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38 Cards in this Set

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What is an Eigenvalue?

The standard deviation squared + added...?

What is PDF?

Probability Distribution Function. When integrated over a set of numbers A, will give prob. of X in A.

What is a PMF?

Probability Mass Function. Probability that a discrete random variable is equal to some real value.

What is a CDF?

Cumulative Distribution Function. Probability that a random variable is less than or equal to a certain real number.

Describe Central Limits Theorem.

Given a large sample size, the distribution of means will be normal. Std error works b/c of Theorem. As we approach infinity, looks normal.

What is a random variable?

Variable independent from samples what we assign any number or you don't know the number.

What is meant by 'power'? Name the 5 components.

1-beta. 5 Components: alpha, beta, delta/effect size, n/sample

2 Rules of AIC

1. Choose lowest value.


2. If within 2 units, use less parameters

Covariance vs correlation

Correlation is standardized covariance. Covariance is a measure of correlation.

What is a linear model?

Predicting variable by multiplying parameters.

Anova vs Ancova

Anova: treating parameters of interest as last variable


Ancova: parameters are NOT multiplied by each other

What are the parameters of binomial, poisson, uniform, and normal distributions?

Binomial: n (sample), p, q


Poisson: lambda (mean)


Uniform: a (min), b (max)


Normal: Mew (mean), Sigma (s.d)

Definition of parameter.

Describes population. Truth. You never know parameters true values of full population.

Definition of statistic.

Estimate is parameters. Ex: slope, correlation, t-score

What is an anova test?

Only tells if groups are different. Need to do post-hoc test. Tukey HSD most common.

T-test equation (hypothesis testing)?

[(delta)mean-theta]/std error

What correction to use for data?

Bonferroni: more conservative


Holm: more liberal

What describes shape of distributions: t, F, chi-squared

t: df


F: df1, df2


Chi-squared: df

What parameter describes chi-squared distribution? Draw it.

Degrees of freedom. More df = steeper distribution.

Describe F distribution.

Parameters: df1, df2. Looks like ch-squared distribution. Approaches infinity, looks normal.

Definition of p-value

Probability of finding observed results if null were true. How valuable is the data.

What are standardized beta values?

Slope: 2 parameters measured in different values. Standardized slopes to see which slopes are important.

Definitions of mean, median, and mode.

Mean: average


Median: middle


Mode: most

Definitions of standard deviation and range.

Standard deviation: Avg spread of data points around the mean. Also determines how wide your curve is.


Range: difference btwn largest and smallest values

Binomial: Parameters, Dis or Con?, Type of data?

Parameters: n, p, q


Discrete


Given a probability of something happening, is this gonna happen?

Poisson: parameters, Dis or Con?, Type of data?

Parameters: lambda (mean)


Discrete


Concerned w/ numbers or counts. Used for rare events.

Uniform: parameters, Dis or Con?, Type of data?

Parameters: a, b (min, max)


Can be continuous (cdf) or discrete (pmf)


Constant probability.

Normal: parameters, dis or con?, Type of data?

Parameters: mew, sigma/stdev


Continuous


Data that has a mean and standard deviation. Bell-shaped curve

How do you calculate standard error?

Stdev or sigma/sqrt(sample size)

How do you calculate the 95% Confidence Internal?

Mean +/- 1.96*(stdev)

How do you calculate the coefficient of variation?

(Stdev/mean)*100=%

How do you calculate standard deviation?

Sqrt((1/N) Epsilon (xi-mew)^2)

How do you calculate variation?

Average squared deviation from the mean

How are t, F, and chi-squared distributions related?

Uses df for distribution shape. Both analyze variance.

Difference between binomial and poisson glm.

Poisson is predicting occurrence based on predictor level. Binomial is predicting events based on predictor level.

When to use factorial anova?

To compare means of 2 groups

When to use random effects?

If we think levels we observe in that group too be samples from a larger population

When to use go glm?

When there's a relationship between variables and accounts for error.