1. is used when we have categorical (nominal) rather than interval / ratio data can also be used for measurement data, is less powerful and than typical tests such as means CHI Square

2. CHI Square for a multicategory case GoodBad MediumTotal Observed26401581 Expected27272781 CHI square or X 2 = X 2 = 11.63

3. SPSS output NPar Tests Chi-Square Test Frequencies

4. CHI Square for a Contingency Table Analysis (when there is more than one variable) GoodBadMediumTotal Finance26 (27) 40 (27) 15 (27) 81 Newspaper21 (30) 27 (30) 42 (30) 90 The table shows that webpages in the Finance category were more were more likely to be good than were webpages in the Newspaper condition. Thus, the column a webpage is in (Good, Bad, or Medium) graduate) is contingent upon (depends on) the row the webpage is in (Finance or newspaper category)

5. SPSS:using the Non Parametric tool NPar Tests Chi-Square Test Frequencies

6. SPSS: using cross tabs Mean = 393.2 Crosstabs

7. Confidence Limits on Mean Sample mean is a point estimate (estimate is in form of a single number) We want interval estimate (a range of numbers), and be able to specify with 95% confidence that estimate will lie in that range –Probability that interval computed this way includes  = 0.95

8. For Darts Data

9. Displaying Confidence Intervals What would 99% confidence intervals look like?

10. Margin of Error Generally computed for 95% confidence Computed for Proportions Simple Formula (for estimating sample size before starting study) Margin = + 1/ sqrt(N) For sample size 100 = 1/sqrt(100) =.1 or 10% For sample size 400 = 1/sqrt(400) =.05 or 5%

11. Formula for calculating Margin of Errors after gathering data Probability Yes =.55, No =.45 N = 200 Margin = 1.96 * sqrt((p*(1-p))/N) = 1.96 * sqrt((.25)/200) = 1.96 *.0012