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NCMHCE Exam > Research and Statistics (78) > Flashcards

Research and Statistics (78) Flashcards

(78 cards)

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1
Q

A correlation describes a ____________ between 2 variables

A

relationship

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2
Q

correlation describes a relationship between

A

two variables

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3
Q

a factor is also known as

A

an independent variable

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4
Q

AB Design

A

a pretreatment baseline measure is performed

the treatment is applied

measurement is taken after the treatment is applied

AB relies on comparing the treatment effect on either a single participant or group of participants.

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5
Q

ABAB Design

A

Measure a baseline (the first A)

the treatment is applied

Measurement is taken (the first B)

return to baseline or the withdrawal of treatment (the second A) is performed

The re-introduction of treatment is applied (The second B )

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6
Q

ANOVA

A

ANalysis Of VAriance

used with more than two groups or samples

Results of ANOVA tests are called f-ratios

Used with parametric data

Used with interval or ratio data

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7
Q

Are field studies considered true experimental or quasi-experimental?

A

Quasi-experimental

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8
Q

Are lab studies considered true experimental or quasi-experimental?

A

True experimental

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9
Q

Behavioral observations

A

Consider what happened before a target behavior, the behavior itself and its consequences.

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10
Q

Best fitting line is also known as

A

Regression line

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11
Q

Between Groups Design

A

Participants who receive the treatment are in one group

different levels of the independent variable are given to different groups of participants

one independent variable is given to one group and not to another group

the effect of the dependent variable is compared to each group receiving and not receiving the treatment

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12
Q

Case study vs experiment

A

one person is studied; not as controlled or objective as experiments.

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13
Q

Cluster Sampling

A

The population is divided into groups from which the researcher randomly selects an equal number of participants

Each group should represent the larger population from which it was selected

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14
Q

Coefficient of determination

A

The square of the correlation coefficient

an indicator of the percent of variance between variable

indicates how much the independent variable determines what the dependent variable will be

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15
Q

Confidence Interval

A

A range of values of a normal distribution of sample means which the population is expected to fall within

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16
Q

Confidence Level

A

The probability value of the confidence interval given as a percentage

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17
Q

Confidence Limit

A

the values of the lower end and the upper end of the range of the confidence interval

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18
Q

control group

A

independent variable is not manipulated in this group

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19
Q

correlation coefficient

A

ranges from -1 to 1, has both direction and magnitude

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20
Q

correlational method

A

research that examines relationships among factors does not determine cause and effect

