A chi square test
revealed a significant difference between responses and treatment conditions, [chi square] (1, N = 19) = 5.
A regression analysis of the groups pointed tot eh same differences noted from the Chi square test
and both were confirmed by the t-test and f-test statistics.
First, to determine the overall effectiveness of the SPS in identifying high risk patients, a one-group chi square test
was employed comparing base line suicidal frequency data with observed numbers of suicidal incidents.
Although one might expect those planners selling long-term care insurance to be better informed or to have stronger feelings concerning the seriousness of the catastrophic illness problem than those not selling long-term care insurance, a chi square test
failed to show a statistically significant
Three statistical analyses aided analyzing the results: Chi Square Test
of Independence, Correlation and ANOVA (Analysis of Variation).
Chi Square Test
of Significance, Part II: Experimental Design Chapter 15.
The authors cover measures of central tendency, correlation, regression, chi square test
of significance, analysis of variance, group comparisons, and split block design.
A chi square test
was used in analyzing the data to determine if there were significant differences between levels of assertiveness and participants' age, birth order, ethnicity, academic classification and prior history of counseling.
As the socio-demographic characteristics of non-respondent caregivers were unknown, characteristics of patients with respondent caregivers and patients with non-respondent caregivers were obtained from the patient's medical record and were analyzed for statistical significance using a Chi Square Test
of Independence (Table 2).