intro to statistics

formula for confidence interval

sample mean +or- t critical (SD/sqrtn)

as sample size increases

standard error of the mean decreases

As standard deviation increases...

standard error increases

assumptions for one sample t test

normality, random sampling, independent observations

confidence interval widens as confidence level increases

because t critical value will increase, the higher the confidence level the larger the margin of error.

o

population standard deviation

s

sample standard deviation

the mean of the standard normal distribution is

always 0

the mean of the normal distribution

not always 0

large degree of freedom

thinner distribution

as n gets larger

t critical will get smaller

For a normal model, about what percentage of scores fall within 3 standard deviations of the mean?

99.7%

if extreme values change

it is possible for the mode to change data value occurs more frequently after the change

how to compute new mean after the addition of a value

multiply original n and mean, then add the new value. Then divide by new population size

affect of adding new value on large n vs small n

the addition of the same value to a smaller data set will effect the data more. EX: Dividing by 51 instead of 50 has less impact than dividing by 6 instead of 5

when the mean is greater than the median

skewed right, extreme upper values

When the mean is less than the median

skewed left

does removing extreme values have more effect on the mean or the median

more effect on the mean, extreme values do not effect median greatly

percent score

numeric, continuous

year of birth

discrete, numeric

t stat

compares two means

z score

distance from observation to the mean