Textbooks
1. OpenStax, Introductory Statistics. OpenStax. 19 September 2013.
2. Tyrrell, S. 2009. SPSS: Stats practically short and simple (1st edition).
Original Question:
Forum
During Week 5, we used measures of association (Lambda, Gamma, Pearson's r) to determine if a relationship is weak, medium, or strong.
This week, we'll study tests of significance. Like measures of association, levels of measurement of your variables determine which test of significance works for your research project. Here is the guideline:
1. Before-and-after design and the variable is at I/R level: Dependent Sample T-test
2. DV and IV are BOTH categorical variables (nominal/ordinal): Chi-square
3. DV and IV are both continuous variables: regression
4. DV is a continuous variable (I/R level):
1. IV is categorical (dichotomous nominal/ordinal): Independent Sample T-test
2. IV is categorical with more than 2 categories: ANOVA
Why do we need to run tests of significance?
1. They allow us to see if our relationship is "statistically significant." To be more specific, these test tell us if a relationship observed in a sample, like your research project based on GSS 2012 data set, is generalizable to the population from which this sample was drawn.
2. Test result reported under "p" in the SPSS output tells us the chances that a relationship observed in the sample is not real, but rather due to factors like a sampling error. We compare this "chance" with level of significance, commonly set as .05 or .01. If this chance is smaller than level of significance, we can reject the null hypothesis, and keep the research hypothesis.
This week in the forum discussion:
1. you will decide which test of significance you will use for your project. Use the guideline above to make your choice;
2. you will be using a process for hypothesis testing which outlines five steps researchers can follow to complete this process:
1. Write your research hypothesis (H1) and your null hypothesis (H0).
2. Identify and record your level of significance: either .05 or .01.
3. Complete the test using SPSS.
4. Identify the number under Sig. (2-tail). This will be represented by "p." compare the numbers in steps 2 (level of significance) and 4 and apply the following rule:
1. If p < or = level of significance, than you reject the null hypothesis
5. Determine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain what that means to your research .
Attachment:- ANOVA.rar