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NCC > Reseach And Design > Flashcards

Reseach And Design Flashcards

1
Q

Characteristics of a research study

Develop an idea into testable hypothesis

A

Defining the relevant variables and identifying the target population

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2
Q

Characteristics of a research study

Choosing an appropriate research design

A

Choose appropriate research strategy and specific research design

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3
Q

Characteristics of a research study

Selecting a sample

A

Determine how the sample will be selected from the population

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4
Q

Characteristics of a research study

Conducting the survey

A

Investigator conduction studies and collects and records the data

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5
Q

Characteristics of a research study

Analyzing to obtain data

A

Appropriate descriptive and inferential statistics techniques

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6
Q

Characteristics of a research study

Reporting the results

A

Prepares a report of the research results

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7
Q

Variable

A

Any characteristic behavior event or phenomenon that is capable of bearing or existing in at least two different states conditions or levels

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8
Q

Constant

A

When a characteristic is restricted to a single state or condition

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9
Q

Independent variable

A

Believe to affect or alter status of another variable

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10
Q

Dependent variable

A

Referred to as treatment or intervention is symbolize with X. Is considered the outcome of the treatment

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11
Q

Manipulated variables

A

Are considered the independent variable’s

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12
Q

Organismic variables

A

Variables that cannot be controlled by the researcher or independent variable

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13
Q

Nonexperimental research

A

Primarily to collect data about variables rather than to test hypothesis

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14
Q

Observational studies

A

Observing behavior in a systematic way often in a naturalistic settings

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15
Q

Case studies

A

Associated with an in-depth description and analysis of a single person also can entail an intensive investigation of a single institution agency community or social unit

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16
Q

Surveys

A

Administering a questionnaire either in person or by phone or through mail subject to nonresponse bias

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17
Q

Random assignment

A

Helps ensure that any observed differences between groups on the dependent variable or actually due to the effects of the independent variable

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18
Q

Quasi-experimental research

A

Does not provide the investigator with the same degree of experimental control

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19
Q

Ex post facto research

A

Involves assessing the effects of an independent variable after it has occurred

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20
Q

Developmental research

A

Conducted to assess changes that occur as function of time

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21
Q

Cross-sectional studies

A

Evaluate change over time by comparison groups of people of different ages at the same point in time

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22
Q

Longitudinal studies

A

Investigate changed by assessing people belonging to the same age group over an extended period of time

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23
Q

Cohort (generational) affects

A

Are occurring when observed differences between subjects of different ages are due to differences in experience or other factors rather then to increasing age

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24
Q

Cross sequential (cohort sequential) study

A

Combines cross-sectional and longitudinal methods by assessing members of two or more age groups at two or more different times

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25
Q

Simple random sample and

A

Every member of the population has an equal chance of being included in the sample

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26
Q

Stratified random sampling

A

When the population of interest Sperrys in terms of specific strata or characteristics that are relevant to the research hypothesis and Vesta gate or can you stratified random sample and to ensure that each stratum is represented

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27
Q

Cluster sampling

A

Sampling entails select units or clusters of individuals rather than individuals and either including all individuals in those units in research study or randomly selecting individuals from each unit

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28
Q

Control group

A

Either no treatment control group or a placebo controlled group

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29
Q

Placebo control groups

A

Are exposed to nonspecific factors that are not uniqueto a particular therapy but are common to most

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30
Q

Basic questions

A

Is there a relationship between the independent and the dependent variable?
If so is the relationship a causal one?

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31
Q

Three factors that can cause variability in the studies dependent variable

A

The independent variable or experimental variance
Systematic error due to extraneous variables and
Random error due to random fluctuations in subjects experimental conditions and methods of measurement

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32
Q

True experimental study

A

Investigators control is maximized

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33
Q

True experimental research

A

Enhances a researchers ability to maximize their ability due to the independent experimental variable

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34
Q

Extraneous variable or confounding variable

A

Source of systematic error a very bold that is a relevant to the purpose of the research

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35
Q

Random assignment of subjects to treatment group

A

Equalize is the effect of all known and unknown extraneous variables

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36
Q

Holding the extraneous variables constant

A

Selecting subjects were homogeneous

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37
Q

Matching subjects on extraneous variables

A

Making the groups equivalent in terms of the extraneous variables

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38
Q

Building the extraneous variables into study

A

Including it in the study as an additional independent variable

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39
Q

Internal validity

A

The extent that it provides accurate answers to the first two research questions

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40
Q

External validity

A

The degree that it produces an accurate answer to the third question. Can the relationship between independent independent variables be generalized to other people setting times and operations?

