Use the General Social Survey (GSS) dataset for this Discussion.

There is nothing special or mysterious about ANOVA. It is only a series of t-tests that SPSS runs simultaneously to provide both speed and statistical power. For example, if you want to know if there is a difference in the dependent ratio variable, Size of Place in 1000S, based on the independent nominal variable Race of Respondent (with 3 levels,black, white, other), do the following:

Open the GSS data set, select Analyze, select One-way ANOVA, drag Size of Place into the Dependent List box, drag Race of Respondent into the Factor box, select Post Hoc, select an appropriate Post Hoc test from the Equal Variances Assumed box, click Continue, click OK.

Review the Sig. value in the Between Groups row in the SPSS Output under ANOVA and decide to reject or fail to reject the null hypothesis.

If you reject the null and determine that the ANOVA is statistically significant, review the Multiple Comparisons Output below the ANOVA Output.** This Output compares each level of the IV to every other level of the IV and tells us if the comparison is statistically significant.

For example, the first 2 rows of the Multiple Comparisons Output compares white to black and white to other and tells of if there is a statistically significant difference in Size of Place between black and white and white and other. In this case, both comparisons are statistically significant because the respective Sig. values are less than .05.

Since there are only 3 levels of the IV there are only 3 comparisons that we are interested in reviewing, white/black, white/other, black/other. Note: black/white is the same as white/black, white/other is the same as other/white and black/other is the same as other/black.

**Note: If you fail to reject the null and find that the ANOVA is not statistically significant, then there is no need to review Multiple Comparisons… …so don’t.

For your discussion post, follow this outline and use each point as a header::

-Identify the dependent variable (DV) and its Level of Measurement (Hint: it must be interval or ratio)

-Identify the independent variable (IV) and its Level of Measurement (Hint: The IV must be nominal and it must have 3 or more levels)

-Write a research question (RQ)** that can be addressed by a One-way ANOVA. Use this format:

Is there a difference in the DV based on the IV? For example:

Is there a difference in Size of Place in 1000s based on Race of Respondent?

**Note: a question is an interrogative sentence that ends with a question mark. Keep your RQ simple and concise.

-Write the null hypothesis for your question. Use this format:

There is no difference in (insert DV) based on (insert IV).

-State the research design that aligns with the RQ.

-State the means test used to address the RQ. You have only 1 choice here: One-way ANOVA.

-Decide if the ANOVA is statistically significant and decide to reject or fail to reject the null hypothesis based on the significance finding.

-If the ANOVA is significant, calculate the effect size.** For a One-way ANOVA effect size is measured by = eta-squared. Calculate eta-squared this way:

Go to the ANOVA Output.

Go to the Between Groups row and select the value in the Sum of Squares column.

Go to the Total row and select the value in the Sum of Squares column.

Divide the Between Groups Sum of Squares by the Total Sum of Squares. The result of this division is eta-squared and it must have a value between 0 and 1.

Explain the meaning of effect size.

Decide if the effect is small, medium, or large.

If the ANOVA is not significant the effect size is meaningless… …so don’t calculate it… …just don’t.

Use SPSS to answer the research question. Post your response to the following:

1. What is your research question?
2. What is the null hypothesis for your question?
3. What research design would align with this question?
4. What dependent variable was used and how is it measured?
5. What independent variable is used and how is it measured?
6. If you found significance, what is the strength of the effect?
7. Explain your results for a lay audience and further explain what the answer is to your research question.

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