[L3] Samples, Populations, and the Normal Distribution Flashcards
In ___, we need to make sure, as far as
we can, that our sample is an unbiased and representative
sample of our population.
Inferential Statistics
we also need to make sure that our sample is ___
enough.
large
___– the “gold standard” to which other
sampling techniques aspire.
Random Sampling
Two Conditions for Random Sampling to be satisfied:
equi-probability and independence
every member of the population
must have an equal chance of being selected.
Equi-probability –
– the selection of any one member of the
population should not affect the chances of any other
being selected.
Independence
In practice it is very
___ to carry out RS!
difficult
Random Sampling is
virtually impossible
sampling methods
Volunteer sample
Snowball sampling
Purposive sampling
Convenience sampling
The Importance of the Normal Distribution
Many variables that can be measured on a continuous
scale are (approximately) normally distributed.
* Many statistical tests make the assumption that our data
are normally distributed.
Many ___ that can be measured on a continuous
scale are (approximately) normally distributed.
variables
The area under the curve is equal to the ___
number of people
in that area.
Where we have a histogram represented as a line chart,
with continuous variable on the x-axis (and where the yaxis
represents the frequency density), we can calculate
the number of people who have any score, or range of
scores, by calculating the ____
area of the chart.
Many ____ make the assumption that our data
are normally distributed.
statistical tests
The Normal Distribution goes on to
___ in each
direction.
infinity
There is no _
_
_
__ to the x-axis, on a normal
distribution plot, at least in theory.
beginning and end
The great advantage of a normal distribution is that if you
know (or can estimate) two values
__
_ you know everything there is to know about
it.
(Mean and Standard
Deviation),
A score that is presented in terms of the number of
standard deviations above the mean is called a
__
z-score.
A score that is presented in terms of the number of
___ above the mean is called a z-score.
standard deviations
To calculate a z-score, we use the formula:
__
z = score – mean / σ (standard deviation)
A z score is a transformed score that designates how many
___ the corresponding raw score is
above or below the Mean.
Standard Deviation units
– process by which the raw score is
altered
Score transformation
The z transformation results in a distribution having a
____
Mean of 0 and an SD of 1.
Z scores allow us to determine the ____ any score in the
distribution.
number or percentages
of scores that fall above or below