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41
Q

Basic research questions

A

Is there a relationship between the independent independent variable?
If so, is the relationship a casual one? Can the relationship between independent and dependent variables be generalized to other people, settings, times and operations?

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42
Q

A study has Internal validity

A

When it allows an investigator to determine if there is a causal relationship between independent and dependent variables

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43
Q

Threats to internal validity

Maturation

A

Any biological or physiological change that occurs within the subject during the course of the study as a function of time
Best controlled to include more than one group

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44
Q

Research

A

Defined as the empirical systematic investigation of the relationship between two or more variables

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45
Q

Threats to internal validity

History

A

History threatens the studies internal validity when an external event systematically affects the status of the subjects on the dependent variable
Best controlled by including more than one group

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46
Q

Threats to internal validity

Testing

A

Taking a test can alter person’s performance on the test when it is re-administered

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47
Q

Instrumentation

A

Changes in accuracy or sensitivity of the measuring device or procedures during the course of study can confound the study results

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48
Q

Threats to internal validity

Statistical regression

A

The tendency of extreme scores on a measure to regress toward the mean when the measure is readministered to the same group of people

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49
Q

Regression of the mean

A

Statistical regression is sometimes thought to be synonymous with Galton notion

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50
Q

Threats to internal validity

Selection

A

Is a threat to his studies internal validity whenever the method used to assign subjects to treatment groups result in systematic differences between the groups at the beginning of the study

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51
Q

Threats to internal validity

Attrition our mortality

A

When subjects who dropped out of one’s group differ in an important way from subjects who dropped out of other group

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52
Q

Threats to internal validity

Interaction with selection

A

Groups are initially non-equivalent, selection can act alone and/or can interact with other factors to threaten the studies internal validity

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53
Q

External validity

A

Has validity when it’s finding can be generalized to other people, settings, and conditions.

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54
Q

Threats to external validity

Interaction between testing and treatment

A

The administration of a pretest can sensitize subject to the purpose of the research study and thereby alter their reaction to the independent variable

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55
Q

Threats to external validity

Interactions between selections and treatment

A

Subjects and food in a research study can have characteristics that make them responded to the independent variable in a particular way

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56
Q

Threats to external validity

Reactivity – reactive arrangements

A

Research participants can respond to an independent variable in a particular way simply because they know their behavior is being observed

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57
Q

Hawthorne effect

A

Tendency of subjects to perform better because of attention they are receiving as a research participant or evaluation apprehension

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58
Q

Demand characteristics

A

Behavior of research participants can be altered by cues and experimental setting that inform the subject of the purpose of the study or suggest what behaviors are expected of them

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59
Q

Between group designs

A

Used the effect of different level of an independent variable are assessed by administering each level to a different group of subjects and then comparing the status or performance of the groups on the independent variable

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60
Q

Factorial design

A

Whenever a set includes two or more independent variables

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61
Q

Within subject design

A

All levels of the independent variable are administered sequential to all subjects

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62
Q

Single group timeseries design

A

One type of within subject design

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63
Q

Mixed designs

A

Combines between groups and within subject methodologies

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64
Q

Single subject design

A

Combines behavioral principles with the technique of experimental psychology to solve socially – relevant problems

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65
Q

Characteristics of single subject designs

A

Includes at least one baseline – no treatment phase and one treatment phase. Helps control any maturation affects

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66
Q

A B design

A

A. Phase and single treatment

B. Phase

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67
Q

Reversal design ABA, ABAB, etc.

