National Counselor Exam with correct
| | | | |
answers
Convergent |Validation |- |correct |answer |Refers |to |times |when |there |is |a |high |correlation |
between |the |concept |the |test |is |meant |to |study |and |OTHER |constructs.
Bergan's |Behavioral |Model |of |Consultation |- |Four |Stages: |- |correct |answer |- |Problem |
identification
- |Problem |analysis
- |Plan |implementation
- |Problem |evaluation
Consultation |is |used |when |counselors |would |like |to |function |more |effectively |in |individual, |
group, |or |community |settings. |Bergen's |model |uses |a |BEHAVIORAL |APPROACH |that |
emphasizes |the |verbal |interactions |during |consultation. |Bergan's |model |also |focuses |on |
problem |behaviors, |their |antecedents, |and |their |consequences.
Descriptive |statistics |- |correct |answer |Aims |to |describe |collected |data |and |includes: |
- |means
- |percentages
- |standard |deviations
- |frequency |counts.
Analysis |of |variance |- |correct |answer |A |type |of |inferential |data |used |to |measure |the |
PROBABILITY |of |an |EVENT |occurring |in |the |POPULATION.
Five |Stages |of |the |Racial/Cultural |Identity |Developmental |Model? |- |correct |answer |- |
Conformity
- |Dissonance
,- |Desistance |& |Immersion
- |Introspection
- |Integrative |awareness. |
Integrative |awareness |occurs |when |the |individual |can |appreciate |aspects |of |both |the |
dominant |and |minority |cultures.
Four |levels |of |measurement: |- |correct |answer |Nominal, |Ordinal, |Interval, |and |Ratio.
Nonparametric |statistical |measures |- |correct |answer |Often |used |with |DESCRIPTIVE |DATA |and |
should |be |used |with |NOMINAL |DATA |(numbers |that |represent |a |category |or |quality). |Ex: |chi-
square
The |typical |range |for |the |STANDARD |DEVIATION |when |calculating |a |Z-SCORE |- |correct |answer |
The |range |for |standard |deviation |of |a |z-score |is |-3.0 |to |3.0.
For |a |z-score, |the |mean |is |0 |and |the |standard |deviation |is |1.0. |When |the |raw |score |is |below |
the |mean, |the |z-score |is |negative, |and |when |the |raw |score |is |above |the |mean, |the |z-score |is |
positive.
Why |might |the |t-test |be |used? |- |correct |answer |To |determine |whether |the |mean |scores |of |
two |groups |are |significantly |different |from |each |other |
This |test |compares |the |t |value |from |the |first |calculation |to |the |t |value |in |the |second |
calculation |to |find |whether |the |mean |scores |of |the |two |groups |are |significantly |different |from |
each |other.
Coefficient |of |nondetermination |- |correct |answer |The |coefficient |of |NONdetermination |is |the |
unique |variance.
To |find |the |coefficient |of |nondetermination, |first |find |the |coefficient |of |determination |by |
squaring |the |correlation |(.80 |x |.80 |= |.64, |or |64%). |
,Then |subtract |this |from |100% |to |find |the |coefficient |of |NONdetermination |(100% |- |64% |= |
36%).
Standardized |scores |- |correct |answer |Standardized |scores |are |helpful |when |comparing |several |
different |test |scores |for |the |same |person, |as |direct |comparisons |between |different |tests |are |
impossible. |
Standardizing |scores |allows |for |continuity |and |an |equality |of |units. |
The |two |most |common |standardized |scores |are |z-scores |and |T-scores, |both |of |which |are |
conversions |of |raw |score |distributions. |
Standardized |scores |express |the |person's |distance |from |the |MEAN, |NOT |the |median, |in |terms |
of |the |standard |deviation |from |that |standard |score |distribution.
Kruskal-Wallis |test |(nonparametric |statistic) |- |correct |answer |- |Used |when |the |researcher |has |
MORE |THAN |TWO |MEAN |SCORES |on |a |SINGLE |VARIABLE |also |known |as |a |nonparametric |one-
way |analysis |of |variance. |
- |Nonparametric |statistics |are |used |when |it |is |uncertain |whether |the |distribution |of |scores |
falls |along |a |normal |curve |or |whether |the |variance |of |the |test |sample |represents |the |variance |
within |the |general |population.
