<p> SOC 190.2: Community-Based Research</p><p>SPSS Exercise #2: Crosstabs and analyzing data.</p><p>1. First, let’s fix the value labels for Q5-Q17. They should be as follows: a. 1=better, 3=same, 4=don’t know. -999 = missing. b. Now all variables should have -999 set as missing. 2. Save the file. 3. Print the frequencies for all variables. Analyze-Descriptives-Frequencies. Menu opens up. Use the cursor to move all variables q1-q17 into the right window. Click ok. Let’s look at the results. 4. Correlation: Analyze-Correlate-Bivariate. As with Frequencies, move q1-q17 into the right window. Click OK. The results are known as a correlation table The asterisks denote significant (p<.05) levels. Why are the correlations for q5-q17 negative for r coefficients under Q1 and Q2 but not under Q4? 5. Now let’s try a crosstab, not unlike what we saw with the SDA data. ANALYZE- DESCRIPTIVES-CROSSTAB. Choose q5 for column and q1 for row. Click on CELLS at the bottom of the menu. Click on ROW and COLUMN and hit continue. Click on OK, and the program runs.</p><p>Homework: We will start this in class. You may do this with someone else – I even encourage it. When you turn in the homework, indicate the team members. Due next week. </p><p>1. Create a bar vertical graph for q1-q4. Discuss the results. 2. Create a bar horizontal bar chart for the ‘top box’ (percentage ‘better’) for the q5-q17 variable. Discuss the results. 3. Discuss the results for the correlation table. 4. How to conclude and recommend: First identify the q5-q17 metrics that are significantly correlated with the Q1-Q4 overall program metrics. Then, of those with significant correlations, examine the q5-q17 variables to identify those with the highest, and lowest ratings. The q5-q17 metrics that are correlated AND have high values are their strengths. The ones with low values are areas FSSBA might consider improving. Discuss in ‘bullet’ form. We need to do this analysis for each of the q1-q4 variables, which function here as our dependent variables. </p>