A

The A.B. design can be expanded to include more than one baseline phase or more than one baseline and more than one treatment phase the extension of the A.B. design are called reversal or withdrawal designs

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68
Q

Multiple baseline design

A

Maybe unethical
Does not require withdrawal of treatment during the course of the study but instead involve sequential applying the treatment either two different behaviors of the same subject called multiple baseline across behaviors or to the same subject in a different setting

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69
Q

Formative evaluation

A

Obtaining the information needed to determine if the program is being implemented as intended or whether any modifications are needed so that the program can achieve its objectives

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70
Q

Summative evaluations

A

Entails assessing the program is affecting us in determining if the program should be continued or expanded

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71
Q

Continuous variable

A

Theoretically can take an infinite number of values on the measurement scale

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72
Q

Discrete variable

A

Can assume only a finite number of values

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73
Q

Qualitative variable

A

Places people in unordered categories

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74
Q

Quantitative variable

A

Permits comparison of people in terms of order

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75
Q

Nominal scale

A

Measurement divides variables into an ordered categories i.e. sex of sales people

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76
Q

Ordinal scale

A

More mathematically complex than a nominal scale. Divides observations into categories but also provides information on order of those categories. Likert type scale one for strongly agree seven for strongly disagree

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77
Q

Likert scale

A

A forced answer scale ranging categories from 1 to 10

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78
Q

Interval scales

A

Has a property of order as well as the property of equal intervals between successive points on the measurement scale e.g. IQ tests are usually considered a representative of the interval scale

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79
Q

Ratio scale

A

Most mathematically complex of the four measurement scales. It has properties of order and equal intervals as well as properties of an absolute zero point.makes it possible to multiply and divide racial scores to determine more precisely how much more or less of a characteristic one person has to another. Example Kelvin scale

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80
Q

Descriptive statistics

A

Used to describe or samurais a distribution of set data

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81
Q

Frequency distribution

A

Summarizing the data in terms of the number of frequency observations in each case

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82
Q

Cumulative frequency

A

Indicate the total number of observation that falls at or below each category or score

83
Q

Shapes of distribution

Normal curve

A

Systematic bell shaped and defined by specific mathematical formula

84
Q

Shapes of distribution

Kurtisis

A

Refers to the relative peaked nice hike or flatness of the distribution

85
Q

Shapes of distribution

Platkurtic

A

Went to distribution is flatter

86
Q

Shapes of distribution

Leptokurtic

A

Went to distribution is peaked

87
Q

Shapes of distribution

Skewed distribution

A

More than half of the observations fall on one side of the distribution

88
Q

Shapes of distribution

Positively skewed distribution

A

Most of the scores are in the negative low side of the distribution the positive tail is extended

89
Q

Shapes of distribution

Negatively skewed distribution

A

Most scores are located on the positive high school side of the distribution and the negative tail is extended due to the presence of a few low scores

90
Q

Measures of central tendency

Mode

A

The score category that occurs the most frequently

91
Q

Measures of central tendency

Median

A

The score the divides a distribution in half when the data has become ordered from low to high. Useful for it it’s in sensitivity to outliers and open ended distributions where there are no specific upper and lower limits

92
Q

Multimodal

A

Two or more scores are categories that occur equally often

93
Q

Bimodal

A

When two scores are equal

94
Q

Susceptibility to sampling fluctuations

A

This means that, if a large number of samples are randomly selected from the population, the mold can be expected to vary considerably from sample to sample.

95
Q

Measures of central tendency

Arithmetic mean

A

M-X
Mean equals the sum of the means divided by number of means
Used for its lease to susceptibility to sample and fluctuation usually provides an unbiased estimate of the population mean

96
Q

Measure of variability

Range

A

Calculated by simply subtracting the lowest score in the distribution from The highest score

97
Q

Measure of variability

Variance mean square

A

Is a more thorough measurement of variability then the range because it’s calculations includes all the scores in the distribution rather than just the highest and lowest dance is calculated using

98
Q

Measure of variability

Standard deviation

A

The standard deviation is calculated by taking the square root of the variance

99
Q

Population parameters and sample statistics

A

Estimates population values based on obtain samples

100
Q

Characteristics of sampling distribution

A

Due to the effects of random chance factors, it is unlikely that any sample will perfectly represent the population from which it was drawn

