IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA


 Emily Lewis
 6 years ago
 Views:
Transcription
1 CALIFORNIA STATE UNIVERSITY, LOS ANGELES INFORMATION TECHNOLOGY SERVICES IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA Summer 2013, Version 2.0 Table of Contents Introduction...2 Downloading the Data Files...2 ChiSquare...2 ChiSquare Test for GoodnessofFit...2 With Fixed Expected Values...2 With Fixed Expected Values and within a Contiguous Subset of Values...4 With Customized Expected Values...5 OneWay Analysis of Variance...7 Post Hoc Tests...9 TwoWay Analysis of Variance...11 Importing and Exporting Data...14 Using Scripting for Redundant Statistical Analyses...17 For additional handouts, visit For video tutorials, visit
2 Introduction SPSS stands for Statistical Package for the Social Sciences. This program can be used to analyze data collected from surveys, tests, observations, etc. It can perform a variety of data analyses and presentation functions, including statistical analysis and graphical presentation of data. Among its features are modules for statistical data analysis. These include (1) descriptive statistics, such as frequencies, central tendency, plots, charts and lists; and (2) sophisticated inferential and multivariate statistical procedures, such as analysis of variance (ANOVA), factor analysis, cluster analysis, and categorical data analysis. IBM SPSS Statistics 20 is wellsuited for survey research, though by no means is it limited to just this topic of exploration. This handout introduces basic skills for performing hypothesis tests utilizing ChiSquare test for GoodnessofFit and generalized pooled t tests, such as ANOVA. The stepbystep instructions will guide users in performing tests of significance using SPSS Statistics and will help users understand how to interpret the output for research questions. Downloading the Data Files This handout includes sample data files that can be used for handson practice. The data files are stored in a selfextracting archive. The archive must be downloaded and executed in order to extract the data files. The data files used with this handout are available for download at Instructions on how to download and extract the data files are available at ChiSquare The ChiSquare (χ2) test is a statistical tool used to examine differences between nominal or categorical variables. The ChiSquare test is used in two similar but distinct circumstances: To estimate how closely an observed distribution matches an expected distribution also known as the GoodnessofFit test. To determine whether two random variables are independent. ChiSquare Test for GoodnessofFit This procedure can be used to perform a hypothesis test about the distribution of a qualitative (categorical) variable or a discrete quantitative variable having only finite possible values. It analyzes whether the observed frequency distribution of a categorical or nominal variable is consistent with the expected frequency distribution. With Fixed Expected Values Research Question # 1 Can the hospital schedule discharge support staff evenly throughout the week? A large hospital schedules discharge support staff assuming that patients leave the hospital at a fairly constant rate throughout the week. However, because of increasing complaints of staff shortages, the hospital administration wants to determine whether the number of discharges varies by the day of the week. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 2
3 H 0 : Patients leave the hospital at a constant rate (there is no difference between the discharge rates for each day of the week). H 1 : Patients do not leave the hospital at a constant rate. To perform the analysis: 1. Start IBM SPSS Statistics Click the Open button on the Data Editor toolbar. The Open Data dialog box opens. 3. Navigate to the Data Files folder, select the Chihospital.sav file, and then click the Open button. The observed values must be declared before running the ChiSquare test. To declare the observed values: 1. Click the Data menu, and then click Weight Cases. The Weight Cases dialog box opens (see Figure 1). 2. Select the Weight cases by option. 3. Select the Average Daily Discharges [discharge] variable in the box on the left, and then click the transfer arrow button to move it to the Frequency Variable box. 4. Click the OK button. Figure 1 Weight Cases Dialog Box To perform the analysis: 1. Click the Analyze menu, point to Nonparametric Tests, point to Legacy Dialogs, and then click Chisquare. The Chisquare Test dialog box opens. 2. Select the Day of the Week [dow] variable and move it to the Test Variable List box (see Figure 2). 3. Click the OK button. The Output Viewer window opens (see Figure 3). Figure 2 Chisquare Test Dialog Box IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 3
4 Figure 3 ChiSquare Frequencies Output Table Figure 4 ChiSquare Test Statistics Output Table Reporting the analysis results: H 0 : Rejected in favor of H 1. H 1 : Patients do not leave the hospital at a constant rate. Explanation: Figure 4 indicates that the calculated χ 2 statistic, for 6 degrees of freedom, is Additionally, it indicates that the significance value (0.000) is less than the usual threshold value of This suggests that the null hypothesis, H 0 (patients leave the hospital at a constant rate), can be rejected in favor of the alternate hypothesis, H 1 (patients leave the hospital at different rates during the week). With Fixed Expected Values and within a Contiguous Subset of Values By default, the ChiSquare test procedure builds frequencies and calculates an expected value based on all valid values of the test variable in the data file. However, it may be desirable to restrict the test s range to a contiguous subset of the available values, such as weekdays only (Monday through Friday). Research Question # 2 The hospital requests a followup analysis. Can staff be scheduled assuming that patients discharged on weekdays only (Monday through Friday) leave at a constant daily rate? H 0 : Patients discharged on weekdays only (Monday through Friday) leave at a constant daily rate. H 1 : Patients discharged on weekdays only (Monday through Friday) do not leave at a constant daily rate. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 4
5 To run the analysis: 1. Click the Analyze menu, point to Nonparametric Tests, point to Legacy Dialogs, and then click Chisquare. The Chisquare Test dialog box opens. 2. Select the Use specified range option in the Expected Range section (see Figure 2). 3. Type 2 in the Lower box and 6 in the Upper box. 4. Click the OK button. The Output Viewer window opens (see Figure 5 and Figure 6). Notice that the test range is restricted to Monday through Friday. Figure 6 Test Statistics Output Table Figure 5 ChiSquare (Subset) Frequencies Output Table NOTE: The expected values are equal to the sum of the observed values divided by the number of rows, while the observed values are the actual number of patients discharged. Reporting the analysis results: H 0 : Do not reject. Patients discharged on weekdays only (Monday through Friday) leave at a constant daily rate. Explanation: Figure 5 indicates that, on average, 92 patients were discharged from the hospital each weekday. The rate for Mondays was below average and the rate for Fridays was above average. Figure 6 indicates that the calculated value of the ChiSquare statistic was at 4 degrees of freedom. Because the significance level (0.213) is greater than the rejection threshold of 0.05, H 0 (patients were discharged at a constant rate on weekdays) could not be rejected. Using the ChiSquare test procedure, the hospital determined that the patient discharge rate was not constant over the course of an average week. This was primarily due to more discharges on Fridays and fewer discharges on Sundays. When the test s range was restricted to weekdays, the discharge rates appeared to be more uniform. Staff shortages could be corrected by adopting separate weekday and weekend staff schedules. With Customized Expected Values Research Question # 3 Does firstclass mailing provide quicker response time than bulk mail? A manufacturing company tries firstclass postage for direct mailings, hoping for faster responses than with bulk mail. Order takers record how many weeks each order takes after mailing. H 0 : Firstclass and bulk mailings do not result in different customer response times. H 1 : Firstclass and bulk mailings result in different customer response times. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 5
