Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
38 Cards in this Set
 Front
 Back
interval data

data with a numerical value, absolute difference between 2 values can alway be determined by subtraction


nominal or categorical data

data not measured on an interval scale (nonnumeric), such as gender, state of birth or presence of disease


ordinal data

data which is categorical, but has inherent ordering. Example: level of health (excellent, good, fair, poor)


variance

dispersion about the mean. measured as the average squared deviation from the mean. variance=sum of (value associate with member of populationpopulation mean)^2/number of population members


standard deviation

square root of the variance (square root of the average squared deviation from the mean)


normal (Gaussian) distribution

bellshaped curve. ~68% of population within 1 SD, 95% within 2 SDs


stratified random sample

population divided in subpopulation (strata) prior to random sampling


bias

systematic difference between the characteristics of the sample and the population


two ways to obtain data

experimental and observational


sample standard deviation (equation)

s=√(Σ〖(XX ̅ )〗^2/n1)


standard error of the mean (SEM), (xbar subscript xbar)

standard deviation of all possible sample means, measures the uncertainty in the estimate of the mean


As the sample size from the population increases, the standard error of the mean (SEM) ______.

Decreases


The more variable the total population is the standard error of the mean (SEM) _______.

Increases


Term which states:
normal distribution of sample means indepent of the the original population mean value of all sample means=mean of original population SD of all possible means of samples (SEM) depends on both the SD of the original population and the sample size. 
Central Limit Theorem


median

the value that half the population falls below, 0.5(n+1) observation


25th percentile point (lowest quartile) formula

0.25 (n+1) observation


interquartile range

the interval between the 25th and 75th percentile points


percentile which corresponds to mean + 0.67 standard deviation (in a normal distribution)

75th percentile


Percentile which corresponds to mean + 1 standard deviation (in a normal distribution)

84th percentile


Percentile which corresponds to mean + 2 standard deviations

97.5the percentile


Null hypothesis

Hypothesis that there is no effect introduced by a treatment


Analysis of variance

Class of related procedure to test for differences between groups


Parametric statistical methods

Procedures comparing groups based on population parameters within normal distribution (i.e. mean, standard deviation)


Nonparametric statistical methods

Procedures comparing groups based on frequencies, ranks or percentiles


Formula for variance within the treatment groups

s_within^2=1/4(s_control^2+s_(treatment 1)^2+s_(treatment 2)^2+s_(treatment 3)^2),
S^2 is variance, for study with a control and 3 treatment groups 

If the null hypothesis is true, what is the relationship between the withingroups variance and betweengroups variance?

About equal (both are estimates of the same population variance).


About equal (both are estimates of the same population variance).

F=population variance estimated from sample means/population variance estimated as average of sample variances (F=s_between^2 / s_within^2)


What is a “big” F?

There is a larger than expected variability within the samples, so rejection of the null hypothesis that all the samples were drawn from the same population. Report a Pvalue < 0.05.


What is single factor or one way analysis of variance?

Analysis of variance with one factor distinguishing different experimental groups.


Degreeoffreedom parameters

Numerator =Number of samples (m) minus 1, Denominator = number of samples (m) times 1 less than the size of each sample. Vn=m1. Vd=m(n—1)


t ratio formula

t= difference in sample meand/standard error of difference of sample means, or
t=(mean1mean2)/SqRt((s^2_one/n)+(s^2_two/n)) 

pooled variance estimate

s^2=1/2(s^2_one + S^2_two)


twotailed t test

Statistical test in which extreme values of t that lead us to reject the null hypothesis lie in both tails of the distribution (i.e. both ends of the bell curve)


When determining the critical values of t (either calculating or using a table) what information must be known?

Degrees of freedom (Ʋ). This is determined by sample size n. Ʋ=2(n1).


How is the ttest and analysis of variance related?

They ttest is simply a special case of analysis of variance applied to two groups.


When the experimental design involves multiple groups should a ttest or analysis of variance be used?

Analysis of variance. Ttest is designed only for 2 group analysis.


What is the Bonferroni t test?

First perform an analysis of variance to test the overall null hypothesis. then use a multiplecomparison procedure to isolate the treatment(s) producing the different results.


What is the Bonferri inequality formula?

αT < kα, or αT/k < α. k is the number of statistical tests. Cutoff value is α. (i.e. combined ttest cutoff value is no more than k times α.