101
Q

Sampling error

A

inaccuracies

102
Q

Inferential statistics test

A

Indicates where the obtain samples to distichs falls in the appropriate sampling distribution

103
Q

Rejection region

A

Region of unlikely values lights on both tales of the sampling distribution

104
Q

Retention region

A

Regions of likely values lies in the central portion of the sampling distribution

105
Q

Null hypothesis is rejected

A

Obtain samples statistics is in the rejection region

106
Q

No hypothesis is retained

A

Statistical tests indicate that the sample statistic lives in the retention region

107
Q

Alfa or level of significance

A

0.01 or 0.05 represents the sampling distribution in the rejection region and the remaining percentage represents the retention region

108
Q

Type I error = alpha

A

Occurs when an investigator rejects a true null hypothesis

109
Q

Type II error = beta

A

Occurs when an investigator retains a false null hypothesis

110
Q

Beta

A

Directly calculated for a particular study depending on the Alpha

111
Q

Inverse relationship

A

As the probability of making a Type I error increases the probability of making a Type II error Increases and vice versa

112
Q

Statistical power

A

A statistical test enables an experimenter to reject a faults Null hypothesis

113
Q

Using a one tailed test when appropriate

A

One tail test is more powerful than a two-tailed test

114
Q

Using a parametric test

A

Parametric statistical tests such as a t-test or ANOVA or more powerful than nonparametric test

115
Q

Homoscedacity

A

The variance of the population that the different groups represented are equal

116
Q

Critical values and degrees of freedom

A

Test that allows investigator to determine whether the obtains sample value is in the rejection or retention region of the sampling distribution this is done by comparing the tested to sticks to a critical value which is the number that corresponds to the boundary that divides the sampling distribution into rejection retention

117
Q

Chi– square test

A

Used to analyze the frequency of observation of a nominal variable test

118
Q

ANOVA

A

Analysis of variance is used to compare two or more means

119
Q

One-Way ANOVA

A

Is used want to study includes one independent variable and two or more dependent groups

120
Q

Factor analysis of variance

A

An extension of the one way ANOVA that is employed want to study includes two or more independent variables

121
Q

Assumptions

A

Use of the Pearson r and most other qualifications require that three assumptions be met

122
Q

Linearity

A

Assumption that there is a linear relationship between the variables relationship between the X-Men why can be summarized in a straight line

123
Q

Unrestricted range

A

Use of the Persons r is also based on the assumptions that there is an unrestricted range of scores on both variables

124
Q

Homoscrdasticity

A

The third assumption is that the range of why scores is about the same for the values of X

125
Q

Threats to internal validity

History

A

History threatens the studies internal validity when an external event systematically affects the status of the subjects on the dependent variable
Best controlled by including more than one group

126
Q

Threats to internal validity

Testing

A

Taking a test can alter person’s performance on the test when it is re-administered

127
Q

Instrumentation

A

Changes in accuracy or sensitivity of the measuring device or procedures during the course of study can confound the study results

128
Q

Threats to internal validity

Statistical regression

A

The tendency of extreme scores on a measure to regress toward the mean when the measure is readministered to the same group of people

129
Q

Regression of the mean

A

Statistical regression is sometimes thought to be synonymous with Galton notion

130
Q

Threats to internal validity

Selection

A

Is a threat to his studies internal validity whenever the method used to assign subjects to treatment groups result in systematic differences between the groups at the beginning of the study

131
Q

Threats to internal validity

Attrition our mortality

A

When subjects who dropped out of one’s group differ in an important way from subjects who dropped out of other group

132
Q

Threats to internal validity

Interaction with selection

A

Groups are initially non-equivalent, selection can act alone and/or can interact with other factors to threaten the studies internal validity

133
Q

External validity

A

Has validity when it’s finding can be generalized to other people, settings, and conditions.

