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Stats in Health Science > Chapter 1 > Flashcards

Chapter 1 Flashcards

1
Q

Kinesiology

A

the study of the art and science of human movement, can be studied qualitatively or quantitatively

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2
Q

Quantitative

A

distance, force, time, joint angles, etc.; considered to be be objective because they are made with mechanical instruments, which require minimal judgement on the part of the investigator and reduce investigator bias to a minimum

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3
Q

Qualitative

A

(Subjetive); because they require human judgement, and are used to determine the quality of a performance (ex: a gymnastics routine, golf swing, patients level of pain)

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4
Q

Measurement

A

the process of comparing a value to a standard

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5
Q

Data

A

the result of measurement

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6
Q

Statistics

A

a mathematical technique by which data are organized, treated, and presented for interpretation and evaluation.

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7
Q

Evaluation

A

the philosophical process of determining the worth of the data

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8
Q

Reproducible

A

the data from the measurement, a second measurement under the same conditions should produce the same result as the first measurement

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9
Q

Reliability

A

(the consistency of the data); usually determined by the test–retest method, where the first measure is compared with a second or third measure on the same subjects under the same conditions

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10
Q

Validity

A

refers to the soundness (appropriateness) of the test in measuring what it is designed to measure; can be determined via logical analysis of the measurement procedures, or via comparison to another test already known to be valid

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11
Q

Objectivity

A

means that the data are collected without bias by the investigator; sometimes referred to as inter-rater reliability

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12
Q

Bias

A

can be detected by comparing an investigators scores to those of an expert or panel of experts

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13
Q

Measurement involves four steps:

A
  1. The object to be measured is identified and defined.
  2. The standard with which the measured object will be compared is identified and defined.
  3. The object is compared with the standard.
  4. A quantitative statement is made of the relationship of the object to the standard.
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14
Q

milli

A

1/1,000

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15
Q

centi

A

1/100

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16
Q

deci

A

1/10

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17
Q

zero

A

0

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18
Q

deca

A

10

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19
Q

hecto

A

100

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20
Q

kilo

A

1,000

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21
Q

mega

A

1,000,000

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22
Q

giga

A

1,000,000,000

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23
Q

Variable

A

a characteristic of a person, place, or object that can assume more than one value; (a person may perform differently when measured on the same variable more than once)

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24
Q

Constant

A

a characteristic that can assume only one value (never changes so we only need to measure it once)

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25
Q

Continuous Variable

A

theoretically can assume any value (distance, force, time, etc.); can be measures as short as a millionth of a cm or as a light-year

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26
Q

Discrete Variable

A

limited to certain numbers, usually whole numbers or integers (we can’t have a fraction of a person)

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27
Q

Nominal Scales

A

subjects are grouped into mutually exclusive categories without qualitative differentiation between the categories; data grouped this way are sometimes called frequency data because the scale indicates the number of times an event happens (size of the number doesn’t indicate an amount but instead indicates category assignment)

28
Q

Ordinal scale (rank-order scale)

A

gives quantitative order to the variables but does not indicate how much better one score is than another. (differences between the positions may be unequal) Medals, nothing saying how much better 1st is than 2nd or 3rd

29
Q

Interval Scale

A

has equal units, or intervals, of measurement—that is, the same distance exists between each division of the scale—but has no absolute zero point. (since 0 doesn’t indicate the absence of value, one point is not 2 or 3x’s larger) temp bc zero isn’t an absence of heat

30
Q

ratio scale

A

(most complete scale of measurement); based
on order, has equal distance between scale points, and uses zero to represent the absence of value. All units are equidistant from each other, and proportional, or ratio, comparisons are appropriate (distance, force, or time-negative scores are impossible)

31
Q

Nominal and ordinal scales are called…

A

nonparametric because they do not meet

the assumption of normality.

32
Q

Interval and ratio scales are classified as…

A

parametric. (primary focus in this course)

33
Q

Research

A

a special technique for solving problems; (Identifying the problem is a critical part of research)

34
Q

Historical research

A

a search through records of the past to determine what happened and why (an attempt to solve problems by learning from the past)

35
Q

Observational research

A

(or descriptive research) involves describing events or conditions, which the researcher does not actively manipulate. In this type of study, researchers often examine correlations in the data. (A common tool is the survey.)