6 Before the ChiSquare test is run, the cases must be weighted. Because this example compares two different methods, one method must be selected to provide the expected values for the test and the other will provide the observed values. To weight the cases: 1. Open the Chimail.sav file. 2. Click the Data menu, and then click Weight Cases. The Weight Cases dialog box opens. 3. Select the Weight cases by option. 4. Select the First Class Mail [fcmail] variable and move it to the Frequency Variable box. 5. Click the OK button. To run the analysis: 1. Click the Analyze menu, point to Nonparametric Tests, point to Legacy Dialogs, and then click Chisquare. The Chisquare Test dialog box opens. 2. Select the Week of Response [week] variable and move it to the Test Variable List box. 3. Select the Values option in the Expected Values section. 4. Type 6 in the Values box, and then click the Add button. 5. Repeat step 4, adding the values 15.1, 18, 12, 11.5, 9.8, 7, 6.1, 5.5, 3.9, 2.1, and 2 (in that order). 6. Click the OK button. The Output Viewer window opens. NOTE: The expected frequencies in this example are the response percentages that the firm has historically obtained with bulk mail. Figure 8 Week of Response Test Statistics Figure 7 FirstClass/Bulk Mail Week of Response Reporting the analysis results: H 0 : Do not reject. There was no statistical difference between customer response times using firstclass mailing and customer response times using bulk mailing. Explanation: The manufacturing company hoped that firstclass mail would result in quicker customer response. As indicated in Figure 7, the first two weeks indicated different response times of four and seven percentage points, respectively. The question was whether the overall differences between the two distributions were statistically significant. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 6
7 The ChiSquare statistic was calculated to be at 11 degrees of freedom (see Figure 8). The significance value (p) associated with the data was 0.345, which was greater than the threshold value of Hence, H 0 was not rejected because there was no significant difference between firstclass and bulk mailings. The firstclass mail promotion did not result in response times that were statistically different from standard bulk mail. Therefore, bulk postage was more economical for direct mailings. OneWay Analysis of Variance Oneway analysis of variance (OneWay ANOVA) procedures produce an analysis for a quantitative dependent variable affected by a single factor (independent variable). Analysis of variance is used to test the hypothesis that several means are equal. This technique is an extension of the twosample t test. Think of it as a generalization of the pooled t test. Instead of two populations (as in the case of a t test), there are more than two populations or treatments. Research Question # 4 Which of the alloys tested would be appropriate for creating an underwater sensor array? To find the best alloy for an underwater sensor array, four different types are tested for resistance to corrosion. Five plates of each alloy are submerged for 60 days after which the number of corrosive pits on each plate is measured. H 0 : The four alloys exhibit the same kind of behavior and are not different from one another. H 1 : The four alloys exhibit different kind of behaviors and are different from one another. To run OneWay ANOVA: 1. Open the Alloy.sav file. NOTE: Each case within the OneWay ANOVA data file represents one of the 20 metal plates (5 plates of 4 different alloys) and is characterized by 2 variables. One variable assigns a numeric value to the alloy. The other variable is used to quantify the number of pits on the plate after being underwater for 60 days (see Figure 9). Figure 9 Alloy Data File 2. In Data View, click the Analyze menu, point to Compare Means, and then click One Way ANOVA. The OneWay ANOVA dialog box opens. 3. Select the pits variable in the box on the left and move it to the Dependent List box. 4. Select the Alloy [alloy] variable in the box on the left and move it to the Factor box (see Figure 10). IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 7
8 Figure 10 OneWay ANOVA Dialog Box 5. Click the Options button. The OneWay ANOVA: Options dialog box opens. 6. Select the Descriptive, Homogeneity of variance test, and Means plot check boxes (see Figure 11). 7. Click the Continue button. Figure 11 OneWay ANOVA: Options Dialog Box 8. Click the OK button. The Output Viewer window opens. Figure 12 ANOVA Descriptive Output Figure 13 Output for Test of Homogeneity of Variances IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 8
9 Figure 14 ANOVA Output Reporting the analysis results: H 0 : Reject in favor of H 1. H 1 : The four alloys do not exhibit the same kind of behavior. They are statistically different from one another. Explanation: Figure 12 lists the means, standard deviations, and individual sample sizes of each alloy. Figure 13 provides the degrees of freedom and the significance level of the population; df1 is one less than the number of sample alloys (41=3), and df2 is the difference between the total sample size and the number of sample alloys (204=16). Figure 14 lists the sum of the squares of the differences between means of different alloy populations and their mean square errors. In Figure 14, the Between Groups variation is due to interaction in samples between groups. If sample means are close to each other, this value is small. The Within Groups variation is due to differences within individual samples. The Mean Square values are calculated by dividing each Sum of Squares value by its respective degree of freedom (df). The table also lists the F statistic , which is calculated by dividing the Between Groups Mean Square by the Within Groups Mean Square. The significance level of is less than the threshold value of 0.05 indicating that the null hypothesis can be rejected. In conclusion, the alloys are not all the same. Post Hoc Tests In ANOVA, if the null hypothesis is rejected, then it is concluded that there are differences between the means (μ 1, μ 2,, μ a ). It is useful to know specifically where these differences exist. Post hoc testing identifies these differences. Multiple comparison procedures look at all possible pairs of means and determine if each individual pairing is the same or statistically different. In an ANOVA with α treatments, there will be α*(α1)/2 possible unique pairings, which could mean a large number of comparisons. Research Question # 5 Is the mean difference between alloy sets statistically significant? The rejection of the previous null hypothesis leads to the conclusion that all the alloys do not exhibit the same behavior. The next part of the analysis determines if the mean difference between individual alloy sets is statistically significant. H 0 : μ 0 = μ 1 = μ a H 1 : μ 0 μ 1 μ a To run post hoc tests: 1. In Data View, click the Analyze menu, point to Compare Means, and then click One Way ANOVA. The OneWay ANOVA dialog box opens (see Figure 15). IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 9
