IR WEEK 1

Question 1

describe ways of knowing

Answer 1

scientific method, deductive reasoning, inductive reasoning, trial and error, authority, tradition

Question 2

includes deduction and induction in systematic empirical and controlled analysis

Answer 2

scientific method

Question 2

gather facts and observations without preconceived notions, facts about a sample leads to conclusions about about a whole

Answer 2

inductive reasoning

Question 3

start with a premise or known scientific principle, tie that premise in with other observations and make a conclusion

Answer 3

deductive reasoning

Question 4

keep trying until something works

Answer 4

trial and error

Question 5

turn to an expert

Answer 5

authority

Question 6

we accept certain truths as givens

Answer 6

tradition

Question 7

3 major parts of the research continuum

Answer 7

Descriptive, exploratory, experimental

Question 8

the researcher attempts to describe a group of individuals on a set of variables, to document their characteristics

Answer 8

descriptive

Question 9

researcher examines a phenomenon of interest and explores how it relates to other factors (find relationships)

Answer 9

exploratory

Question 10

compares two or more conditions (determines cause and effect)

Answer 10

experimental

Question 11

5 major phases of the research process

Answer 11

1. identify the research question
2. design the study
3. carry out methods
4. data analysis
5. communication

Question 12

enough evidence accumulates to discredit an existing theory; may cause a change in perspective

Answer 12

paradigm shift

Question 13

List and describe the 7 parts of a primary research article

Answer 13

Abstract, Introduction, Methods, Results, Discussion, Acknowledgements, References

Question 14

overview and purpose

Answer 14

abstract

Question 15

statement of the problem; specific purpose and hypothesis

Answer 15

introduction

Question 16

study design; data analysis and procedures

Answer 16

methods

Question 17

narrative description of statistical outcomes

Answer 17

results

Question 18

interpretation of statistical outcomes

Answer 18

discussion and conclusions

Question 19

technical assistant; funding source

Answer 19

acknowledgments

Question 20

all references cited in articles

Answer 20

references

Question 21

synthesizes the data from multiple research studies and provides an argument or interpretation of the state of the field

Answer 21

review paper

Question 22

data sets are split and published separately instead of being presented in unified way

Answer 22

salami science

Question 23

a characteristic that can be manipulated or observed an that can take on different values, either quantitatively or qualitatively

Answer 23

variable

Question 24

variables that might change in response to some intervention

Answer 24

dependent

Question 25

condition, intervention or characteristic that will predict or cause a given outcome

Answer 25

independent variable

Question 26

declarative statement that predicts relationships between independent and dependent variables in a specific population

Answer 26

hypothesis

Question 27

alternative/research hypothesis

Answer 27

best guess answer to the research question; the expectation that is to be tested

Question 28

null hypothesis

Answer 28

opposite of the research hypothesis; challenging the alternative hypothesis.

Question 29

non directional hypothesis

Answer 29

no indication of change, higher or lower

Question 30

directional hypothesis

Answer 30

predicting that something is either going to go higher, lower, or stay the same

Question 31

the larger group to which research results are generalized

Answer 31

population

Question 32

researcher chooses a subgroup of the population; reference group for estimating characteristics or drawing conclusions about the population

Answer 32

sample

Question 33

individuals selected for a sample over-represent or under-represent certain population attributes that relate to the study variables

Answer 33

sampling bias

Question 34

factors that preclude or prevent someone from being a subject

Answer 34

those with conditions/ diseases additional to the disease under study extreme ages certain disabilities or deficits that can affect how they can participate

Question 35

factors of inclusion; population that qualifies someone as a subjec

Answer 35

gender disease state having particular treatment only certain symptoms

Question 36

every unit has equal chance of having some of the characteristics throughout the population. The sample should be representative of the population

Answer 36

random sampling (probability sampling)

Question 37

groups should be equivalent. differences between groups have been distributed as a function of chance alone

Answer 37

random assignment

Question 38

the difference between average (statistics) and population averages (parameters); should be due to chance, not intentional error or bias

Answer 38

sampling error

Question 39

experiment requirement through which change is observed. If we observe a change in the treatment group but not the control, we can attribute the change to the treatment.

