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Complete the desk of statistical techniques over the course of the week and describe what is the difference between the extraordinary techniques. Make sure you use the discussion board to ask questions and to clarify techniques. (I performed the Independent Samples t-test to start the process; I expect the terms to be a bit difficult, so I truly want this discussion to be a learning experience)Here are some definitions:IV=Manipulation; Levels of IV=how many groups; Fixed=participants take on one cost (i.e., group 1 or group 2);Random=participants can take on any value (e.g., quantity of depression).Between Subjects=different people in each group (fixed) or different amounts of IV (random)Within Subjects=same people measure repeatedly# of DVs=how many consequences are used in the statistical technique.
Technique
Independent Variable
Dependent Variable
Definition
# of IVs
Fixed or Random
# of levels in IV (If Fixed)
Between or Within Subjects
# of DVs=how many outcomes are used in the statistical technique.
Technique
Independent Variable
Dependent Variable
Definition
# of IVs
Fixed or Random
# of levels in IV (If Fixed)
Between or Within Subjects
# of DVs
Fixed or Random
One Sample t-test
Tests whether the value of a sample differs from a hypothesized value
0
N/A
N/A
N/A
1
Random (outcome can take on any value)
Independent Samples t-test
compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different
1
fixed
2
between
1
random
Definition
# of IVs
Fixed or Random
# of levels in IV (If Fixed)
Between or Within Subjects
# of DVs
Fixed or Random
Paired Samples t-test (AKA repeated measures t-test or dependent measures t-test)
Tests whether the mean difference between two sets of observations is zero
1
Fixed
2
Within
1
fixed
One-Way ANOVA
Tests whether there are any statistically significant differences between the means of two or more independent (unrelated) groups
2
Random
Between
1
Random
Repeated Measures ANOVA
test to detect any overall differences between related means for related groups
1
Random
Within
1
Fixed
Factorial ANOVA (can also be called a Mixed Factors Factorial ANOVA)
Tests the differences on a continuous dependent variable between two or more independent discrete grouping variables
2 or more
Random
Between
1
fixed
Simple Regression
allows us to summarize and study relationships between two continuous (quantitative) variables
1
Fixed
1
Between
1
Fixed
Multiple Regression
used when we want to predict the value of a variable based on the value of two or more other variables
1
Fixed
1
Within
2 or more
Fixed
Logistic Regression
Describes and explains the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables.
1
Random
1
Between
N/A
N/A
Examine sample means to determine the main effect of each factor (and the interaction of both factors) on differences in DV
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