10 Figure 15 OneWay ANOVA Dialog Box 2. Click the Post Hoc button. The OneWay ANOVA: Post Hoc Multiple Comparisons dialog box opens. 3. Select the LSD check box (see Figure 16). 4. Click the Continue button, and then click the OK button. The Output Viewer window opens. NOTE: LSD stands for List Significant Difference, which compares the means one by one. Figure 16 OneWay ANOVA: Post Hoc Multiple Comparisons Dialog Box Figure 17 Multiple Comparisons Output IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 10
11 Reporting the analysis results: H 0 : Reject in favor of H 1. H 1 : At least one of the means is different. Figure 18 Means Plot Explanation: Figure 17 shows the results of comparing pairs of means between different alloy sets. Each row indicates the difference between the two corresponding treatments. Alloys 1 and 4 have a mean difference of 2.4 (a relatively small value). Also, the significance level of indicates that the null hypothesis cannot be rejected for the comparison of alloys 1 and 4. There is no statistically significant difference between them. Alloy pairs 1 and 2, 1 and 3, 2 and 3, 2 and 4, and 3 and 4 have large mean differences with significance values of In these cases, the null hypothesis can be rejected, leading to the conclusion that they are statistically different. Also, the means plot (see Figure 18) shows that alloys 1 and 4 have average mean values of pits very close to each other. Because alloys 1 and 4 have the lowest mean number of corrosive pits, they are the best choices for the array. Depending on the relative costs of the two alloys, the one that is more cost effective can be chosen. TwoWay Analysis of Variance Twoway analysis of variance (TwoWay ANOVA) is an extension of the oneway analysis of variance. With TwoWay ANOVA, two or more independent variables can be tested instead of just one. Using multiple variables has two advantages: increased efficiency and an increase in the result s statistical power. Research Question # 6 Will test anxiety and different teachers affect student test scores? To answer the question, two classes were given a cumulative standardized test. Before the test, students were asked about the level of anxiety they were feeling: none, some and lots. The experiment compared two different classes taught by teachers A and B using the same test. After evaluating the standardized test, each group s mean score was examined. H 0 : Test anxiety and teacher do not affect student test scores. H 1 : Test anxiety and teacher do affect student test scores. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 11
12 To run TwoWay ANOVA: 1. Open the TwoWayANOVA.sav file (see Figure 19). Figure 19 TwoWay ANOVA Data File 2. In Data View, click the Analyze menu, point to General Linear Model, and then click Univariate (see Figure 20). The Univariate dialog box opens. 3. Select the SCORE variable in the box on the left and move it to the Dependent Variable box. 4. Select the ANXIETY and TEACHER variables in the box on the left and move them to the Fixed Factor(s) box (see Figure 21). Figure 20 Analyze Menu When Selecting Univariate Figure 21 Univariate Dialog Box 5. Click the Options button. The Univariate: Options dialog box opens. 6. Select the Descriptive statistics check box, and then click the Continue button (see Figure 22). 7. Click the OK button. The Output Viewer window opens (see Figure 23 and Figure 24). IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 12
13 Figure 22 Univariate: Options Dialog Box Figure 23 ANOVA Descriptive Output Table Figure 24 Output Table for Tests of BetweenSubjects Effects IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 13
14 Reporting the analysis results: H 0 : Reject in favor of H 1 for Anxiety and the interaction between Anxiety and Teacher (Anxiety*Teacher). H 1 : Testing anxiety and teacher affect student test scores. Explanation: Figure 23 lists the means and standard deviations from three anxieties in two classes. Students who have some testing anxiety and are in Teacher B s class have the highest mean score (mean=36.67). Because the significance value of the Teacher variable (0.901) is more than the threshold value (0.05) as indicated in Figure 24, it can be concluded that the Teacher factor alone does not affect test scores. The significance values of the Testing Anxiety variable (0.033) and the interaction between the two factors Anxiety*Teacher (0.047) are less than the threshold value (0.05), leading to the conclusion that both Testing Anxiety alone and the combination of Testing Anxiety and Teacher (Anxiety*Teacher) do affect student test scores. Importing and Exporting Data SPSS Statistics can be used to analyze data in a Microsoft Excel spreadsheet. SPSS Statistics provides the ability to import an Excel spreadsheet directly into the Data Editor window and automatically create variables based on the spreadsheet s column headings. Data can also be exported from SPSS Statistics into Microsoft Excel and PowerPoint. To import an Excel spreadsheet into SPSS Statistics: 1. Click the Open button on the Data Editor toolbar. The Open Data dialog box opens. 2. Click the Files of type arrow and select Excel (*.xls, *.xlsx, *.xlsm) from the list. 3. Select the demo.xls file, and then click the Open button (see Figure 25). The Opening Excel Data Source dialog box opens (see Figure 26). NOTE: If the Excel file contains multiple worksheets, select the desired worksheet by clicking the Worksheet arrow (see Figure 26). To import a specific range of cells, specify the range in the Range box. Figure 26 Opening Excel Data Source Dialog Box Figure 25 Open Data Dialog Box 4. Click the OK button. SPSS Statistics processes and reads the Excel file and converts all first row column headings into variables using the best approximation for the variable attributes (see Figure 27 and Figure 28). IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 14
15 Figure 27 Excel File Figure 28 Excel File Imported into SPSS Statistics The reverse situation may also arise, where data in an SPSS Statistics file must be analyzed using Excel. This can be accomplished by exporting the contents of the Data Editor window into an Excel spreadsheet. To export SPSS Statistics data into an Excel spreadsheet: 1. In the Data Editor window, click the File menu, and then click Save As. The Save Data As dialog box opens. 2. Click the Save as type arrow and select Excel 97 through 2003 (*.xls) or Excel 2007 through 2010 (*.xlsx) from the list (see Figure 29). NOTE: Selecting the Write variable names to spreadsheet check box will cause SPSS Statistics to write the variable names as column headings in the spreadsheet. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 15
