APU SOCI332 Week 6 Forum Latest 2019 February Question # 00597870 Subject: Education Due on: 02/07/2019 Posted On: 02/07/2019 04:45 AM Tutorials: 1 Rating: 4.7/5

SOCI332
Statistics for Social Science

Week 6
Forum

Tests of Significance and Measures of Association

In Week 4, we used epsilons and 10-percent-point rule to
determine if a potential relationship between two variables is worth examining
further. During Week 5, we studied tests of significance. In this week’s forum,
we will apply these tests of significance to our project variables. We will
also run measures of association to determine the strength and direction of the
relationship between our variables. As we discussed previously, the levels of
measurement of our variables determine which test of significance works for the
research project. Here is the guideline:

1. Before-and-after design and the DV is at I/R level:
Dependent Sample T-test

2. DV and IV are BOTH categorical variables
(nominal/ordinal): Chi-square

*Special note for Chi-square: you should have less than 20%
of the cells with an expected count of 5 or less. This information is reported
automatically, right below the chi-square output table. If your chi-square test
fails to meet this requirement, it is necessary to use “recoding” to
combining certain answer categories together so the expected counts would
increase.

3. DV and IV are both continuous (interval/ratio) variables:
regression

4. Comparison of groups (when IV is categorical –
nominal/ordinal and DV is continuous – interval/ratio):

a. Between
2 groups: Independent Sample T-test

b. Among 3
or more groups: ANOVA

Why do we need to run tests of significance?

They allow us to see if our relationship is
“statistically significant.” To be more specific, these tests tell us
if a relationship observed in a sample, like your research project based on GSS
2016 data set, is generalizable to the population from which this sample was
drawn (US adults).

Test results 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.

Next, we’ll use tests of “measures of association”
to figure out the exact strength of a relationship between two variables. In
addition, we’ll learn how to interpret SPSS outputs for measures of association
tests such as lambda, gamma, and Pearson’s r, along with other possible tests.
These tests are also specific to the level of measurement of your variables.
Here are the guidelines:

Both DV and IV are nominal variables: Lambda (when it is not
a 2X2 table)

If it is a 2X2 table: Phi

Both DV and IV are ordinal variables: Gamma

One variable ordinal AND the other variable dichotomous
nominal (like Yes/No, male/female, etc.): Gamma

One variable ordinal AND the other variable nominal (not dichotomous,
has more than 2 categories): Cramer’s V.

Both DV and IV are I/R variables: Pearson’s r

To interpret the output, see attached handout. Keep in mind
measures of association is a statistical procedure based on Proportional
Reduction of Error (PRE). Thus the format of interpretation will be: Knowing
the IV will reduce error in predicting the DV by *%.

Please note: Don’t just say “IV” and
“DV” in your explanation. You need to enter your variables names for
IV and DV, and replace * for the exact test value from the output. If the value
of Lambda is .34, then it will be interpreted as 34%.

****Ok, now it is time for you to try! For this week’s
forum, be sure to perform the correct test of significance (choose one) and
measure of association (choose one) on your variables for the final project.
You can download the class handout attached at the bottom of the page.

This week in the forum discussion:

I. You will decide which test of significance you will use
for your project. Use the guideline above to make your choice.

II. You will use the process for hypothesis testing which
outlines five steps:

Write your research hypothesis (H1) and your null hypothesis
(H0).

Identify and record your level of significance (alpha):
either .05 or .01.

Complete the significance test using SPSS. (Include the
output of the analysis (table) in your post.)

Identify the number under Sig. (2-tail). This will be represented by “p.”
Compare the numbers in steps 2 (alpha) and 4 (p) and apply the following rule:

If p < or = alpha, than you reject the null hypothesis

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.

III. You will decide which measure of association you will
use for your project. Use the guideline above to make your choice. Include the
output (tabe) in your post. Based on the output, describe the strength and
direction of the relationship between the variables. Also explain the PRE.