Answer 39

control group

Question 40

factors that contaminate the independent variable so that separate effects of the variable are obscured

Answer 40

extraneous variables

Question 41

not measured in the study but can have confounding effects

Answer 41

lurkers

Question 42

either the subjects are unaware of treatment type but the researcher knows or vice versa

Answer 42

single blinding

Question 43

neither subjects or investigators know the identity of treatment groups until after data are collected or analyzed

Answer 43

double blinding

Question 44

List the three essential characteristics of an experiment

Answer 44

1. Independent variable manipulated by researcher 2. A control group must be incorporated into the design 3. Subjects must be randomly assigned to groups

Question 45

participants knowledge of treatment status or the investigators expectations can influence performance or reporting of outcomes

Answer 45

experimental bias

Question 46

every person in the population has an equal chance of being chosen; sample should be representative of the population

Answer 46

random sampling

Question 47

convenience sampling chosen on basis of availability. Ex: asking for volunteers by posting signs or advertisements

Answer 47

non-probability sampling

Question 48

Explain why statistics are important in research

Answer 48

Application of mathematical methods to research conclusions about the world made from observations (experiments) Allows us to make accurate inferences from our incomplete observations

Question 49

an educated guess, a process of inferring features of a population by looking at a small sample Address the questions of the likelihood that an observed difference between two groups could have arisen by chance

Answer 49

inferential statistics

Question 50

describe data only (does not manipulate or compare data) Measures of central tendency Measures of variability

Answer 50

descriptive statistics

Question 51

numbers that tend to cluster around the middle of a set of values

Answer 51

measures of central tendency

Question 52

the score that occurs most frequently in a distribution

Answer 52

mode

Question 53

the value above which there are as many scores as below it. Divides a rank-order distribution into 2 equal halves

Answer 53

median

Question 54

(X-bar) sum of a set of numbers divided by the number of scores, n

Answer 54

mean

Question 55

an observation that falls well above or well below the overall bulk of the data

Answer 55

outliers

Question 56

difference between largest value and the smallest value. Only uses the largest and smallest observations ignoring the rest of the data

Answer 56

range

Question 57

the typical value of how far the data falls from the mean, by summarizing the deviations from the mean

Answer 57

standard deviation

Question 58

Statistical inference is an educated guess, a process of inferring features of a population by looking at a small sample; addresses questions of likelihood

Answer 58

inferential statistics

Question 59

choosing of samples as representatives of the entire population

Answer 59

sampling

Question 60

the distribution obtained by computing the statistic for a large number of samples drawn from the same population

Answer 60

sample distribution

Question 61

FALSE POSITIVE when we conclude that a real difference exists, when the differences are in fact due to chance.

Answer 61

type 1 error (alpha)

Question 62

FALSE NEGATIVE when we conclude that the differences are due to chance when the samples are truly different. | calling the results not statisitically significant when they really are

Answer 62

type 2 error (beta)

Question 63

consists of arbitrary labels with no implied order; unranked; categorical | can be numbered but numbers have no significance

Answer 63

nominal data

Question 64

consists of numerical ranked data that is ranked according to some criterion; each rank is different from the others, but the differences might not be equal. Ex: pain ratings, (on a scale of 1-10)

Answer 64

ordinal data

Question 65

consists of ranked data with intervals between each other being equal but with no meaningful zero point ex: IQ scores

Answer 65

interval data

Question 66

like interval data but zero point is meaningful; highest level of measurement. Ex: most lab values, no negative values, height, weight, age

Answer 66

ratio data

Question 67

acquisition of new knowledge for its own sake, without reference to potential practical use

Answer 67

basic research

Question 68

directed toward solving immediate practical problems with functional applications and testing theories that direct practice

Answer 68

applied research

Question 69

structured process of investigating facts and theories in medicine exploring connections, improving patient care

Answer 69

clinical research