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26 Cards in this Set
 Front
 Back
Theory and methodology for study design and for describing, analyzing, and interpreting data.

Statistics


Each member of the population has an equal chance of being chosen

Simple random sample


Population is divided into nonoverlapping groups (called strata). Sample is then choses from these groups

Stratified random sample


Random sampling with a system. Starting point chosen at random and then samples are chosen at regular intervals after.

Systematic sample


Units to be sampled are chosen in clusters close to each other. Within clusters, units are chosen by simple random sampling

Cluster sample


Subjects are convenient (next 20 patients in your clinic)

Convenience sample


Data that is categorical and discrete

Qualitative data


Data that is numeric and continuous

Quantitative data


Median

Midpoint


Mode

Value that occurs most frequently
Unimodal and multimodal 

Measure of the variability in scoring

Standard deviation


The square of the standard deviation

Variance


Middle of the box plot

Median


Box contains what percentage?

25th percentile to 75th percentile


Whiskers of box plot depict?

The highest and lowest scores.


Zscore

The standard deviation above or below the mean


Parameter

The value calculated in a population


What can standard normal deviation do?

1. With a mean of zero and standard deviation of one
2. Allows standard scores to be calculated (zscores) 3. Converting scores to percentile ranks 

Sample size

1. Greater the sample size, more likely the distribution will look like the true distribution in a population
2. With increased sample size, the spread (variation around the mean) decreases 

A single number, like the mean

Point estimate


A range of numbers that describe uncertainty due to play of chance

Interval estimate


A range of values that has a specified probability of containing the parameter being estimated

Confidence interval


Measure of correlation, Pearson's r

r = 1
r = +1 r = 0 

Type I error

False Positive, when you reject the null hypothesis when it is true


Type II error

False negative, when you accept Ho when Ho is false


Power

1Beta
