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Quantitative Analysis: Inferential Statistics, These are based on…
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A system of equations that can be used to represent linear patterns of relationships in observed data
Two variable linear model: examines the relationship between one independent variable (the cause or predictor) and one dependent variable (the effect or outcome). The slope and intercept can be used to estimate additional values
A line that describes the relationship between two or more variables is called a regression line. The process of estimating regression coefficients is called regression analysis
ANOVA: an analysis of variance. Comparing the effects of two levels (0 and 1) of a dummy variable on the outcome variable
ANCOVA: an analysis of covariance. Completing ANOVA while controlling the effects of one or more covariate
Multivariate regression: Multiple outcome variables are modeled as being predicted by the same set of predictor variables
Comparing the post-test outcomes of treatment and control group subjects in a randomized post test only control group design
The design is a one way ANOVA and the statistical test is a Student's t-test (or t-test), which examines whether the means of the two groups are statically different from each other or whether one group has a statistically larger (or smaller) mean than the other
null hypothesis (the treatment group) and alternative hypothesis (the group without treatment). The goal of all statistical tests is to reject the null hypothesis