic Crosstabulation in SPSS Instructing SPSS to create a crosstabulation based upon circus performers acts and sexes, including row, column, and total percentages, results in the following table. sex * act Crosstabulation Act stunt Clown acrobatics/ strength animal sideshow other Total sex Male Count 2 4 5 3 5 1 20 % within sex 10.0% 20.0% 25.0% 15.0% 25.0% 5.0% 100.0% % within act 33.3% 44.4% 55.6% 60.0% 55.6% 50.0% 50.0% % of Total 5.0% 10.0% 12.5% 7.5% 12.5% 2.5% 50.0% female Count 4 5 4 2 4 1 20 % within sex 20.0% 25.0% 20.0% 10.0% 20.0% 5.0% 100.0% % within act 66.7% 55.6% 44.4% 40.0% 44.4% 50.0% 50.0% % of Total 10.0% 12.5% 10.0% 5.0% 10.0% 2.5% 50.0% Total Count 6 9 9 5 9 2 40 % within sex 15.0% 22.5% 22.5% 12.5% 22.5% 5.0% 100.0% % within act 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% % of Total 15.0% 22.5% 22.5% 12.5% 22.5% 5.0% 100.0% TABLE 2.22 SPSS TWO-VARIABLE CROSSTABULATION Each cell contains four values. The first value provides the frequency for the cell. The second value, refers to the particular cell s percentage within that row (sex). The third value refers to the particular cell s percentage within that column (act). The last value refers to that particular cell s percentage within the entire sample. Table 2.22 displays SPSS s version of Table 2.7. Of course, without the instruction to include percents within the cells, the crosstabulation would appear much less cumbersome than Table 2.22 does, looking similar to table 2.3. When the user enters a variable name into the layers box in the Crosstabs window, SPSS automatically nests rows of the crosstabulation within the layers. Once again, each cell contains the frequency for the appropriate combination of categories unless the user the user requests percentages. Example 2.25 Nested Crosstabulation in SPSS
The following nested crosstabulation below utilizes the same variables as and, accordingly, has a similar appearance to Table 2.10. As with Table 2.10, for the sake of simplicity, the table contains only frequencies. Interestingly, though, unlike Table 2.10, the crosstabulation created by SPSS does not display rows or columns that consistently have a frequency of 0. Thus, no row appears for the income category of $900-$1049 in the male layer of the following table. salaries * act * sex Crosstabulation Sex Act Total acrobatics/ stunt clown strength animal sideshow other stunt Male salaries $300-$449 0 0 0 0 1 0 1 $450-$599 0 0 1 0 3 1 5 $600-$749 0 4 2 2 0 0 8 $750-$899 2 0 2 1 1 0 6 Total 2 4 5 3 5 1 20 Female salaries $300-$449 0 1 0 0 1 0 2 $450-$599 0 2 0 0 3 0 5 $600-$749 2 2 2 0 0 0 6 $750-$899 2 0 2 2 0 0 6 900-$1049 0 0 0 0 0 1 1 Total 4 5 4 2 4 1 20 TABLE 2.23 SPSS NESTED CROSSTABULATION Categories of male and female appear as nested elements within each weekly salary category in the rows of the crosstabulation. Marginal values for each act category appear at the end of the respective column. Adding the values at the end of all rows marked female or male produces the marginal values for the respective sex category. Graphs and Charts in SPSS The most obvious method of creating graphs and charts in SPSS uses the Graphs option at the top of the Data View and Variable View pages. Choosing this option produces a pulldown menu containing the names of most graphs and charts available in the program. However, other methods can create the same illustrations. The process of creating the appropriate illustration varies based upon the graph or chart selected. One who wishes to create bar graphs and pie charts might notice that the Frequencies window provides users the option of including these illustrations with frequency table output. Doing so, the user need only click on the charts button located at the bottom of the page, then select the desired illustration and indicating whether it should display frequencies or percentages. This process, however, can only produce basic graphs and charts. One who wishes to produce nested or stacked illustrations should use the Graphs option described. To maintain consistency all directions for creating graphs provided in
this chapter involve the use of the Graphs option. The bar graphs and pie charts already provided in this chapter were created using this method. Bar Graphs Clicking on the Graphs option brings the names of three method of creating the graph to the screen. Although all of these methods eventually produce similar illustrations, some methods involve fewer steps than others do depending upon the particular graph desired. The last of the methods listed, Legacy Dialogues generally proves the simplest method of creating bar graphs. Beginning with the selection of this method, then, the following steps describe the process of creating a basic (one-variable) bar graph. 1. From the pull-down menu under the Graphs option at the top of the Data View or Variable View screen, select Legacy Dialogues. A listing of graphs and charts available through this method should appear. 2. Select Bar. A window entitled Bar Charts should appear. The Bar Charts window, by default, identifies a simple bar graph as the desired illustration and summaries for groups of cases as the data in the chart. 3. Click Define. A new window, entitled. Define Simple Bar: Summaries for Groups of Cases should appear. FIGURE 2.15 SPSS SIMPLE BAR GRAPH WINDOW
