stats 2

sampling distribution via hypothesis testing

Statistics have a predictable distribution called a sampling distribution. The
sampling distribution allows us to quantify the variability in sample statistics.
This allows us to calculate a p-value, which is the probability of observing a test
statistic

to find an increase in y with a given x

ONLY do mx part of equation
ex: given y = 3 + 5x; this indicates that the value of x increases by 4, the predicted value of y would INCREASE BY: 20 (5 x 4)

when want to compare outcomes

ex: changes in cholesterol from day 1 and day 7 on medicine used a paired difference t-test for the change in cholesterol

top 25%

#NAME?

first quartile

lower 25%, take subject number (n) divide by 4 take that number and find where the results are which is your answer

if add one point to data

mean and median both increase, SD unchanged unless score is multiplied or divided

sampling distribution of a stat

the distribution of values taken by a statistic in ALL possible samples of the same size from the SAME population

if do any manipulation of any kind and not NATURAL

experiment

again when ADD # to all subjects

mean and median increase by that # and SD is unchanged

remember with hypothesis testing doing differences

double check greater than or less than if want second variable to be higher than first, will be LESS then NOT GREATER

chance problems

use basic standard z scores,
ex: P (x>10)
(P 13> x <14) --> P(Z<0.5) - P(Z<0.25) {upper value - lower value of p score)

chance problems w/ n included

find equation on sheet that incorporates all variables
same equation but as the divider = SD /square root of n

b1

m in the equation, slope

two sided with z

(1-p value) x 2

LINEAR REGRESSION

NOT APPROPRIATE IF DATA IN SCATTER PLOT HAS A CURVED RELATIONSHIP

population of interest

group of everyone w/ or w/out what you're looking at

parameter of interest

people who have w/e you are looking for

outliers

have a greater impact on the mean than the median

normal distribution

mean falls w/in the middle of the max - min range