EDMS 451 Study Guide - Final Guide: Null Hypothesis, Type I And Type Ii Errors, Standard Score

• School: University of Maryland
• Department: Measurement, Statistics, and Evaluation
• Course: EDMS 451
• Professor: Gregory Hancock

Document Summary

Y= a+bx (it becomes y"= a+bx when predicting a y value for regression or line of best fit) (cid:1851) (cid:1835)(cid:1866)(cid:1872)(cid:1857)(cid:1870)(cid:1855)(cid:1857)(cid:1868)(cid:1872):(cid:1854)=(cid:1870)(cid:4666)(cid:3274)(cid:3273)(cid:4667), (cid:1867)(cid:1868)(cid:1857):(cid:1853)=(cid:1851) (cid:1854)(cid:1850) (cid:1852)(cid:3025)=(cid:3025) (cid:3025) (cid:3273),(cid:1852)(cid:3026)=(cid:3026) (cid:3026) (cid:3274) Z score for actual y: (cid:1852)=(cid:3026) (cid:3026) (cid:3274). (cid:3273) Confidence interval for the actual y value: (cid:4666)(cid:1851) (cid:3030)(cid:3045)(cid:3047)(cid:3026). (cid:3025),(cid:1851) +(cid:3030)(cid:3045)(cid:3047)(cid:3026). (cid:3025)(cid:4667) Linearity of the relation between x and y. Normality of errors around the regression line. Homoscedasticity(evenness of the spread) of errors around regression line. Slope: change in y/change in x (note: it is also related to correlation) When the x and y relation gets weaker, the y predictions regress from their actual values. Relies more on nominal and ordinal data. Observes the frequencies/counts of events while comparing the observed results with the. Only 1-tailed tests are used, but the degrees of freedom are necessary. Df= k-1, k represents the number of categories. Relies more on the modes of the data, while z and t tests, correlations, covariance, and.