134
Q

Threats to external validity

Interaction between testing and treatment

A

The administration of a pretest can sensitize subject to the purpose of the research study and thereby alter their reaction to the independent variable

135
Q

Threats to external validity

Interactions between selections and treatment

A

Subjects and food in a research study can have characteristics that make them responded to the independent variable in a particular way

136
Q

Threats to external validity

Reactivity – reactive arrangements

A

Research participants can respond to an independent variable in a particular way simply because they know their behavior is being observed

137
Q

Hawthorne effect

A

Tendency of subjects to perform better because of attention they are receiving as a research participant or evaluation apprehension

138
Q

Demand characteristics

A

Behavior of research participants can be altered by cues and experimental setting that inform the subject of the purpose of the study or suggest what behaviors are expected of them

139
Q

Between group designs

A

Used the effect of different level of an independent variable are assessed by administering each level to a different group of subjects and then comparing the status or performance of the groups on the independent variable

140
Q

Factorial design

A

Whenever a set includes two or more independent variables

141
Q

Within subject design

A

All levels of the independent variable are administered sequential to all subjects

142
Q

Single group timeseries design

A

One type of within subject design

143
Q

Mixed designs

A

Combines between groups and within subject methodologies

144
Q

Single subject design

A

Combines behavioral principles with the technique of experimental psychology to solve socially – relevant problems

145
Q

Characteristics of single subject designs

A

Includes at least one baseline – no treatment phase and one treatment phase. Helps control any maturation affects

146
Q

A B design

A

A. Phase and single treatment

B. Phase

147
Q

Reversal design ABA, ABAB, etc.

A

The A.B. design can be expanded to include more than one baseline phase or more than one baseline and more than one treatment phase the extension of the A.B. design are called reversal or withdrawal designs

148
Q

Multiple baseline design

A

Maybe unethical
Does not require withdrawal of treatment during the course of the study but instead involve sequential applying the treatment either two different behaviors of the same subject called multiple baseline across behaviors or to the same subject in a different setting

149
Q

Formative evaluation

A

Obtaining the information needed to determine if the program is being implemented as intended or whether any modifications are needed so that the program can achieve its objectives

150
Q

Summative evaluations

A

Entails assessing the program is affecting us in determining if the program should be continued or expanded

151
Q

Continuous variable

A

Theoretically can take an infinite number of values on the measurement scale

152
Q

Discrete variable

A

Can assume only a finite number of values

153
Q

Qualitative variable

A

Places people in unordered categories

154
Q

Quantitative variable

A

Permits comparison of people in terms of order

155
Q

Nominal scale

A

Measurement divides variables into an ordered categories i.e. sex of sales people

156
Q

Ordinal scale

A

More mathematically complex than a nominal scale. Divides observations into categories but also provides information on order of those categories. Likert type scale one for strongly agree seven for strongly disagree

157
Q

Likert scale

A

A forced answer scale ranging categories from 1 to 10

158
Q

Interval scales

A

Has a property of order as well as the property of equal intervals between successive points on the measurement scale e.g. IQ tests are usually considered a representative of the interval scale

159
Q

Ratio scale

A

Most mathematically complex of the four measurement scales. It has properties of order and equal intervals as well as properties of an absolute zero point.makes it possible to multiply and divide racial scores to determine more precisely how much more or less of a characteristic one person has to another. Example Kelvin scale

160
Q

Descriptive statistics

A

Used to describe or samurais a distribution of set data

161
Q

Frequency distribution

A

Summarizing the data in terms of the number of frequency observations in each case

162
Q

Cumulative frequency

A

Indicate the total number of observation that falls at or below each category or score

163
Q

Shapes of distribution

Normal curve

A

Systematic bell shaped and defined by specific mathematical formula

164
Q

Shapes of distribution

Kurtisis

A

Refers to the relative peaked nice hike or flatness of the distribution

165
Q

Shapes of distribution

Platkurtic

A

Went to distribution is flatter

166
Q

Shapes of distribution

Leptokurtic

A

Went to distribution is peaked

167
Q

Shapes of distribution

Skewed distribution

A

More than half of the observations fall on one side of the distribution

168
Q

Shapes of distribution

Positively skewed distribution

A

Most of the scores are in the negative low side of the distribution the positive tail is extended

169
Q

Shapes of distribution

Negatively skewed distribution

A

Most scores are located on the positive high school side of the distribution and the negative tail is extended due to the presence of a few low scores