16 NOTE: If only certain variables from the Data Editor window are desired in the spreadsheet, users can click the Variables button and select or deselect variables in the Save Data As: Variables dialog box (see Figure 30). Figure 29 Save Data As Dialog Box Figure 30 Save Data As: Variables Dialog Box 3. Click the Look in arrow and select a location to save the file. 4. Type a name for the Excel file in the File name box. 5. Click the Save button. The Output Viewer window opens with a report summarizing the details and results of the export operation (see Figure 31). Figure 31 SPSS Statistics Export Output Report To export an SPSS Statistics Output chart into a PowerPoint slide: 1. In the Output Viewer window, click to select the table. A box appears around the table and a red arrow to the left of it. 2. Click the File menu, and then click Export. The Export Output dialog box opens. 3. Click the Type arrow and select PowerPoint (*.ppt) from the list (see Figure 32). 4. Click the Browse button. The Save File dialog box opens. 5. Click the Look in arrow and select a location to save the file. 6. Type a name for the PowerPoint file in the File name box (see Figure 33). 7. Click the Save button. 8. Click the OK button. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 16
17 Figure 32 Export Output Dialog Box Figure 33 Save File Dialog Box Using Scripting for Redundant Statistical Analyses Every statistical analysis used by SPSS Statistics is executed through a special programming language. The code used for each analysis can be captured, stored as a script file, and edited if necessary. A series of scripts in a script file can be run either individually or all at once. Scripting automates a series of statistical analyses that are performed on a file that always has the same variables, but contains data that changes. Scripts are captured and edited in the IBM SPSS Statistics Syntax Editor window. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 17
18 The following example illustrates the benefits of capturing, storing and running scripts. The sample data is taken from a classroom setting for a weeklong course. At the end of each week, each student s data is compiled. The variables in the set include the subject name, gender, pretest scores, posttest scores, grade point average, computer ownership, and method of administering examinations. Each week, a report is generated that answers a series of questions about the class from the previous week. The questions answered and the statistical analyses used are the same every week, as described in Table 1. Table 1 Scripted Questions and Statistical Techniques Question Does the data set include equal numbers of each gender and each test method? Is there a difference between the male and female pretest scores? Is there a difference between the male and female posttest scores? Is there a difference between the overall pretest and posttest scores? Do gender, computer ownership, and test method affect test scores? Do gender, computer ownership, and test method affect test scores differently depending on gender? Is there a linear relationship between the pretest and posttest scores for each gender? Can pretest scores predict posttest scores for each gender? Is there an overall linear relationship between pretest and posttest scores? Can pretest scores predict posttest scores? Statistical Technique(s) to Answer Question Split the file Crosstabs Select all cases IndependentSamples T Test IndependentSamples T Test PairedSamples T Test ThreeWay ANOVA Split the file TwoWay ANOVA Scatter plot graph with file split Simple regression with file split Select all cases Scatter plot graph Simple regression To construct a script file that will automatically run the analyses: 1. Open the ClassData.sav file. 2. Click the Edit menu, and then click Options. The Options dialog box opens. 3. Click the Viewer tab, select the Display commands in the log check box, click the Apply button, and then click the OK button (see Figure 34). NOTE: The script file is built by performing each statistical analysis in the desired order. All analyses must be performed manually one time while the file is being built. In this example, the file will first be split before creating a crosstabs table. 4. Click the Data menu, and then click Split File. The Split File dialog box opens. 5. Select the Compare groups option, and then move the gender variable to the Groups Based on box. 6. Click the Paste button to add the command to the script file. The Split File dialog box closes and the IBM SPSS Statistics Syntax Editor window opens with the pasted command displayed (see Figure 35). 7. In the IBM SPSS Statistics Data Editor window, click the Analyze menu, point to Descriptive Statistics, and then click Crosstabs. The Crosstabs dialog box opens. IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 18
19 Figure 35 IBM SPSS Statistics Syntax Editor Window Figure 34 Options Dialog Box 8. Move the gender variable to the Row(s) box and the method variable to the Column(s) box. 9. Click the Paste button. The Crosstabs dialog box closes and the command is pasted in the IBM SPSS Statistics Syntax Editor window (see Figure 36). The first question in Table 1 has been entered into the script file. NOTE: Scripts for each of the remaining analytical techniques can be entered into the script file by choosing the desired parameters in each dialog box, and then clicking the Paste button. Figure 36 IBM SPSS Statistics Syntax Editor Window Figure 37 Save Syntax As Dialog Box 10. To save the script file, click the File menu in the IBM SPSS Statistic Syntax Editor window, and then click Save As. The Save Syntax As dialog box opens (see Figure 37). 11. Select a location to save the file, enter a file name, and then click the Save button. SPSS Statistics script files have the.sps file extension. The program provides several options for running script files. The Run menu of the IBM SPSS Statistic Syntax Editor window contains commands for All, Selection, and To End (see Figure 39). IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 19
20 To run an existing script file: 1. In the Data Editor window, click the File menu, point to Open, and then click Syntax (see Figure 38). The Open Syntax dialog box opens. 2. Locate and select the WeeklyAnalysis.sps syntax file, and then click the Open button. The IBM SPSS Statistics Syntax Editor window opens with the script displayed. 3. In the IBM SPSS Statistics Syntax Editor window, click the Run menu, and then click All (see Figure 39). Every command in the script file is executed and the results are displayed in the Output Viewer window. NOTE: If the Display commands in the log check box on the Viewer tab of the Options dialog box remains selected, individual script commands will appear with the output in the Output Viewer window. Figure 38 File Menu When Selecting Syntax Figure 39 Run (Syntax) Menu IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA 20
IBM SPSS Statistics 20 Part 1: Descriptive Statistics
CALIFORNIA STATE UNIVERSITY, LOS ANGELES INFORMATION TECHNOLOGY SERVICES IBM SPSS Statistics 20 Part 1: Descriptive Statistics Summer 2013, Version 2.0 Table of Contents Introduction...2 Downloading the
More informationSPSS Tests for Versions 9 to 13
SPSS Tests for Versions 9 to 13 Chapter 2 Descriptive Statistic (including median) Choose Analyze Descriptive statistics Frequencies... Click on variable(s) then press to move to into Variable(s): list
More informationJanuary 26, 2009 The Faculty Center for Teaching and Learning
THE BASICS OF DATA MANAGEMENT AND ANALYSIS A USER GUIDE January 26, 2009 The Faculty Center for Teaching and Learning THE BASICS OF DATA MANAGEMENT AND ANALYSIS Table of Contents Table of Contents... i
More informationDirections for using SPSS
Directions for using SPSS Table of Contents Connecting and Working with Files 1. Accessing SPSS... 2 2. Transferring Files to N:\drive or your computer... 3 3. Importing Data from Another File Format...
