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Statistics 1+2 (important concepts)

This class was created by Brainscape user Benthe van de Garde. Visit their profile to learn more about the creator.

By: Benthe van de Garde
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Decks in this class (13)

Lecture 1: Introduction to Statistics
Constructs,
Variables,
4 kinds of measurement levels
12  cards
Lecture 2: Probability Distributions
Frequency distributions,
The,
The standard normal distributions
11  cards
Lecture 3: The Sampling Distribution
Central limit theorem,
The standard error,
Confidence interval
4  cards
Lecture 4: Hypothesis testing
Hypothesis testing,
Equality hypotheses vs inequality...,
Fisher s philosophy on hypotheses
12  cards
Lecture 5: Linear Regression
General linear model,
Bivariate linear regression,
Predictor
13  cards
Lecture 6: Sum of Squares
Sum of squared errors,
Residuals,
Goodness of fit
11  cards
Lecture 7: Binary Predictors
Binary variables,
Regression with binary predictors,
Dummy coding
9  cards
Lecture 8: ANOVA
Caeg,
Between group sum of squares,
Within group sum of squares
7  cards
Lecture 9: Multiple Regression
Multiple regression,
Multiple regression formula,
Centering predictors
14  cards
Lecture 10: Nested models
Nested models,
Incremental f tests,
Hierarchical regression
6  cards
Lecture 11: Interaction
Interaction,
Regression equation with interaction,
When would you use interaction
7  cards
Lecture 12: Reliability and Validity
Observed vs latent constructs,
Measurement error,
Contra indicative items
13  cards
Lecture 13: Dimension Reduction
Principal components analysis pca,
Exploratory factor analysis efa,
Confirmatory factor analysis cfa
12  cards

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Statistics 1+2 (important concepts)

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