Stats Flashcards
Statistics
Descriptive and inferential
Descriptive stats
Describing and summering data
Talk about main features
What do we get out of data?
Inferential stats
Putting meaning onto data
Test hypothesis
Make predictions and conclusions based on data
Look at differences and relationships
3 parts of descriptive
Central tendency, variability, distribution
Central tendency
Where central is
- mean, median, mode
Mean
Most stable, takes all data points into consideration
Variability
How data Varys around Central
- standard deviation, variance, range
Distribution
How data is distributed
- quartile
- normal distribution
Kurtosis
Frequency of outliars
Measure of I now much tail you have
Mesokurtic
Normal kurtosis
Platykurtic
Long kurtosis
Leptokurtic
Short kurtosis
Positive skew
Left
Negative skew
Right
How to figure out if 2 continuous variables are related or associated
Run correlation test
(Pearson’s)
How to figure out if 2 categorical variables are related associated
Chi squared
Association or related between 1 outcome and more than 1 predictor
Logistic regression
Relation and association between > 1 outcome and >1 predictor
Multiple regression
Relation and association with Predicting loading on > 2 outcomes
Factor analysis
Structural equation modeling and path analysis
Beta heights
higher B, stronger relationship
T-test asses differences
Between 1 independent variable that’s categorical and a dependent variable that’s continuous
ANOVA (analysis of valance) differences between
1 Ind w/ > 2 groups and 1 dep continuous
Repeated measures ANOVA
Have anova at multiple times (usually longitudinal studies)
Asses changes over time
Manova asses differences between
1 Ind categorical w/ >2 levels and 2 dep continuous
ANCOVA
Anova controlling for effects of another variable
Normal curve
Data distributed naturally
Z formula
X- u / o
Z tables
Give percentile based on Z score
Positive Z
Above average
Negative Z
Below average