More informationIBM SPSS Statistics for Beginners for Windows
ISS, NEWCASTLE UNIVERSITY IBM SPSS Statistics for Beginners for Windows A Training Manual for Beginners Dr. S. T. Kometa A Training Manual for Beginners Contents 1 Aims and Objectives... 3 1.1 Learning
More informationChapter 5 Analysis of variance SPSS Analysis of variance
Chapter 5 Analysis of variance SPSS Analysis of variance Data file used: gss.sav How to get there: Analyze Compare Means Oneway ANOVA To test the null hypothesis that several population means are equal,
More informationAn introduction to IBM SPSS Statistics
An introduction to IBM SPSS Statistics Contents 1 Introduction... 1 2 Entering your data... 2 3 Preparing your data for analysis... 10 4 Exploring your data: univariate analysis... 14 5 Generating descriptive
More informationStatistical Analysis Using SPSS for Windows Getting Started (Ver. 2014/11/6) The numbers of figures in the SPSS_screenshot.pptx are shown in red.
Statistical Analysis Using SPSS for Windows Getting Started (Ver. 2014/11/6) The numbers of figures in the SPSS_screenshot.pptx are shown in red. 1. How to display English messages from IBM SPSS Statistics
More informationSPSS Introduction. Yi Li
SPSS Introduction Yi Li Note: The report is based on the websites below http://glimo.vub.ac.be/downloads/eng_spss_basic.pdf http://academic.udayton.edu/gregelvers/psy216/spss http://www.nursing.ucdenver.edu/pdf/factoranalysishowto.pdf
More informationData Analysis in SPSS. February 21, 2004. If you wish to cite the contents of this document, the APA reference for them would be
Data Analysis in SPSS Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 354870348 Heather Claypool Department of Psychology Miami University
More informationOneWay ANOVA using SPSS 11.0. SPSS ANOVA procedures found in the Compare Means analyses. Specifically, we demonstrate
1 OneWay ANOVA using SPSS 11.0 This section covers steps for testing the difference between three or more group means using the SPSS ANOVA procedures found in the Compare Means analyses. Specifically,
More informationBusiness Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.
Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGrawHill/Irwin, 2008, ISBN: 9780073319889. Required Computing
More informationSPSS Explore procedure
SPSS Explore procedure One useful function in SPSS is the Explore procedure, which will produce histograms, boxplots, stemandleaf plots and extensive descriptive statistics. To run the Explore procedure,
More informationUsing SPSS, Chapter 2: Descriptive Statistics
1 Using SPSS, Chapter 2: Descriptive Statistics Chapters 2.1 & 2.2 Descriptive Statistics 2 Mean, Standard Deviation, Variance, Range, Minimum, Maximum 2 Mean, Median, Mode, Standard Deviation, Variance,
More informationData analysis process
Data analysis process Data collection and preparation Collect data Prepare codebook Set up structure of data Enter data Screen data for errors Exploration of data Descriptive Statistics Graphs Analysis
More informationSPSS Manual for Introductory Applied Statistics: A Variable Approach
SPSS Manual for Introductory Applied Statistics: A Variable Approach John Gabrosek Department of Statistics Grand Valley State University Allendale, MI USA August 2013 2 Copyright 2013 John Gabrosek. All
More informationSPSS Resources. 1. See website (readings) for SPSS tutorial & Stats handout
Analyzing Data SPSS Resources 1. See website (readings) for SPSS tutorial & Stats handout Don t have your own copy of SPSS? 1. Use the libraries to analyze your data 2. Download a trial version of SPSS
More informationCourse Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics
Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGrawHill/Irwin, 2010, ISBN: 9780077384470 [This
More informationData exploration with Microsoft Excel: analysing more than one variable
Data exploration with Microsoft Excel: analysing more than one variable Contents 1 Introduction... 1 2 Comparing different groups or different variables... 2 3 Exploring the association between categorical
More informationIntroduction to SPSS 16.0
Introduction to SPSS 16.0 Edited by Emily Blumenthal Center for Social Science Computation and Research 110 Savery Hall University of Washington Seattle, WA 98195 USA (206) 5438110 November 2010 http://julius.csscr.washington.edu/pdf/spss.pdf
More informationAn introduction to using Microsoft Excel for quantitative data analysis
Contents An introduction to using Microsoft Excel for quantitative data analysis 1 Introduction... 1 2 Why use Excel?... 2 3 Quantitative data analysis tools in Excel... 3 4 Entering your data... 6 5 Preparing
More informationIntroduction to Regression and Data Analysis
Statlab Workshop Introduction to Regression and Data Analysis with Dan Campbell and Sherlock Campbell October 28, 2008 I. The basics A. Types of variables Your variables may take several forms, and it
More informationBill Burton Albert Einstein College of Medicine william.burton@einstein.yu.edu April 28, 2014 EERS: Managing the Tension Between Rigor and Resources 1
Bill Burton Albert Einstein College of Medicine william.burton@einstein.yu.edu April 28, 2014 EERS: Managing the Tension Between Rigor and Resources 1 Calculate counts, means, and standard deviations Produce
More informationCreate Custom Tables in No Time
SPSS Custom Tables 17.0 Create Custom Tables in No Time Easily analyze and communicate your results with SPSS Custom Tables, an addon module for the SPSS Statistics product line Share analytical results
More informationGetting Started With SPSS
Getting Started With SPSS To investigate the research questions posed in each section of this site, we ll be using SPSS, an IBM computer software package specifically designed for use in the social sciences.
