Introduction and Review
A Guide to Stats
Univariate and Bivariate
Screening the Data Part 1
Screening the Data Part 2
100
What are two types of statistics?
What is descriptive and inferential.
100
What is multi-level modeling used for?
What is to analyze nested data.
100
A statistical tool used to predict the value of a variable given the value of a related variable.
What is linear regression.
100
Name two ways to handle missing data.
What is delete cases and estimate the missing data.
100
Which is worse, data missing at random or systematically?
What is systematically because that means it is related to the DV.
200
What affects power?
What is sample size, alpha level, effect size, and amount of error.
200
What is the difference between MANOVA and MANCOVA?
What is there are one or more covariates present in a MANCOVA.
200
The effect of one IV at a single level of another IV (in a factorial ANOVA).
What is simple main effect.
200
What is the difference between univariate and multivariate outliers?
What is univariate is an extreme value on one case while multivariate is an unusual combination of scores on two or more variables.
200
In which direction does a negatively skewed data distribution have a tail?
What is left.
300
List and explain the 3 strategies of behavioral research.
What is descriptive (polls), experimental (random assignment and manipulation of IV), and non-experimental (levels of IV not manipulated).
300
How many variables can be assessed in a bivariate r?
What is two?
300
A correlation coefficient that indicates no linear relationship between two variables.
What is zero.
300
What are 3 types of missing data
What is missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR).
300
Define leverage.
What is how far an observed value is from the mean.
400
What steps must be taken when performing an analysis on SPSS?
What is 1) selecting reliable and valid measurements 2) choosing an appropriate computational program 3) using the program correctly 4) interpreting the output.
400
What is used to compare the mean of a variable from your sample with that of a known population?
What is a one-sample t-test.
400
A statistic that indicates the difference between a sample mean and population mean (in units of standard deviation).
What is the z-score.
400
What is the difference between listwise and pairwise?
What is listwise is more extreme and deletes cases which do not have data on all variables and in pairwise cases are omitted only if they do not have data on a variable used in the current calculation.
400
Name one way to estimate missing data and describe it.
What is mean substitution (using individual mean for missing data), group mean substitution (reduction in within-group variance can make differences among variable spuriously large), or regression (using non-missing data to predict the values of missing data).
500
What are 3 types of discrete variables and 2 types of continuous variables?
What is quantitative/interval (continuous) and qualitative, nominal, and categorical (discrete).
500
Which method/s can be used when predictors are continuous and outcomes are discrete?
What is a logistic regression.
500
What is the formula for the F statistic used in an ANOVA?
What is the ratio of between-group variance to within-group variance or between-group variance/within-group variance.
500
What is mean substitution?
What is using the individual mean for missing data.
500
Define kurtosis.
What is the peakedness of a distribution.
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