Practice Exam #2/Part B Tip Sheet

(Anaerobic Power Data Set)

A.     Is the power output for the 50m sprint different from that for the 200m sprint?

·        DV=Power Measure

·        IV#1=Sprint Length (2 levels)

Ø      STATS Test =Paired T-Test (2 tailed)

Ø      ? Might be “Unpaired” but not enough info to determine?

ä     Excel Tips: Input zero into the “Hypothesis Means Difference” box when you do the data analysis.  This means you believe there is NO (zero) difference between your population #1 mean and population #2 mean (m1-m2=0)

B.     Is the anaerobic power of the 15s power step “related” to that of the 60s power step test?

·        DV=Power Measure

·        IV=Power Step Test (two levels)

o       Note: The bigger the r value #, the smaller the p value (Table A.2)

o       R Squared

Ø      STATS Test =Correlation

ä     Excel Tips: Put both variables (60s & 15s tests) side by side then highlight BOTH columns together as the “Input Range”

C.    Can 60 second power step test performance be “predicted” from the 15 second performance?  If so, how?

·        DV=60 Second Power Measure

·        IV=15 Second Power Measure

o       Note: The bigger the r value #, the smaller the p value (Table A.2)

o       DV is always the Y variable.

Ø      STATS Test =Regression Analysis

ä     Summary Tips: Look at “r value” on Excel output.  (r=72.9%)  so r is low and not a good or strong model for predicting a relationship.  Ideally you want at least a % in the 80s and ideally a % in the 90s before you have a true correlation that can be used to predict. 

(Equipment Comparison Data)

A.     Is the rating of perceived exertion (RPE) significantly different across the four exercise conditions?

·        DV=RPE

·        IV=Equipment (four levels)

Ø      STATS Test =One-Way ANOVA (with Tukey Post Hoc)

o       Tukey cannot be done with Excel!

ä     Excel Tips: Can’t stack columns like in SPSS, you have to put variables side by side i.e. RPE1 | RPE2 | RPE3 | RPE4 |

B.     Is heart rate “related” to RPE when men and women work out on exercise equipment #1? (ONLY select Equipment #1 and make new data sheet!)

·        DV=RPE

·        IV=HR

Ø      STATS Test =Correlation (“related” is key word for correlation test)

ä     Summary Tips: With df=32, p>.10 so it is not significant and cannot be used to predict i.e. no significant correlation exists.

C.    Can RPE be used to “predict” heart rate when exercise equipment #1 is used?

·        DV=HR (y variable—the one being “predicted”)

·        IV=RPE (x variable)

Ø      STATS Test =Regression Analysis (“predict” is key word for Regression Analysis Test)

ä     Summary Tips: R squared value is low (.00963) so can’t use this to predict because there is NO significant correlation.

o       Question?: Is the Significant F equivalent to the “p value”?  If so, then F=.5807 means p>.05 so not significant.  I am confused about this part.

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