More informationAn Introduction to SPSS. Workshop Session conducted by: Dr. Cyndi Garvan GraceAnne Jackman
An Introduction to SPSS Workshop Session conducted by: Dr. Cyndi Garvan GraceAnne Jackman Topics to be Covered Starting and Entering SPSS Main Features of SPSS Entering and Saving Data in SPSS Importing
More informationIntroduction to PASW Statistics 34152001
Introduction to PASW Statistics 34152001 V18 02/2010 nm/jdr/mr For more information about SPSS Inc., an IBM Company software products, please visit our Web site at http://www.spss.com or contact: SPSS
More informationIntroduction Course in SPSS  Evening 1
ETH Zürich Seminar für Statistik Introduction Course in SPSS  Evening 1 Seminar für Statistik, ETH Zürich All data used during the course can be downloaded from the following ftp server: ftp://stat.ethz.ch/u/sfs/spsskurs/
More information4. Descriptive Statistics: Measures of Variability and Central Tendency
4. Descriptive Statistics: Measures of Variability and Central Tendency Objectives Calculate descriptive for continuous and categorical data Edit output tables Although measures of central tendency and
More informationExcel Charts & Graphs
MAX 201 Spring 2008 Assignment #6: Charts & Graphs; Modifying Data Due at the beginning of class on March 18 th Introduction This assignment introduces the charting and graphing capabilities of SPSS and
More informationCan SAS Enterprise Guide do all of that, with no programming required? Yes, it can.
SAS Enterprise Guide for Educational Researchers: Data Import to Publication without Programming AnnMaria De Mars, University of Southern California, Los Angeles, CA ABSTRACT In this workshop, participants
More informationKSTAT MINIMANUAL. Decision Sciences 434 Kellogg Graduate School of Management
KSTAT MINIMANUAL Decision Sciences 434 Kellogg Graduate School of Management Kstat is a set of macros added to Excel and it will enable you to do the statistics required for this course very easily. To
More informationTesting Group Differences using Ttests, ANOVA, and Nonparametric Measures
Testing Group Differences using Ttests, ANOVA, and Nonparametric Measures Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 354870348 Phone:
More informationBowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition
Bowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition Online Learning Centre Technology StepbyStep  Excel Microsoft Excel is a spreadsheet software application
More informationSimple Predictive Analytics Curtis Seare
Using Excel to Solve Business Problems: Simple Predictive Analytics Curtis Seare Copyright: Vault Analytics July 2010 Contents Section I: Background Information Why use Predictive Analytics? How to use
More informationSAS Analyst for Windows Tutorial
Updated: August 2012 Table of Contents Section 1: Introduction... 3 1.1 About this Document... 3 1.2 Introduction to Version 8 of SAS... 3 Section 2: An Overview of SAS V.8 for Windows... 3 2.1 Navigating
More informationSAS AddIn 2.1 for Microsoft Office: Getting Started with Data Analysis
SAS AddIn 2.1 for Microsoft Office: Getting Started with Data Analysis The correct bibliographic citation for this manual is as follows: SAS Institute Inc. 2007. SAS AddIn 2.1 for Microsoft Office: Getting
More informationSPSS: Getting Started. For Windows
For Windows Updated: August 2012 Table of Contents Section 1: Overview... 3 1.1 Introduction to SPSS Tutorials... 3 1.2 Introduction to SPSS... 3 1.3 Overview of SPSS for Windows... 3 Section 2: Entering
More informationThere are six different windows that can be opened when using SPSS. The following will give a description of each of them.
SPSS Basics Tutorial 1: SPSS Windows There are six different windows that can be opened when using SPSS. The following will give a description of each of them. The Data Editor The Data Editor is a spreadsheet
More informationData Analysis Tools. Tools for Summarizing Data
Data Analysis Tools This section of the notes is meant to introduce you to many of the tools that are provided by Excel under the Tools/Data Analysis menu item. If your computer does not have that tool
More informationData Analysis. Using Excel. Jeffrey L. Rummel. BBA Seminar. Data in Excel. Excel Calculations of Descriptive Statistics. Single Variable Graphs
Using Excel Jeffrey L. Rummel Emory University Goizueta Business School BBA Seminar Jeffrey L. Rummel BBA Seminar 1 / 54 Excel Calculations of Descriptive Statistics Single Variable Graphs Relationships
More informationTutorial for proteome data analysis using the Perseus software platform
Tutorial for proteome data analysis using the Perseus software platform Laboratory of Mass Spectrometry, LNBio, CNPEM Tutorial version 1.0, January 2014. Note: This tutorial was written based on the information
More informationInstructions for SPSS 21
1 Instructions for SPSS 21 1 Introduction... 2 1.1 Opening the SPSS program... 2 1.2 General... 2 2 Data inputting and processing... 2 2.1 Manual input and data processing... 2 2.2 Saving data... 3 2.3
More informationThe ChiSquare Test. STAT E50 Introduction to Statistics
STAT 50 Introduction to Statistics The ChiSquare Test The Chisquare test is a nonparametric test that is used to compare experimental results with theoretical models. That is, we will be comparing observed
More informationThis book serves as a guide for those interested in using IBM SPSS
1 Overview This book serves as a guide for those interested in using IBM SPSS Statistics software to assist in statistical data analysis whether as a companion to a statistics or research methods course,
More informationThis book serves as a guide for those interested in using IBM
1 Overview This book serves as a guide for those interested in using IBM SPSS/PASW Statistics software to aid in statistical data analysis whether as a companion to a statistics or research methods course
More informationA Basic Guide to Analyzing Individual Scores Data with SPSS
A Basic Guide to Analyzing Individual Scores Data with SPSS Step 1. Clean the data file Open the Excel file with your data. You may get the following message: If you get this message, click yes. Delete
More informationWhat is a Mail Merge?
NDUS Training and Documentation What is a Mail Merge? A mail merge is generally used to personalize form letters, to produce mailing labels and for mass mailings. A mail merge can be very helpful if you
More informationIn this article, learn how to create and manipulate masks through both the worksheet and graph window.
Masking Data In this article, learn how to create and manipulate masks through both the worksheet and graph window. The article is split up into four main sections: The Mask toolbar The Mask Toolbar Buttons
More informationUsing Microsoft Excel to Analyze Data from the Disk Diffusion Assay
Using Microsoft Excel to Analyze Data from the Disk Diffusion Assay Entering and Formatting Data Open Excel. Set up the spreadsheet page (Sheet 1) so that anyone who reads it will understand the page (Figure
More informationImporting and Exporting With SPSS for Windows 17 TUT 117
Information Systems Services Importing and Exporting With TUT 117 Version 2.0 (Nov 2009) Contents 1. Introduction... 3 1.1 Aim of this Document... 3 2. Importing Data from Other Sources... 3 2.1 Reading
More informationSimple Linear Regression, Scatterplots, and Bivariate Correlation
1 Simple Linear Regression, Scatterplots, and Bivariate Correlation This section covers procedures for testing the association between two continuous variables using the SPSS Regression and Correlate analyses.
