Log onto: https://apps.csbs.utah.edu/

Enter your UID and password. Make sure you have popups allowed for this site. You may need to go to preferences (right most tab) and change your client to Java. I have found the java client to be more stable than the citrix client, which you need to download and install, in the past.

Change to Java

You should now have a window open something like this. Open SPSS PASW 18.

A connection window will come up and SPSS will start. Sometimes this will fail for some reason or other. If it does try it again and it usually will work.

Open an existing data set or start a new one. Copy and paste your data from excel into the data window.

You can and should rename the variables under the Variable View tab.

Unfortunately, our data is not of the form we need for SPSS analysis. We really want all 3 collected data sets to be in one variable and a second variable to describe which group they are in. Restructuring the data in this format is easily done in SPSS. First go to Data->Restructure. Save your data in case (your computer is the H:// drive called client not the default selected C://).

You want to restructure into cases. This should be the default option.

Variables into cases

Click next. You want 1 group so make sure that it is selected

Click next and add your variables to the list to be transposed. Also change the case group identification to none if you dont want case id as a variable.

Set to None

Add your variables here

Select one

Click next. Lastly you want to create one index variable.

You can now click next then finish. The remaining properties can remain at their defaults safely. Your data should now be formatted properly. SPSS likes to group the index in an odd way. You can use the data commands to sort this if you like just be sure you keep rows properly associated. If your variables were different list lengths you will have missing data entries near the end of the new list. This is not a problem since the analysis will be done with listwise deletion which will ignore these cases. You should rename your data so it is easier to understand later. Mine have been renamed group and data.

One index variable desired

Finally our data is formatted correctly for all our SPSS needs. For an ANOVA test select: Analyze->Compare Means->One-Way ANOVA

This will bring up the following window. Stuff in your comparisons to the appropriate spots with the factor being the grouping variable. Additional output options and tests can be found under Post Hoc... and Options... In this case I told it to run a Tukey's test and provide descriptives in addition to the ANOVA test.

My output looked like this and can easily be exported into a .doc file. You should usually change the settings to shrink tables instead of wrapping them though. Again your computer is the H:// drive not the C:// drive.

Oneway [DataSet3] H:\Desktop\haptics\original_1.sav

Descriptives

data

N Mean

Std.

Deviation

Std.

Error

95% Confidence Interval

for Mean

Minimum Maximum

Lower

Bound

Upper

Bound

1 38 9.6582 4.72225 .76605 8.1060 11.2103 3.00 25.40

2 33 3.1136 2.08230 .36248 2.3753 3.8520 1.00 9.00

3 44 26.649

1

15.91236 2.39888 21.8113 31.4869 2.54 76.20

Total 115 14.281

0

14.36057 1.33913 11.6282 16.9338 1.00 76.20

ANOVA

data

Sum of Squares df Mean Square F Sig.

Between Groups 11658.181 2 5829.091 55.086 .000

Within Groups 11851.582 112 105.818

Total 23509.763 114

Post Hoc Tests

Multiple Comparisons

data

Tukey HSD

(I) group (J) group

Mean

Difference (I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

1 2 6.54452* 2.44771 .023 .7305 12.3585

3 -16.99093* 2.27807 .000 -22.4020 -11.5799

2 1 -6.54452* 2.44771 .023 -12.3585 -.7305

3 -23.53545* 2.36887 .000 -29.1622 -17.9087

3 1 16.99093* 2.27807 .000 11.5799 22.4020

2 23.53545* 2.36887 .000 17.9087 29.1622

*. The mean difference is significant at the 0.05 level.

Homogeneous Subsets

data

Tukey HSDa,b

group N

Subset for alpha = 0.05

1 2 3

2 33 3.1136

1 38 9.6582

3 44 26.6491

Sig. 1.000 1.000 1.000

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 37.809.

b. The group sizes are unequal. The harmonic mean of the

group sizes is used. Type I error levels are not guaranteed.

The ANOVA test tells me that at least one of the data sets is significantly different from the others. The following table for Tukey's test in fact tells me that each of the 3 groups is significantly different than the others. Note that we did not do any transformations on this data, thus we have broken the normal distribution assumption of the ANOVA test, so these results may be worthless. But now that you can do it yourself, you can do it on transformed data. Always save off your transformed data into a new variable! This way you have a fresh copy of the data on hand if you need it. Two-way ANOVA is a little different. Two way ANOVA is not directly supported by the system. However its equivalent can be done through: Analyze->General Linear Model->Univariate Your fixed factors should be the experimenter and body part. The dependent variable should be the combined data as in the previous ANOVA example. You will need to properly format your data for this but that should not be too hard given what you have learned here.

Example formatted data

Quickly formatting the data and running a 2 way ANOVA gives me the following output. Remember that within this test each reported value is the contribution of that variable above and beyond all the other variables listed. It tells us that the body part has a significant influence on the data despite which experimenter collected it and the interaction between the two. It also tells us that each experimenter had a significant influence on the end resultant data above and beyond the body part and interaction between the experimenter and body part. That last fact ideally should not be true but since the data was collected in wildly different ways this makes some sense. Lastly, it also evaluates the contributions of the interaction between the body part and experimenter. This also appears to contribute a significant impact on the measurements above and beyond that explained by the body part and experimenter separately. Be aware that in this case the intercept it reports is meaningless since it is for a body part index of 0 and an experimenter index of 0 neither of which exist.

Between-Subjects Factors

N

part 1.00 15

2.00 15

experimenter 1.00 10

2.00 10

3.00 10

Tests of Between-Subjects Effects

Dependent Variable:data

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 229.242a 5 45.848 64.349 .000

Intercept 785.408 1 785.408 1102.327 .000

part 190.008 1 190.008 266.678 .000

experimenter 30.717 2 15.358 21.556 .000

part * experimenter 8.517 2 4.258 5.977 .008

Error 17.100 24 .713

Total 1031.750 30

Corrected Total 246.342 29

a. R Squared = .931 (Adjusted R Squared = .916)

Helpful Troubleshooting

Make sure you have popups enabled when using the citrix client.

If the program stops responding, give it a moment.

If it continues behaving improperly, close and restart it.

If this persists across instances you will need to log off the server. To do this go to you connection center and click on connections. Click the SPSS server (should be first indented name, they tend to vary). Click the log off button to the right.

There are other write-ups on how to do these functions in SPSS if this one isn't to your liking Google another one.