170
Q

Measures of central tendency

Mode

A

The score category that occurs the most frequently

171
Q

Measures of central tendency

Median

A

The score the divides a distribution in half when the data has become ordered from low to high. Useful for it it’s in sensitivity to outliers and open ended distributions where there are no specific upper and lower limits

172
Q

Multimodal

A

Two or more scores are categories that occur equally often

173
Q

Bimodal

A

When two scores are equal

174
Q

Susceptibility to sampling fluctuations

A

This means that, if a large number of samples are randomly selected from the population, the mold can be expected to vary considerably from sample to sample.

175
Q

Measures of central tendency

Arithmetic mean

A

M-X
Mean equals the sum of the means divided by number of means
Used for its lease to susceptibility to sample and fluctuation usually provides an unbiased estimate of the population mean

176
Q

Measure of variability

Range

A

Calculated by simply subtracting the lowest score in the distribution from The highest score

177
Q

Measure of variability

Variance mean square

A

Is a more thorough measurement of variability then the range because it’s calculations includes all the scores in the distribution rather than just the highest and lowest dance is calculated using

178
Q

Measure of variability

Standard deviation

A

The standard deviation is calculated by taking the square root of the variance

179
Q

Population parameters and sample statistics

A

Estimates population values based on obtain samples

180
Q

Characteristics of sampling distribution

A

Due to the effects of random chance factors, it is unlikely that any sample will perfectly represent the population from which it was drawn

181
Q

Sampling error

A

inaccuracies

182
Q

Inferential statistics test

A

Indicates where the obtain samples to distichs falls in the appropriate sampling distribution

183
Q

Rejection region

A

Region of unlikely values lights on both tales of the sampling distribution

184
Q

Retention region

A

Regions of likely values lies in the central portion of the sampling distribution

185
Q

Null hypothesis is rejected

A

Obtain samples statistics is in the rejection region

186
Q

No hypothesis is retained

A

Statistical tests indicate that the sample statistic lives in the retention region

187
Q

Alfa or level of significance

A

0.01 or 0.05 represents the sampling distribution in the rejection region and the remaining percentage represents the retention region

188
Q

Type I error = alpha

A

Occurs when an investigator rejects a true null hypothesis

189
Q

Type II error = beta

A

Occurs when an investigator retains a false null hypothesis

190
Q

Beta

A

Directly calculated for a particular study depending on the Alpha

191
Q

Inverse relationship

A

As the probability of making a Type I error increases the probability of making a Type II error Increases and vice versa

192
Q

Statistical power

A

A statistical test enables an experimenter to reject a faults Null hypothesis

193
Q

Using a one tailed test when appropriate

A

One tail test is more powerful than a two-tailed test

194
Q

Using a parametric test

A

Parametric statistical tests such as a t-test or ANOVA or more powerful than nonparametric test

195
Q

Homoscedacity

A

The variance of the population that the different groups represented are equal

196
Q

Critical values and degrees of freedom

A

Test that allows investigator to determine whether the obtains sample value is in the rejection or retention region of the sampling distribution this is done by comparing the tested to sticks to a critical value which is the number that corresponds to the boundary that divides the sampling distribution into rejection retention

197
Q

Chi– square test

A

Used to analyze the frequency of observation of a nominal variable test

198
Q

ANOVA

A

Analysis of variance is used to compare two or more means

199
Q

One-Way ANOVA

A

Is used want to study includes one independent variable and two or more dependent groups

200
Q

Factor analysis of variance

A

An extension of the one way ANOVA that is employed want to study includes two or more independent variables

201
Q

Assumptions

A

Use of the Pearson r and most other qualifications require that three assumptions be met

202
Q

Linearity

A

Assumption that there is a linear relationship between the variables relationship between the X-Men why can be summarized in a straight line

203
Q

Unrestricted range

A

Use of the Persons r is also based on the assumptions that there is an unrestricted range of scores on both variables

204
Q

Homoscrdasticity

A

The third assumption is that the range of why scores is about the same for the values of X

NCC (5 decks)

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