More informationDirections for Frequency Tables, Histograms, and Frequency Bar Charts
Directions for Frequency Tables, Histograms, and Frequency Bar Charts Frequency Distribution Quantitative Ungrouped Data Dataset: Frequency_Distributions_GraphsQuantitative.sav 1. Open the dataset containing
More informationIntroduction to IBM SPSS Statistics
CONTENTS Arizona State University College of Health Solutions College of Nursing and Health Innovation Introduction to IBM SPSS Statistics Edward A. Greenberg, PhD Director, Data Lab PAGE About This Document
More informationGeoGebra Statistics and Probability
GeoGebra Statistics and Probability Project Maths Development Team 2013 www.projectmaths.ie Page 1 of 24 Index Activity Topic Page 1 Introduction GeoGebra Statistics 3 2 To calculate the Sum, Mean, Count,
More informationPsych. Research 1 Guide to SPSS 11.0
SPSS GUIDE 1 Psych. Research 1 Guide to SPSS 11.0 I. What is SPSS: SPSS (Statistical Package for the Social Sciences) is a data management and analysis program. It allows us to store and analyze very large
More informationSPSS/Excel Workshop 3 Summer Semester, 2010
SPSS/Excel Workshop 3 Summer Semester, 2010 In Assignment 3 of STATS 10x you may want to use Excel to perform some calculations in Questions 1 and 2 such as: finding Pvalues finding tmultipliers and/or
More informationWhen to use Excel. When NOT to use Excel 9/24/2014
Analyzing Quantitative Assessment Data with Excel October 2, 2014 Jeremy Penn, Ph.D. Director When to use Excel You want to quickly summarize or analyze your assessment data You want to create basic visual
More informationt Tests in Excel The Excel Statistical Master By Mark Harmon Copyright 2011 Mark Harmon
ttests in Excel By Mark Harmon Copyright 2011 Mark Harmon No part of this publication may be reproduced or distributed without the express permission of the author. mark@excelmasterseries.com www.excelmasterseries.com
More informationOneWay Analysis of Variance (ANOVA) Example Problem
OneWay Analysis of Variance (ANOVA) Example Problem Introduction Analysis of Variance (ANOVA) is a hypothesistesting technique used to test the equality of two or more population (or treatment) means
More informationUsing Excel in Research. Hui Bian Office for Faculty Excellence
Using Excel in Research Hui Bian Office for Faculty Excellence Data entry in Excel Directly type information into the cells Enter data using Form Command: File > Options 2 Data entry in Excel Tool bar:
More informationEXCEL Analysis TookPak [Statistical Analysis] 1. First of all, check to make sure that the Analysis ToolPak is installed. Here is how you do it:
EXCEL Analysis TookPak [Statistical Analysis] 1 First of all, check to make sure that the Analysis ToolPak is installed. Here is how you do it: a. From the Tools menu, choose AddIns b. Make sure Analysis
More informationUsing Microsoft Excel to Analyze Data
Entering and Formatting Data Using Microsoft Excel to Analyze Data Open Excel. Set up the spreadsheet page (Sheet 1) so that anyone who reads it will understand the page. For the comparison of pipets:
More informationSPSS for Simple Analysis
STC: SPSS for Simple Analysis1 SPSS for Simple Analysis STC: SPSS for Simple Analysis2 Background Information IBM SPSS Statistics is a software package used for statistical analysis, data management, and
More informationDescriptive Statistics
Descriptive Statistics Primer Descriptive statistics Central tendency Variation Relative position Relationships Calculating descriptive statistics Descriptive Statistics Purpose to describe or summarize
More informationTwoWay ANOVA with Post Tests 1
Version 4.0 StepbyStep Examples TwoWay ANOVA with Post Tests 1 Twoway analysis of variance may be used to examine the effects of two variables (factors), both individually and together, on an experimental
More informationStudent Guide to SPSS Barnard College Department of Biological Sciences
Student Guide to SPSS Barnard College Department of Biological Sciences Dan Flynn Table of Contents Introduction... 2 Basics... 4 Starting SPSS... 4 Navigating... 4 Data Editor... 5 SPSS Viewer... 6 Getting
More informationUsing Excel for Statistics Tips and Warnings
Using Excel for Statistics Tips and Warnings November 2000 University of Reading Statistical Services Centre Biometrics Advisory and Support Service to DFID Contents 1. Introduction 3 1.1 Data Entry and
More informationIntroduction to Statistical Computing in Microsoft Excel By Hector D. Flores; hflores@rice.edu, and Dr. J.A. Dobelman
Introduction to Statistical Computing in Microsoft Excel By Hector D. Flores; hflores@rice.edu, and Dr. J.A. Dobelman Statistics lab will be mainly focused on applying what you have learned in class with
More information8. Comparing Means Using One Way ANOVA
8. Comparing Means Using One Way ANOVA Objectives Calculate a oneway analysis of variance Run various multiple comparisons Calculate measures of effect size A One Way ANOVA is an analysis of variance
More informationSCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES
SCHOOL OF HEALTH AND HUMAN SCIENCES Using SPSS Topics addressed today: 1. Differences between groups 2. Graphing Use the s4data.sav file for the first part of this session. DON T FORGET TO RECODE YOUR
More informationThe Excel 2007 Data & Statistics Cookbook A PointandClick! Guide
The Excel 2007 Data & Statistics Cookbook A PointandClick! Guide Larry A. Pace Anderson University TwoPaces LLC Anderson SC Pace, Larry A. The Excel 2007 Data & Statistics Cookbook: A PointandClick!
