0.8 Conducting a parametric one-way analysis of variance  (Page 4/4)

• Copy skewness and kurtosis information into the skewness and kurtosis calculator

Step two

• Compute Descriptive Statistics on the Dependent Variable
• * Do so via the ANOVA procedure
• * Note. Do not use the ANOVA statistical significance information provided in the output. Use only the M s, SD s, and n s.
• * The screen shot will occur in the next step (Mean and standard deviation)

Step three

• Conduct Analysis of Variance
• √ Analyze
• √ General Linear Model
• √ Univariate

• √ Dependent variable is sent over to the top box, titled dependent variable
• √ Grouping Variable is sent over to the fixed factor box

• √ Options
• √ Descriptive Statistics
• √ Estimate of effect size
• √ Continue

• √ Post Hoc
• √ Scheffé
• √ Click on variables on which you want the Post Hoc Tests
• √ Continue
• √ OK

Step four

• Check for Statistical Significance
• 1. Go to the ANOVA table and look at the far right column labeled Sig to check for statistical significance.
• 2. If you have any value less than .05 then you have statistical significance. Remember to replace the third zero with a 1, if the sig value is .000 (i.e., if the sig value reads as .000, replace the third 0, so it reads as .001).
• 3. Numerical Sentence = F ( df between, df within) _sp = _sp F value, _sp p _sp < _sp .001.
• 4. The outcome of the ANOVA, F (2,1179) = 503.22, p = .001, was . . . .

Dependent Variable: Verbal IQ (Wechsler Verbal Intelligence 3)

• a. R Squared = .461 (Adjusted R Square = .460)

Step five

• 1. Partial Eta ² is the effect size n ²
• 2. Cohen (1988)
• .01 - .059 = small effect size
• .06 - .139 = moderate effect size
• .14 and above = large effect size
• Note. n ² cannot be greater than 1.00. Therefore, a 0 should not be placed in front of the decimal point.

Step six:

• Narrative and Interpretation
• 1. F value
• 2. degrees of freedom for groups and for participants
• 3. p value
• 4. Post hoc results
• 5. M , SD , and n for each group (in a table)

Writing up your statistics

So, how do you "write up" your Research Questions and your Results? Schuler W. Huck (2000) in his seminal book entitled, Reading Statistics and Research, points to the importance of your audience understanding and making sense of your research in written form. Huck further states:

This book is designed to help people decipher what researchers are trying to communicate in the written or oral summaries of their investigations. Here, the goal is simply to distill meaning from the words, symbols, tables, and figures included in the research report. To be competent in this arena, one must not only be able to decipher what's presented but also to "fill in the holes"; this is the case because researchers typically assume that those receiving the research report are familiar with unmentioned details of the research process and statistical treatment of data.

Researchers and Professors John Slate and Ana Rojas-LeBouef understand this critical issue, so often neglected or not addressed by other authors and researchers. They point to the importance of doctoral students "writing up their statistics" in a way that others can understand your reporting and as importantly, interpret the meaning of your significant findings and implications for the preparation and practice of educational leadership. Slate and LeBouef provide you with a model for "writing up your parametric ANOVA statistics."

Click here to view: Writing Up Your Parametric One Way ANOVA Statistics

References

• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.) . Hillsdale, NJ: Lawrence Erbaum
• Hyperstats Online Statistics Textbook. (n.d.) Retrieved from (External Link)
• Kurtosis. (n.d.). Definition. Retrieved from (External Link)&term_id=326
• Kurtosis. (n.d.). Definition of normality . Retrieved from (External Link)
• Onwuegbuzie, A. J.,&Daniel, L. G. (2002). Uses and misuses of the correlation coefficient. Research in the Schools, 9 (1) , 73-90.
• Skewness. (n.d.) Retrieved from (External Link)&term_id=356
• Skewness. (n.d.). Definition of normality . Retrieved from (External Link)
• StatSoft, Inc. (2011). Electronic statistics textbook. Tulsa, OK: StatSoft. WEB: (External Link)