STATS 1.1-1.2

data

info that comes from observation, counts, measurements, or responses

statistics

science of collecting, organizing, analyzing and interpreting data in order to make decisions

populationsample

types of data sets

population

all outcomes, responses, measurements or counts of interest

when a population isn't practical

when do we use a sample

sample

subset of population

to make reasonable guesses

what do we use a sample for

Parameter and Statistic

types of sample

parameter

numerical data abt a population

statistic

numerical data abt a sample

descriptive and inferential

branches of statistics

descriptive statistics

describes or presents data

inferential statistics

makes educated guesses abt a population

qualitative and quantitative

two types of data

qualitative

attributes, labels, and numbers that act as labels

hair color, species, jersey number, SSN

examples of qualitative data

Quantitative data

numerical in measurements

age, number of pets, time and temp

examples of quantitative data

4

how many levels of measurement are there

nominalordinalintervalratio

levels of measurement

nominal ordinal

what levels of measurement are qualitative

intervalratio

what levels of measurement are quantitative

nominal

a non meaningful list

ordinal

list that has meaningful order

interval

time and temp zero means 0 (its still a number)

ratio

measures weight zero does not exist

observationexperiment simulation survey

methods of data collection

observation

observe and measure characteristics of a sample hands off

experiment

treatment is applied to a sample group and responses are measured hands on

simulation

uses mathematical or physical models to reproduce desired conditions

crash test danger

when are simulations used

survey

ask ppl questions

census sample

types of survey

census

survey of entire population

sampling

survey of a sample

control randomization replication

3 elements of a good experiment

cofounding variable

experiment cant tell difference betweenterm-37 the effects of different factors on a variable

placebo effect

subject reacts favorably bc they think they're being given a treatment but it was a placebo

Hawthorne effect

ppl change their behavior for an experiment

blinding doubt blinding

how to get rid of bias

blinding

subjects dont know which group they are in

double blinding

neither the subjects nor the experimenter knows which group is which

randomization

The process of randomly assigning subjects to different treatment groups

completely randomized design

subjects are assigned groups through random selection

randomization block design

divide group w similar characteristics then randomly assign subjects to treatments and control groups

matched pair designs

subjects are paired accordingly to similarities then one is placed in treatment and other in control group

replication

repetition of an experiment using a large group of subjects

data is more reliablemore confident

benefits of using a large sample size

bias

a systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others

biased question biased sample

2 types of bias

bias question

What can I get you for dessert this evening?

bias samples

sample that doesnt rep a whole population

Sampling Techniques

Simple random samplestratisfiedcluster systematicconvenience

simple random sample

every member of a population is assigned a number, then numbers are randomly,ly selected

stratified

population is divided into a strata them random samples are taken from each strata few from each

strata

subset of a population

grades

example of strata

cluster

population is divided into strata but then randomly select some groups and choose everyone all from few

systematic

each member of a population is assigned a number then members are chosen at random intervals every 10th, 5th, 3rd

convenience

compromised of available members of the population, select people the are conveinent