Intro to Stats Flashcards

1
Q

population

A

complete collection of all indivs to be studied

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1
Q

sample

A

subcollection of members selected from a population

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2
Q

variables

A

characteristics about the population you want to learn about or measure

i.e height, weight, BP

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3
Q

parameter

A

mathematical description of some characteristic/variable for a population

i.e population mean

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4
Q

statistic

A

mathematical description of some characteristic/variable for a sample

same as parameter just with a sample instead

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5
Q

descriptive stats

A

used to summarize and describe characteristics of data numerically and graphically

i.e sample mean AND standard deviation for age of ER pts

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6
Q

inferential stats

A

used to make conclusions/inferences about populations

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7
Q

types of data

A
  1. categorical- aka qualitative, consists of names or labels
  2. quantitative- aka numerical, numbers representing counts or measurements
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8
Q

subtypes of quantitative

A
  1. discrete- number of possible values is finite/countable
  2. continuous- numerical, infinitely many possible values w/ some continuous scale
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9
Q

measurement

A

another way to classify data to use scales of measurement

aka assignment of values to outcomes

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10
Q

scales of measurement

A

nominal
ordinal
interval
ratio

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11
Q

nominal level

A

names/labels/categories that CANNOT be ordered

least precise level of measurement

i.e f/m gender, y/n responses, survey, vitamins

categories only

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12
Q

ordinal level

A

can be ordered
gaps b/t data cannot be determined/are meaningless

i.e pain scale

categories with some order

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13
Q

interval level

A

ordered
gaps b/t data ARE meaningful
NO natural zero

i.e temperature scale, pH values

ordinal + meaning aka differences but no natural starting pt

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14
Q

ratio level

A

interval + natural zero aka 0= none

most precise scale of measurement

i.e. heart beat, blood pressure

difference and natural starting pt

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15
Q

experiment

A

apply some treatment then observe its effects on subjects

subjects called experimental units

gold standard
random assignment of subjects

16
Q

observational study

A

observing and measuring specific characteristics w/o modifying subjects

aka no manipulation

17
Q

probability sampling

A

selecting members from a pop so that each has a known chance of being selected

18
Q

simple random sample

A

indiv chosen randomly and entirely by chance aka** same probability** of being chosen at any stage during sampling process

via random generator on computer

19
Q

systematic sampling

A

select some starting point and then select every kth element in pop

20
Q

stratified sampling

A

subdivide pop into at least two different subgroups that share same characteristics

then draw sample/stratum from each subgroup

21
Q

cluster sampling

A

divide pop area into sections/clusters

randomly select some of clusters

choose all members from selected clusters

22
Q

multistage sampling

A

collect data by using combo of basic sampling methods

pollsters select a sample in diff stages- each stage might use diff methods of sampling

23
Q

non-probability sampling

A

often biased so results not necessarily valid

voluntary response sample or self selected

write in or call ins

24
convenience sampling
results that are easy to get
25
key concepts of data presentation
organize and summarize with frequency distribution to understand nature of data
26
frequency distribution/table
shows how data is partitioned among several categories/classes list categories w/ number of data values in each can be relative (%) or cumulative
27
histogram
graph w/ bars of equal width drawn adj to each other/without gaps x axis = classes of quantitative data values y axis= frequencies w/ heights of bars corresponding to frequency value | can be relative (%) too
28
frequency polygon
line segments connected to points directly above class midpoint values can be relative too (proportions of %)
29
ogive
line graph w/ cumulative freq