Exam #1 Flashcards
Summation of x divided by n
mean
Summation of (x- pop. mean) squared Summation of (x- sample mean) squared
Sum of squares (ss)
SS divided by N
ss divided by N-1
variance
square root of variance squared
standard deviation
X - pop mean divided by variance
X - sample mean divided by variance
z score of individuals
sample mean - population mean divided by (variance divided by square root of sample size)
z-score of means
Nominal
categorical
ordinal
rank order
interval
equal distance between measurements
rational
meaningful zero
Kurtosis
peakedness of the distribution
lepokurtosis
a lot of scores in the middle
platykurtosis
flat
When do you use the median?
- skewed/non normal
- undetermined values (SAT scores)
- open ended items (1,2,3, >4)
- ordinal
When do you use a bar graph?
Nominal (qualitative) (categorical)
when do you use a histogram?
interval or ratio (quantitative)
What effects variability?
- outliers
- sample size if really small
- stability under sampling
- open ended distributions
SS interpret
Summed squared distance from the mean
variance interpret
typical squared distance from the mean
Standard deviation interpret
typical distance between an individual score and an average score
sampling error
error between a sample statistic and the corresponding population parameter
distribution of sample means
set of means from all the possible random samples of a specific size selected from a specific population
expected value of M
the mean of the distribution of sample means, equal to the population mean
standard error of M
standard deviation of sample mean
variance(m) = variance/ square root of n
Central Limit Theorem
normal is n=30 or more
what is standard error determined by?
(1) the size of the sample and
(2) the standard deviation of the population from which the sample is selected
Law of large numbers
states that the larger the sample size (n), the more probable it is that the sample mean is close to the population mean
Use of a sample not randomly selected in an experiment
limits the degree to which the results can be generalized to a population
We generally like the standard deviation when we are trying to describe a sample of data because
it is expressed in units of the raw metric
SS definition
the sum of the squared deviation
variance definition
the mean squared deviation
Standard deviation definition
square root of the variance and provides a measure of the standard distance from the mean
mean definition
the sum of the scores divided by the number of scores