36
Q

Experimental Research

A

the process that involves manipulating and controlling events or variables to solve a problem (puts researchers in the strongest position to make cause and effect inferences from the data)

37
Q

Experimental Design

A

the process that involves manipulating and controlling certain events or controlling certain events or conditions to solve a problem

38
Q

Hypothesis

A

an educated guess or logical assumption that is based on prior research or known facts and that can be tested by the experimental design (must be stated in a way that a statistical analysis can be performed on the data to determine the probability or odds of obtaining the given results if true)

39
Q

Research Hypothesis (alternate hypothesis)

A

hypothesis that prompts the research (symbolized as H1); predicts relationships or differences between groups of participants

40
Q

Null Hypothesis

A

used to test statistical analysis and predicts no relationship or no difference between groups; states that any relationship or difference that may be observed by measurement is the result of random occurrence

41
Q

Statistical Analysis

A

reports the probability that the results would occur as we observe them if the null hypothesis is true

42
Q

if the probability is small…

A

we reject the null hypothesis and accept the alternate (or research) hypothesis

43
Q

if the probability is large…

A

we accept the null hypothesis

44
Q

If odds against it are better than 95 to 5…

A

we may decide to reject the null

45
Q

The probability that we could have gotten the data that we did if the null is true…

A

is less than or equal to 0.05 (p is less than or equal to .05)

46
Q

Independent Variable

A

the variable that is manipulated or controlled by the researcher, sometimes referred to as the “treatment” variable (plotted on the x axis)

47
Q

Dependent Variable

A

a variable that is dependent on the effects of one or more other variables, the variable which is measured (plotted on the y axis)

48
Q

In correlation-type research the independent and dependent variable are referred to as…

A

the predictor variable and the criterion variable

49
Q

Internal Validity

A

refers to the design of the study itself; it is a measure of the control within the experiment to ascertain that the results are due to the treatment that was applied.

50
Q

Analyzing the posttest differences between the experimental group and the control group helps us sort out how much improvement is due to…

A

(a) the treatment and (b) the learning effect from the pretest. A design of this type without a control group can be criticized for having weak internal validity.

51
Q

intervening variables, (extra-neous variables)

A

factors, which are not controlled in the experiment, and can also reduce the
internal validity. they intervene to affect the dependent variable but are extraneous to the research design.

52
Q

Instrument error

A

refers to incorrect data that are due to a faulty instrument.

53
Q

Investigator error

A

occurs when the investigator introduces bias in recording

the data.

54
Q

External validity

A

refers to the ability to generalize the results of the experiment to the population from which the samples were drawn.

55
Q

Statistical Inference

A

The process of generalizing from a sample to a population, and is one of the basic tools of the statistician.

56
Q

Population

A

any group of persons, places, or objects that have at least one common characteristic

57
Q

Sample

A

If it is impossible or impractical to measure all members of a population, then we measure a portion, or fraction, of the population,

58
Q

The larger the sample, the smaller the error, and…

A

the smaller the sample, the larger the error

59
Q

Random Sample

A

each member of the population has an equal opportu-nity of being selected into the sample.

60
Q

Stratified Sample

A

taken when random selection in a large population is desired and subcategories of the population are of interest. To do this, we select a certain part of the sample from each subgroup of the population.

61
Q

Bias

A

means that factors operate on the sample to make it unrepresentative of the population.

62
Q

Parameter

A

is a characteristic of the entire population. A statistic is a characteristic of a sample that is used to estimate the value of the population parameter.

63
Q

theory

A

a belief regarding a concept or a series of related concepts. Theories are not necessarily true or false.

64
Q

instrument error

A

refers to incorrect data that are due to a faulty instrument.

65
Q

nonparametric

A

Nominal and ordinal scales because they do not meet

the assumption of normality.

66
Q

parametric

A

Interval and ratio scales

67
Q

Statistic

A

A characteristic of a sample

Stats in Health Science (12 decks)

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