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21
Q

dependent variable

A

variable measured in an experiment

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22
Q

double-blind study

A

experimenter and subjects do not know who is in control or experiment groups

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23
Q

experimental group

A

receives manipulation of the independent variable

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24
Q

external validity

A

ability to generalize results to groups outside the research study

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25
homoscedasticity
the assumption that in multiple groups of data each group will have a normal distribution of data
26
how do you find the T-score when you are given the Z-score and standard deviation?
1. Multiply the Z-score by the standard deviation 2. Add the result to the mean
27
In a scattergram, the x-axis represents the:
independent variable.
28
In a scattergram, the y-axis represents the:
dependent variable
29
Incidence
Number of new cases of a disorder during a certain time period
30
Independent variable
Maniipulated in an experiment
31
internal validity
manipulation of the independent variable caused the effects
32
Leptokurtic
High peek small range scores are clustered together not much variance in scores
33
Level of significance
A point or the alpha level at which the researcher decides, usually p = .05 that the data in one group are significantly different than the data gathered from another group in other words, using p = .05, we can be 95% certain that our results are not due to chance and a 5% chance that they are.
34
Linear
linear means that given scattered points on a graph it is possible to draw a line through the scattered points on the graph that would best represent their distribution
35
Magnitude
Strenght of correlation, expressed as a numerical value of "r"
36
Mean
The average of all the scores Adds up all the scores and divide by the number of scores
37
Median
place scores in order from lowest to highest. The score that lies in the middle of all scores is the median. if there is an even number of scores, take the two scores closest to the middle, add them together and divide by two to get the median.
38
Mesokurtic
normal bell-shaped distribution
39
Mode
most frequent occurring score
40
Multiple baseline design
improves generalizability by researching treatment that begins at different times in different groups in different settings
41
negative "r"
inverse relationship between variables
42
non=experimental research
descriptive research correlational research nothing is manipulated associations between variables are determined by correlational techniques takes less time and effort explores information about variables that already exist to find relationships used to predict outcomes does not establish causal relationships between independent and dependent variables
43
Non-linear
non-linear means that given scattered points on a graph it is NOT possible to draw a line through the scattered points on the graph that would best represent their distribution
44
Null Hypothesis
the hypothesis that there is no difference between group A and group B A and B are same
45
One-factor ANOVA
the researcher is considering only one independent variable
46
Person r is also known as
Person product moment correlation coefficient
47
Pearson r is used when the scores are either ________ or ________
Interval Ratio
48
Percentile
a percentile tells what percent of the group scored the same or below a specific score EX. if you scored in the 90th percentile you scored better than 90 percent of your peers, 10 percent scored better than you did
49
Platykurtic
curve is flat and low range of scores is large scores are all over the place
50
Prevalence
Statistics involving the presence of a disorder among a certain population at a certain time
51
Random assignment of subjects
Control group and experimental group should be as similar as possible
52
Reliability
Test gives consistent results over time
53
Scientific statements
Testable, based on observations, linked to measurable outcomes
54
Simple random sampling
Every participant in a given population has an equal chance of being included in the sample The selection of one participant does not affect the selection fo another participant
55
Spearman r is also known as
Rank correlation coefficient
56
Spearman r is used when the scores are given as _________ scaled data.
Ordinal
57
Standard Error of Estimate
The error in any prediction
58
Standardization
similar procedures are used each time test is administered
59
statistical significance
probability that a relationship happened by chance
60
True of False A negative correlation can be more significant than a positive correlation
True
61
True or False Correlations can be greater than 1
False
62
True or False Correlations can be linear or nonlinear
True
63
True or False Correlations can be negative or positive
True
64
T-test
Used to determine is there a significant difference between the means of two groups of scores there can only be two groups the result of the test is known as the t ratio if the t value is above the level of significance, reject the null hypothesis used with interval or ratio data used with parametric data
65
Type I error
You have rejected the null hypothesis what you are saying is that there is a difference between group A and group B because of some independent variable. But the reason this is an error is that in reality there is no difference between groups A and B because of the independent variable you have discovered nothing but you are saying you have discovered something this is the worst mistake you can make. You are saying there is a relationship but there is no relationship. These types of errors can literally kill someone.
66
Type II error
You have accepted the null hypothesis You are saying there is NO difference between groups A and B because of some independent variable but in reality there IS a difference. You have saying you have discovered something when you have NOT you are saying there is no relationship but there is a relationship this type of error is like missing a shoe.
67
Validity
test measures what it says it measures
68
What are some methods of non-experimental research?
case studies archival research observational study survey
69
what are three forms of quasi-experimental research?
field experiments developmental research ex-post factor research
70
what are three types of non-parametric tests of the null hypothesis?
chi square mann-whitney y test wilcoxon matched pairs signed rank test
71
what are two parametric tests of the null hypothesis?
T-test ANOVA
72
What is necessary for inferential research?
Experimental conditions controlled more than one level of independent variables subjects are randomly assigned to groups
73
when and on what type of data do you use non=parametric tests?
when the population distribution is NOT normal the type of data is ordinal or nominal
74
when and on what type of data do you use parametric tests?
when the population distribution is normal the data is either interval or ratio scaled
75
When would you use chi-square?
non parametric nominal data
76
when would you use the Mann-Whitney U-tests?
non-parametric ordinal only two groups all participants are completely randomly chosen non matched groups groups are independent
77
when would you use the Wilcoxon Matched Pairs Signed Rank Test?
Non parametric Ordinal Two groups Matched groups Two groups are dependent
78
Within-Subject Design
An experiment where the same group of participants receives more than one treatment of independent variables sequentially. Example: if you want to see the effect of eating specific foods on memory, the two treatments might be chicken and beef. The group of participants would eat chicken then take a memory test. Later the same group of participants would eat beef and take a memory test. You would then compare the memory scores to answer the question of what treatment aids memory the most.

NCMHCE Exam (49 decks)

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