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STA 126 > Unit 1 > Flashcards

Unit 1 Flashcards

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1
Q

population

A

entire group to be studied

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2
Q

sample

A

subset of the entire group

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3
Q

descriptive statistics

A

revolves around organizing and summarizing data
(showing data through numerical summaries, tables, and graphs)

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4
Q

statistic

A

numerical summary based on a sample

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5
Q

inferential statistics

A

extends results from sample to population
(measures reliability of the result)

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6
Q

parameter

A

numerical summary of a population

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7
Q

process of stats

A
  1. identify research objective
  2. collect data to answer question(s)
  3. describe the data (results)
  4. draw conclusions from data
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8
Q

variables

A

characteristics of individuals within population

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9
Q

types of variables

A
  • qualitative (categorical)
  • quantitative
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10
Q

qualitative (categorical) variables

A

allow for classification of individuals based on some attribute or characteristic (ex: checking account numbers)

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11
Q

quantitative variables

A

provide numerical measures of individuals (ex: BMI)
(values of these variables can be added or subtracted)

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12
Q

2 types of quantitative variables

A
  1. discrete
  2. continuous
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13
Q

discrete variable

A

type of quantitative variable that has either a finite number of possible values or a countable number of possible values

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14
Q

continuous variable

A

quantitative variable that has an infinite number of possible values it can take on and can be measured to any desired level of accuracy (ex: decimals, fractions)

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15
Q

data

A

list of observations a variable assumes (ex: age is a variable, observations 21, 44, etc. are data)

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16
Q

qualitative data

A

observations corresponding to a qualitative variable

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17
Q

quantitative data

A

observations corresponding to a quantitative variable

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18
Q

discrete data (type of quantitative data)

A

observations corresponding to a discrete variable

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19
Q

continuous data (type of quantitative data)

A

observations corresponding to a continuous variable

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20
Q

types of levels of measurement of a variable

A
  • nominal level
  • ordinal level
  • interval level
  • ratio level
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21
Q

nominal level of measurement

A

takes the form of labels, categories but these categories are not ranked (not in specific order)

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22
Q

ordinal level of measurement

A

has properties of the nominal level of measurement but categories are ranked, in specific order

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23
Q

interval level of measurement

A

has properties of ordinal level of measurement but differences in values of the variable have meaning
- value of zero does not mean absence of quantity
- addition and subtraction can be performed on variable values

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24
Q

ratio level of measurement

A

has properties of interval level of measurement but the ratios of the values of the variables have meaning
- value of zero indications absence of quantity
- multiplication and division can be performed on variable values

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25
response variable
variable affected by explanatory variable
26
explanatory variable
value of variable usually varied too see its effect on the response variable
27
observational study
measures the value of the response variable without attempting to influence the value of either the response or explanatory variables
28
designed experiment
- assigns individuals in a study to a certain group - intentionally changes the value of explanatory variable - records value of response variable for each group
29
confounding
occurs when the effects of two or more explanatory variables are not separated
30
lurking variable
explanatory variable that was not considered in a study but affects the value of the response variable in study
31
confounding variable (confounder)
explanatory variable that was considered in a study whose effect cannot be distinguished from a second explanatory variable in study
32
types of observational studies
- cross-sectional - case-control - cohort
33
cross-sectional studies
observational studies that collect information about individuals at a specific point in time, or over a very short period of time
34
case-control studies
studies are retrospective and individuals who have certain characteristics are matched with those that do not
35
retrospective studies
require individuals to look back in time or require the research to look at existing records
36
cohort studies
*these studies are prospective - first identifies a group of individuals to participate in study (cohort) - cohort is then observed over a long period of time - over this time period, characteristics about the individuals are recorded
37
prospective studies
data is collected over time
38
census
list of all individuals in a population along with certain characteristics of each individual
39
steps for obtaining a simple random sample
1. obtain a frame and number the individuals 1 to N 2. use a random number table, graphing calculator, or other software
40
simple random sample
all individuals have equal probability of getting randomly selected
41
how to use random table*
1. look at N (select numbers based on how many digits are in N (ex: 3 digit numbers if N = 753) 2. close eyes and point to a random number 3. use row, column to generate number (if numbers are out of range, skip to next row, same column)
42
frame
list of all the subjects in population to be studied
43
stratified sample
- separates population into strata - then obtains a simple random sample from each stratum *the individuals within each stratum should be homogeneous in some way
44
homogeneous
similar
45
strata
nonoverlapping groups
46
systematic sample
obtained by selecting every kth individual from the population *first individual selected is a random number between 1 and k
47
steps for obtaining systematic sample
1. approximate population size N 2. determine sample size n 3. compute k (k = N/n) and round to nearest integer 4. randomly select a number between 1 and k (p) 5. sample will consist of following individuals (p + (n-1)k)
48
cluster sample
obtained by selecting all individuals within a randomly selected collection or group of individuals
49
convenience sample
individuals in sample are easily obtained *be skeptical of results
50
multi stage sampling
obtaining samples using a combination of the techniques just presented
51
types of sampling techniques
- simple random sampling - stratified sampling - systematic sampling - cluster sampling - convenience sampling - multi-stage sampling (?)
52
bias
when results of the sample are not representative of population
53
types of biases
- sampling bias - nonresponse bias - response bias
54
sampling bias
means that technique used to obtain individuals in sample tend to favor one part of population over another
55
undercoverage (type of sampling bias)
when the proportion of one segment of the population is lower in a sample than it is in the population
56
nonresponse bias
when individuals selected to be in the sample who do not respond to the survey have different opinions fro those who do - can be improved through callbacks or rewards/incentives
57
response bias
when the answers on a survey do not reflect the true feelings of respondent - types: interviewer error, misrepresented answers, wording of questions, order of questions or words
58
data-entry error
leads to results that are not representative of the population - wrong inputting of data after collected *not technically result of response bias
59
nonsampling errors
errors that result from under coverage, nonresponse bias, response bias, or data-entry error
60
samplign error
error that results from using a sample to estimate information about a population - usually occurs because a sample gives incomplete information about population
61
experiment
controlled study conducted to determine the effect of varying one or more explanatory variables
62
factors
explanatory variables
63
treatment
any combination of the values of the factors
64
experimental unit (subject)
a person, object, or some other well-defined item upon which a treatment is applied
65
control gorup
serves as baseline treatment that can be used to compare to other treatments
66
placebo
innocuous medication that looks, tastes, and smells like the experimental medication
67
blinding
nondisclosure of the treatment an experimental unit is receiving
68
single-blind experiment
one in which the experimental unit does not know which treatment he or she is receiving
69
double-blind experiment
one in which neither the experimental unit nor the researcher in contact with the experimental unit knows which treatment the experimental unit is receiving
70
steps for designing an experimetn
1. identify the problem to be solved 2. determine the factors that affect the response variable 3. determine the number of experimental units 4. determine the level(s) of explanatory/predictor variables 5. conduct experiment 6. test claim
71
completely randomized experiment
one in which each experimental unit is randomly assigned to a treatment
72
blocking
- grouping together similar experimental units - then randomly assigning the experimental units within each group to a treatment
73
block
each group of similar individuals
74
randomized block design
used when the experimental units are divided into homogeneous groups (blocks) - with each block, the experimental units are randomly assigned to treatments
75
matched-pairs design
experimental design in which the experimental units are paired up - pairs are matched up so that they are somehow related - only two levels of treatment in this design
76
types of experimental designs
- completely randomized - randomized block - matched-pairs

STA 126 (1 decks)

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