Basic Statistical Analysis |
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Page 178
... degrees of freedom in this case must equal the size of the first sample minus one , plus the size of the second sample minus one . Thus , for the t ratio , - df = N1 − 1 + N2 − 1 or , perhaps , more conveniently , df N , N2- 2 = + ...
... degrees of freedom in this case must equal the size of the first sample minus one , plus the size of the second sample minus one . Thus , for the t ratio , - df = N1 − 1 + N2 − 1 or , perhaps , more conveniently , df N , N2- 2 = + ...
Page 290
... degrees of freedom in the column at the far left and the critical chi square values for the .05 and .01 alpha error levels in the next two columns . Note that in this table as the degrees of freedom increase , the critical chi square ...
... degrees of freedom in the column at the far left and the critical chi square values for the .05 and .01 alpha error levels in the next two columns . Note that in this table as the degrees of freedom increase , the critical chi square ...
Page 348
Richard C. Sprinthall. Degrees of Freedom for the Paired t Ratio The degrees of freedom for the paired t ratio are equal to the number of pairs of scores , N , minus one : df = N 1 Since the paired t makes use of scores that are yoked ...
Richard C. Sprinthall. Degrees of Freedom for the Paired t Ratio The degrees of freedom for the paired t ratio are equal to the number of pairs of scores , N , minus one : df = N 1 Since the paired t makes use of scores that are yoked ...
Common terms and phrases
a z score alpha error analysis ANOVA assumed average basis calculate central tendency chance Chapter column confidence interval control group correlation degrees of freedom equal equation error of difference estimated standard error example experimental F ratio fall find the percentage given graph height hypothesis of difference independent variable inferential statistics interquartile range interval data IQ scores manipulated math measures of central median method mode negative nominal data normal curve normal distribution null hypothesis number of scores obtained occur ordinal data paired parameter percentile person platykurtic population mean post-facto research predict probability problems random sample randomly range rank raw score reject the null relationship sample groups sample means sampling distribution Scale of measurement selected significant standard deviation standard deviation units standard error statistical test statisticians sum of squares technique Test the hypothesis tion variance within-subjects X₁ zero ΣΧ