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EBP II > Exam 1 > Flashcards

Exam 1 Flashcards

1
Q

Mode

A

The most frequent score in a distribution (the option with the highest frequency)

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2
Q

Range

A

The difference between the largest and smallest values

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3
Q

Median

A

The middle score when you place the scores in order from smallest to largest

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4
Q

Standard Deviation

A

The square root of the variance (used to measure the variation in a distribution)

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5
Q

Random Selection/Assignment of Subjects

A
  • A type of assignment that maximizes chances that groups have similar characteristics at the start of a study
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6
Q

Purposive Selection/Assignment of Subjects

A
  • Handpicking subjects who the researcher believes will lend insight into their study/research
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7
Q

Dependent Variable

A

The outcome of a study and variable that the researcher is interested in (must be measurable)

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8
Q

Skewed Data

A

A score that is so far from the mean on the normal bell curve that it ends up affecting the mean

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9
Q

Independent Variable

A

The variable that is believed to affect the outcome (DV). This is the aspect that the researcher manipulates (must have at least 2 variables

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10
Q

Repeated Factor

A

An IV (factor) that is repeated for each subject

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11
Q

Interval/Ratio Scale

A

The most quantitative measurement scale that can includes mathematical operations, order, and distance

Ex) weight, height, temperature

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12
Q

Test-retest Reliability

A

Reproducibility with tests results over time (The more consistent the test results are, the more test-retest reliability there is)

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13
Q

Internal Validity

A

The extent to which the results of the study demonstrate that a causal relationship exists between the independent and dependent variables

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14
Q

External Validity

A

Concerns to whom, in what settings, and at what times the results of the research can be generalized

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15
Q

Hypothesis

A

A proposed explanation made on the basis of limited evidence as a starting point for further investigation (prediction)

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16
Q

Directional Hypothesis

A

Experimenter predicts that a specific relationship exists between variables and predicts the direction (positive or negative) of that relationship

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17
Q

Non-Directional Hypothesis

A

Experimenter predicts that the there is a relationship that exists between variables, but does NOT specify the direction (+/-) of that relationship

(Null and Alternate Hypothesis are examples)

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18
Q

Complex Hypothesis

A

A hypothesis that includes MORE than 1 independent/dependent variable

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19
Q

Simple Hypothesis

A

A hypothesis that involves ONLY 1 independent/dependent variable

20
Q

Face Validity

A

The weakest type of validity - determining the validity of something by only viewing its “face”

Ex) Determining that a tool appears to measure what it is supposed to so you determine that it is valid (no comparison to other tool)

21
Q

Content Validity

A

The extent to which a measure is a complete representation of the concept of interest

(a final exam representing knowledge of the whole course content)

22
Q

Construct Validity

A

Concerned with the meaning of variables (abstract theoretical principles) within a study

(the researcher might say that shoulder ROM determines shoulder function, but one might question that that those are 2 separate measures that do not affect each other)

23
Q

Criterion-Related Validity

A

Extent to which a measure is systematically related to another measure (comparing a new instrument/measure to a gold standard)

24
Q

Between Subject Design (Independent)

A

Different groups receive different levels of the IV

25
Q

Within Subject Design (Dependent)

A

Same subjects receive all levels of the IV (pre-test and post-test)

26
Q

Mixed Design

A

Designs with at least one within subject factor and one between subject factor

27
Q

Normal Distribution

A

The bell curve. Symmetrical frequency distribution that is defined in terms of mean and standard deviation of data set

1 std deviation from mean = 68%
2 std deviation from mean = 95%
3 std deviation from mean = 99%

28
Q

T-Test (t for 2)

A

Evaluating the difference between 2 INDEPENDENT samples

29
Q

Paired t-Test (t for 2)

A

Evaluating difference between 2 DEPENDENT samples

30
Q

1 Way ANOVA

A

BETWEEN Subjects - Evaluating difference of MORE THAN 2 INDEPENDENT samples

31
Q

2 Way ANOVA

A

BETWEEN SUBJECTS - Evaluating difference of MORE THAN 2 INDEPENDENT samples with TWO IVs

32
Q

1 Way Repeated Measures ANOVA

A

WITHIN SUBJECT - Evaluate difference of MORE THAN 2 DEPENDENT samples

33
Q

2 Way Repeated Measures ANOVA

A

WITHIN SUBJECT - Evaluate difference of MORE THAN 2 DEPENDENT samples with TWO IVs

34
Q

Type I Error

A
  • Your statistical conclusion states that there IS a difference, but in reality there IS NO difference
  • Probability of making type I error = ALPHA (reduce alpha to reduce probability of making this error)
35
Q

Type II Error

A
  • Your statistical conclusion states that there IS NO difference, but in reality there IS a difference
  • Probability of making type II error = BETA (reduce beta to reduce probability of making this error)
36
Q

Alpha Level

A

How much probability of drawing incorrect conclusion can be tolerated?

(Generally accepted Alpha Level is 0.05 or 5%) - due to a sampling error

37
Q

Probability Sampling

A

Randomization at some point in the sampling process (simple, systematic, stratified, and cluster sampling are all examples)

38
Q

Subject Attrition

A

A threat to INTERNAL validity. Participants lost from different study groups at different rates or for different reasons

39
Q

Instrumentation

A

Threat to INTERNAL validity. Changes in measuring tools, improper calibration of instruments, unreliable human instrumentation (subjective)

40
Q

Maturation

A

Threat to INTERNAL validity. Changes within the participant/subject that is due to the passage of time (could change the outcome/DV)

41
Q

Correlation Coefficient

A

A statistical summary of the degree of relationship that exists between 2 or more measures (could be between different variables or repeated measures of same variable)

(Scale of .00 (very little) to 1.0 (strong) that determines strength of relationship)

42
Q

Multiple Comparison Tests

A

The next step after null hypothesis is rejected in an ANOVA: comparing group means and pinpointing the differences (post-hoc AKA after the fact)

Use the Scheffe, Bonferroni, and Turkey HSD tests

43
Q

Pearson Product Moment Correlation Coefficient (r)

A

The average of the cross products of the z scores for the X and Y variables (example: averaging the cross products of z scores of 6 month ROM and Gait Velocity)

r: Range of -1 to 1 where positive values has a positive correlation and negative value has negative correlation

44
Q

Experimental vs. Non-Experimental Study

A
  • Experimental: researcher manipulates an Independent Variable
  • Non-Experimental: does not manipulate an IV (descriptions, analysis of relationships, and analysis of differences)
45
Q

Correlation vs. Comparison

A
  • Correlation - compares relative position of SAME individuals/groups on 2 DIFFERENT variables (margarine consumption in Maine positively correlates to divorce rates in Maine) –> does not equal causation
  • Compare/Contrast - DIFFERENT individuals/groups are being compared on the SAME variable

EBP II (3 decks)

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