Stats Chapter 1

Quiz on Monday

Statistics

science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data

analyze

….results of surveys using controlled experiements or operations to research quality control, estimation, and prediction

1. become better citizens and consumers

2. statistical understanding to perform jobs better

   1. to be able to conduct research in field, to make predicitions and forecasts

What are the 3 reasons why we learn stats?

variable

a characteristic or attribute that can assume different values

data

values that variables can assume

random variables

variables whose values are determined by chance

data set

a collection of data values

data value

aka datum, each value in a data set

population

all subjects being studies

census

when data is collected from every subject in the population

sample

a group of subjects from a population

should posess the same or similar characterstics of a population

Descriptive Stats

collection, organization, summarization, and presentaion of data "situation” (al)

inferential stats

generalizing from samples to populations, estimations, hypothesis tests, predicitions

qualitative and quantitative

2 types of variables

qualitative

catergories

quantitative

values, numerical

discrete and continuous

what are the two catergories of quantitative

discrete

counted, dots

continuous

measured, curves, or lines

nominal, ordinal, intervals, and ratio

what are the 4 levels of measurement?

nominal

qualitative, cannot be ranked or orded

(zip code, social security numbers)

ordinal

qualitative, can be put in order or ranked

ex: survey, football rankings, shirt sizes (s,m,l)

intervals

quantitative, can be ranked or ordered

*NO meaningful values for 0

ex: calendary years, temperature

ratio

ranked or ordered, quantitative

0 means 0, nothingness

(ex: distance, volume, quantity of books, household size)

4 sampling methods

random sampling, systematic sampling, stratified sampling, cluster sampling

to avoid bias

we avoid making data lean to a side unwanted

random sampling

(like a lottery) assign numbers to subjects in the population and pick random numbers/values

systematic sampling

still number the subjects in the population but you pick every kth subject

stratified sampling

goup or cluster the population according to characters, then take a sample from each group

cluster

looking at a population that is divided into groups that are more geographic

sampling errors

samples are not perfect representation of a population

non-sampling error

data is collected erronesly (contains errors)

observational studies

observe what is happening or what has happened and dra conclusions

experimental studies

researches manipulate one variable of interest and determine how that manipulation influences other variables

independent variable

can be manipulated, explained

dependent variable

variables being measured, the outcome or resultant

experimental studies

the positives are random selection and control group, along with the independent variable being able to be manipulated

negatives are that it is done in a lab, not in a natural setting.
Hawthorne Effect - behavior changes because of participation
confounding or (lurking) variables are not observed or recorded

observational studies

the positives is that it happens in a natural setting, used when manipulation is unethical or unsafe, variables can be manipulated

the negatives, the cause and effect cannot be shown, it can be expensive and time consuming, accuracy can be poor (of data)

misuse of studies

statements used to sell products
too small, not random, misinterpretation

Detatched Statistics

no comparison is made