More informationSurvey Research Data Analysis
Survey Research Data Analysis Overview Once survey data are collected from respondents, the next step is to input the data on the computer, do appropriate statistical analyses, interpret the data, and
More informationMain Effects and Interactions
Main Effects & Interactions page 1 Main Effects and Interactions So far, we ve talked about studies in which there is just one independent variable, such as violence of television program. You might randomly
More informationAdditional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jintselink/tselink.htm
Mgt 540 Research Methods Data Analysis 1 Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jintselink/tselink.htm http://web.utk.edu/~dap/random/order/start.htm
More informationInstructions for dataentry and dataanalysis using Epi Info
Instructions for dataentry and dataanalysis using Epi Info After collecting data using the tools for evaluation and feedback available in the Hand Hygiene Implementation Toolkit (available at http://www.who.int/gpsc/5may/tools
More informationChapter 2 Introduction to SPSS
Chapter 2 Introduction to SPSS Abstract This chapter introduces several basic SPSS procedures that are used in the analysis of a data set. The chapter explains the structure of SPSS data files, how to
More informationSPSS TUTORIAL & EXERCISE BOOK
UNIVERSITY OF MISKOLC Faculty of Economics Institute of Business Information and Methods Department of Business Statistics and Economic Forecasting PETRA PETROVICS SPSS TUTORIAL & EXERCISE BOOK FOR BUSINESS
More informationClass 19: Two Way Tables, Conditional Distributions, ChiSquare (Text: Sections 2.5; 9.1)
Spring 204 Class 9: Two Way Tables, Conditional Distributions, ChiSquare (Text: Sections 2.5; 9.) Big Picture: More than Two Samples In Chapter 7: We looked at quantitative variables and compared the
More informationTABLE OF CONTENTS. About Chi Squares... 1. What is a CHI SQUARE?... 1. Chi Squares... 1. Hypothesis Testing with Chi Squares... 2
About Chi Squares TABLE OF CONTENTS About Chi Squares... 1 What is a CHI SQUARE?... 1 Chi Squares... 1 Goodness of fit test (Oneway χ 2 )... 1 Test of Independence (Twoway χ 2 )... 2 Hypothesis Testing
More informationProjects Involving Statistics (& SPSS)
Projects Involving Statistics (& SPSS) Academic Skills Advice Starting a project which involves using statistics can feel confusing as there seems to be many different things you can do (charts, graphs,
More informationNormality Testing in Excel
Normality Testing in Excel By Mark Harmon Copyright 2011 Mark Harmon No part of this publication may be reproduced or distributed without the express permission of the author. mark@excelmasterseries.com
More informationHow to Use a Data Spreadsheet: Excel
How to Use a Data Spreadsheet: Excel One does not necessarily have special statistical software to perform statistical analyses. Microsoft Office Excel can be used to run statistical procedures. Although
More informationDescriptive and Inferential Statistics
General Sir John Kotelawala Defence University Workshop on Descriptive and Inferential Statistics Faculty of Research and Development 14 th May 2013 1. Introduction to Statistics 1.1 What is Statistics?
More informationChapter 4 Displaying and Describing Categorical Data
Chapter 4 Displaying and Describing Categorical Data Chapter Goals Learning Objectives This chapter presents three basic techniques for summarizing categorical data. After completing this chapter you should
More informationWord 2010: Mail Merge to Email with Attachments
Word 2010: Mail Merge to Email with Attachments Table of Contents TO SEE THE SECTION FOR MACROS, YOU MUST TURN ON THE DEVELOPER TAB:... 2 SET REFERENCE IN VISUAL BASIC:... 2 CREATE THE MACRO TO USE WITHIN
More informationDoing Multiple Regression with SPSS. In this case, we are interested in the Analyze options so we choose that menu. If gives us a number of choices:
Doing Multiple Regression with SPSS Multiple Regression for Data Already in Data Editor Next we want to specify a multiple regression analysis for these data. The menu bar for SPSS offers several options:
More informationHeat Map Explorer Getting Started Guide
You have made a smart decision in choosing Lab Escape s Heat Map Explorer. Over the next 30 minutes this guide will show you how to analyze your data visually. Your investment in learning to leverage heat
More informationGetting started manual
Getting started manual XLSTAT Getting started manual Addinsoft 1 Table of Contents Install XLSTAT and register a license key... 4 Install XLSTAT on Windows... 4 Verify that your Microsoft Excel is uptodate...
More informationStatistics Review PSY379
Statistics Review PSY379 Basic concepts Measurement scales Populations vs. samples Continuous vs. discrete variable Independent vs. dependent variable Descriptive vs. inferential stats Common analyses
More informationINTERPRETING THE ONEWAY ANALYSIS OF VARIANCE (ANOVA)
INTERPRETING THE ONEWAY ANALYSIS OF VARIANCE (ANOVA) As with other parametric statistics, we begin the oneway ANOVA with a test of the underlying assumptions. Our first assumption is the assumption of
More informationGETTING YOUR DATA INTO SPSS
GETTING YOUR DATA INTO SPSS UNIVERSITY OF GUELPH LUCIA COSTANZO lcostanz@uoguelph.ca REVISED SEPTEMBER 2011 CONTENTS Getting your Data into SPSS... 0 SPSS availability... 3 Data for SPSS Sessions... 4
More informationSTA201TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance
Principles of Statistics STA201TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis
More informationMicrosoft PowerPoint 2010
Microsoft PowerPoint 2010 Starting PowerPoint... 2 PowerPoint Window Properties... 2 The Ribbon... 3 Default Tabs... 3 Contextual Tabs... 3 Minimizing and Restoring the Ribbon... 4 The Backstage View...
More informationIBM SPSS Data Preparation 22
IBM SPSS Data Preparation 22 Note Before using this information and the product it supports, read the information in Notices on page 33. Product Information This edition applies to version 22, release
More informationFairfield Public Schools
Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity
More informationHow To Use Spss
1: Introduction to SPSS Objectives Learn about SPSS Open SPSS Review the layout of SPSS Become familiar with Menus and Icons Exit SPSS What is SPSS? SPSS is a Windows based program that can be used to
More informationCharting LibQUAL+(TM) Data. Jeff Stark Training & Development Services Texas A&M University Libraries Texas A&M University
Charting LibQUAL+(TM) Data Jeff Stark Training & Development Services Texas A&M University Libraries Texas A&M University Revised March 2004 The directions in this handout are written to be used with SPSS
More informationUNIVERSITY of MASSACHUSETTS DARTMOUTH Charlton College of Business Decision and Information Sciences Fall 2010
UNIVERSITY of MASSACHUSETTS DARTMOUTH Charlton College of Business Decision and Information Sciences Fall 2010 COURSE: POM 500 Statistical Analysis, ONLINE EDITION, Fall 2010 Prerequisite: Finite Math
More information