Stats Unit 1 Chapter 1

Data

Collections of observations, such as measurements, genders, or survey responses

Statistics

The science of planning studies and experiments; obtaining data; and then organizing, summarizing, presenting, analyzing, and interpreting those data and then drawing conclusions based on them.

Population

Complete collection of ALL measurements or data that are being considered

Census

Collection of data from EVERY member of the population

Sample

SUBCOLLECTION of members selected from a population

Statistical significance

Result is very unlikely to occur by chance

No practical significance

Common sense says it doesn't make a big enough difference to justify treatment/ program

9 potential pitfalls of analyzing data

Misleading conclusions

Reported results

Small samples

Loaded questions

Order of questions

No response

Missing data

Precise numbers

Percentages

parameter

a numerical measurement describing some characteristic of a POPULATION

statistic

a numerical measurement describing some characteristic of a SAMPLE

quantitative (or numerical) data

consists of numbers representing counts or measurements (can be discrete (only integer values) or consistent)

categorical (or qualitative or attribute) data

consists of names or labels that are not numbers representing counts or measurements

correlation

variables are related through another variable, called the larking factor

nominal level of measurement

characterized by data that consists of names, labels, or categories only. Categories cannot be organized in an ordering scheme (do not make sense)

examples of nominal level of measurement

yes/no/undecided, political party, social security number

ordinal level or measurement

can be arranged in some order, but differences (obtained by subtraction) are meaningless

examples of ordinal level or measurement

grades (A-B=nothing), ranks (college #1-college#2=nothing)

interval level of measurement

can be arranged, differences are meaningful, do not have a natural 0 and 0 means it doesn't exist/ didn't happen

examples of interval level of measurement

O degrees F (there is no absence of temperature), 0 years (time did not begin in year 0), 0 earthquake = no earthquake happened

ratio level of measurement

can be arranged, differences are meaningful, has a natural 0 and 0 means none of the quantity is present

examples of ratio level of measurement

0 class time - there were 0 min of class time, 0 on a test - they got nothing right

outlier

outside of 3 standard deviations

unusual data

outside 2 standard deviations

random sample

each member of the population has an equal chance of being selected

simple random sample

a sample of n subjects that is selected in a way that every possible sample of the same size n has the same chance of being chosen

systematic sample

select some starting point, select every kth element in the population

convenience sampling

use results that are easy to get

stratified sampling

subdivide the population into at least 2 different subgroups so that the subjects within the same subgroup share the same characteristics (Age, gender), then draw a sample from each subgroup

cluster sampling

divide the population into sections (or clusters) then randomly select a cluster or two and use all members from the selected clusters

sampling error

sample was collected at random but result is not what a population shows

non-sampling error

a human error such as a computation error or not a proper method used

non-random sampling error

bad sampling

retrospective study

go back in time to collect data over some past period

cross-sectional study

data are measured at one point in time

prospective study

go forward in time and observe groups sharing common factors (like smokers)