The user creates one-variable bar graph by selecting the appropriate variable from those listed in the box above. The designation in the Bars Represent portion of the window identifies the comparison factor used for the graph. 4. An untitled box in the Summaries for Groups of Cases window contains the names of all variables for which data exists in the file. Indicate the variable for which to create the bar graph by clicking on its name and then clicking on the arrow to the left of the box marked Category Axis". 5. Click OK. Example 2.26 Bar Graph in SPSS As mentioned, earlier portions of this chapter contain examples of SPSS-generated graphs and charts. Basic bar graphs pertaining to the variable of circus act and salary category appear as Figure 2.1 and Figure 2.2, respectively. Creating clustered and stacked bar graphs, require only small adjustments to the process for creating the basic bar graph. A description of the process for doing so follows. 1. From the pull-down menu under the option at the top of the Data View or Variable View screen, select Legacy Dialogues. A listing of graphs and charts available through this method should appear. 2. Select Bar. A window entitled Bar Charts should appear. 3. Change the default selection of simple in the Bar Charts window to clustered or stacked. Do not adjust the selection for data in the chart. 4. Click Define. A new window, entitled. Define Clustered Bar: Summaries for Groups of Cases or Define Stacked Bar: Summaries for Groups of Cases should appear.
FIGURE 2.16 SPSS CLUSTERED BAR GRAPH WINDOW The user creates clustered bar graph by selecting the appropriate variable from those listed in the box above. The designation in the Bars Represent portion of the window identifies the comparison factor used for the graph. The comparable box for a stacked bar graph appears identical to this one with the exception of the request to define stacks rather than to define clusters. 5. An untitled box in the Summaries for Groups of Cases window contains the names of all variables for which data exists in the file. a. Indicate the variable for which frequencies should appear as bars graph by clicking on its name and then clicking on the arrow to the left of the box marked Category Axis". b. Indicate the variable by which to separate the data by clicking on its name and then clicking on the arrow to the left of the box marked, Define Clusters by or Define Stacks by. 6. Click OK. Example 2.27 Clustered and Stacked Bar Graphs in SPSS In the case of the circus data, circus act determines the category axis and sex serves as the variable by which to define the clusters or stacks. Ordinarily SPSS distinguishes between
clusters by using different colors. However, Figure 2.3 and 2.4 utilize patterns rather than colors to visually exaggerate the distinction. Pie Charts Creation of a pie chart begins the same way as creating a bar graph does, by selecting the Legacy Dialogues option from the SPSS s Graphs menu. Steps for creating a basic (onevariable) follow. 1. From the pull-down menu under the Graphs option at the top of the Data View or Variable View screen, select Graphs. A listing of graphs and charts available through this method should appear. 2. Select Pie. A small window, asking the user to describe the data points appears. 3. Select Summaries for Groups of Cases and click Define. A window, entitled Define Pie: Summaries for Groups of Cases, should appear. FIGURE 2.17 SPSS DEFINE PIE: SUMMARIES OF GROUPS OF CASES WINDOW The user creates one-variable pie chart by selecting the appropriate variable from those listed in the box above. Clicking on the pies, titles, and options tabs allows for modifications to the chart s appearance.
4. An untitled box in the Define Pie: Summaries for Groups of Cases window contains the names of all variables for which data exists in the file. Indicate the variable for which to create the pie chart dragging its name to the box marked Define Slices by". 5. Click OK. Example 2.28 Basic Pie Chart in SPSS Figure 2.5 in this chapter contains the pie chart created using the preceding steps and based upon the variable of circus act. Ordinarily SPSS distinguishes between pie slices by using different colors. However, Figure 2.5 utilizes patterns rather than colors to visually exaggerate the distinction. To create a paneled pie chart, you also use the Define Pie: Summaries for Groups of Cases window. In addition to moving a variable name to the Define Slices by box, you must identify the categorical variable that serves as a basis for the panels. You should move the name of this variable to either the Rows or the Columns box in the Panel by portion of the window. If you use the Rows box, SPSS will arrange the pie charts vertically in its output. If you use the Columns box, the pie charts will appear horizontally in the SPSS output. Example 2.29 Paneled Pie Chart in SPSS Defining slices of the pie chart by circus act and paneling the data according to sex produces Figure 2.6 in this chapter. As in the basic pie chart, SPSS, unless directed otherwise, distinguishes between pie slices by using different colors. The patterns used in Figure 2.6 merely serve to visually exaggerate this distinction.