Biostats, Central Limits And The Normal Curve

Front 1

the distribution sample mean will be approximately normal regardless of the distribution of values in the orginal population from which the samples are drawn.

Back 1

central limits theorem

Front 2

central limits theorem

the distribution sample mean will be approximately ------regardless of the distribution of values in the orginial population from which the samples are drawn.

Back 2

normal

Front 3

what does the sd of the collection of all possible means of samples of a given size (aka the standard error of the mean) depend on

Back 3

standard deviation of the orignial population

and the size of the sample

Front 4

sd vs standard error

Back 4

sd is for the individual

standard error is for the sampling distribution

Front 5

relative frequency probabilities are based upon ----- research or data that has determined the probability of an event

Back 5

past

Front 6

most important in central tendency

Back 6

mean

Front 7

mean is responsive to ----- position of each score

Back 7

exact

Front 8

the balance point of the distribution

Back 8

mean

Front 9

mean is the point about which the sum of ---- deviations = ---- devations

Back 9

negative

positive

Front 10

which is more sensitive to extreme scores

mean, mode, median

Back 10

mean

Front 11

when used w/ the ----, the mean is an indicator of skewness

Back 11

median

Front 12

the measure the best reflects teh total of scores

Back 12

mean

Front 13

if you have a distribution that's skewed to the r. can yo still base your decision on that

Back 13

no

will be an error

Front 14

if there's a true norm distribution what will equal the mean

Back 14

median

Front 15

what's the least sensitive to sampling fluctuations

Back 15

mean

Front 16

the point along the scale of scores taht divides the upper from the lower half

Back 16

median

Front 17

the median responds to the number of scores above or below, but not the --- location

Back 17

exact

Front 18

median is less/more affected by the extreme score

Back 18

less

Front 19

when is the median better than the mean

Back 19

w/ strongly skewed distributions

Front 20

median is not very useful beyond ------

Back 20

description

Front 21

which is easier to calculate w/ ordered observations

median or mean

Back 21

median

Front 22

which is more subject to sampling fluctuations

mean or median

Back 22

median

Front 23

which is the only stable measure w/ open ended distributions

Back 23

median

Front 24

does the median of the pop reflect the sample

Back 24

no

Front 25

what is mode most affected by

Back 25

size of class interval

Front 26

the mode is sometimes not a ---- point in the distribution

Back 26

unique

can be bimodal, etc

Front 27

mode is has little use beyond -----

Back 27

descriptive

Front 28

mode is the only measure suited for ---- data

Back 28

nominal

Front 29

if the mean is to the right of the median what's the skew

Back 29

positive

Front 30

if the mean is to the left of the median what the skew

Back 30

negative

Front 31

the mean of any set of z scores is always ----

Back 31

0

Front 32

the sd of any set of scores is always ---

Back 32

1

Front 33

the distribution of ------ has whatever shape is characteristecis of the set of raw scores from which they were derived

Back 33

z-scores

Front 34

the z score tells how many ---- the corresponding raw score lies above or below the mean distribution

Back 34

sd

Front 35

the z score has direct mean in terms of the ----- of an out come

Back 35

probablity