Nonparametric |statistical |measures |- |correct |answer |- |Mann-Whitney |U |test |
- |Wilcoxen |signed-rank |test |
- |Kruskal-Wallis |test |
Nonparametric |statistics |are |used |when |it |is |uncertain |whether |the |distribution |of |scores |falls |
along |a |normal |curve |or |whether |the |variance |of |the |test |sample |represents |the |variance |
within |the |general |population.
, Four |steps |in |the |Planning |of |a |Counseling |Program |- |correct |answer |Conceptualization |-> |
Development |-> |Implementation |->Evaluation
It |is |important |to |take |orderly |and |careful |steps |to |ensure |that |the |program |is |thoughtfully |
executed. |Essential |steps |in |program |planning, |in |order, |are |conceptualization, |which |includes |
examining |broader |systems |and |assessment |needs; |development |of |goals |and |objectives |of |
the |program; |implementation; |and |evaluation |of |the |program, |including |whether |goals |and |
objectives |were |met.
When |you |would |use |a |nonparametric |test? |- |correct |answer |When |it |is |uncertain |whether |
the |distribution |of |scores |falls |along |a |normal |curve |OR |whether |the |variance |of |the |test |
sample |represents |the |variance |within |the |general |population. |
Nonparametric |statistics |are |typically |used |with |NOMINAL |DATA, |when |numbers |represent |a |
variable's |qualities, |and |ordinal |data, |when |categories |have |a |definitive |order. |
Examples |of |nonparametric |statistical |measure: |Chi-square, |Mann-Whitney |U |test, |Wilcoxen |
signed-rank |test, |and |Kruskal-Wallis |test.
The |square |of |the |standard |deviation |is |called |__________. |- |correct |answer |Variance |
Refers |to |the |degree |to |which |scores |are |different |from |each |other. |When |measuring |
variability, |researchers |may |use |standard |deviation |(SD) |to |describe |the |variability |within |a |
distribution |of |scores. |Variance |is |the |square |of |the |standard |deviation |and |is |used |when |
conducting |statistical |analyses.
Solomon |Four-Group |Design |is |used? |- |correct |answer |When |you |want |to |determine |the |effect
|of |a |PRETEST.
Some |researchers |use |pretests |to |measure |baseline |characteristics, |traits, |or |behaviors |of |test |
participants. |The |Solomon |four-group |design |allows |researchers |to |examine |the |effect |of |the |
pretest |on |the |test |treatment. |The |four |groups |include |measurements |of |whether |the |pretest |
and |treatment |combined |made |a |difference, |whether |the |pretest |alone |made |a |difference, |
| | | | |
answers
Convergent |Validation |- |correct |answer |Refers |to |times |when |there |is |a |high |correlation |
between |the |concept |the |test |is |meant |to |study |and |OTHER |constructs.
Bergan's |Behavioral |Model |of |Consultation |- |Four |Stages: |- |correct |answer |- |Problem |
identification
- |Problem |analysis
- |Plan |implementation
- |Problem |evaluation
Consultation |is |used |when |counselors |would |like |to |function |more |effectively |in |individual, |
group, |or |community |settings. |Bergen's |model |uses |a |BEHAVIORAL |APPROACH |that |
emphasizes |the |verbal |interactions |during |consultation. |Bergan's |model |also |focuses |on |
problem |behaviors, |their |antecedents, |and |their |consequences.
Descriptive |statistics |- |correct |answer |Aims |to |describe |collected |data |and |includes: |
- |means
- |percentages
- |standard |deviations
- |frequency |counts.
Analysis |of |variance |- |correct |answer |A |type |of |inferential |data |used |to |measure |the |
PROBABILITY |of |an |EVENT |occurring |in |the |POPULATION.
Five |Stages |of |the |Racial/Cultural |Identity |Developmental |Model? |- |correct |answer |- |
Conformity
- |Dissonance
,- |Desistance |& |Immersion
- |Introspection
- |Integrative |awareness. |
Integrative |awareness |occurs |when |the |individual |can |appreciate |aspects |of |both |the |
dominant |and |minority |cultures.
Four |levels |of |measurement: |- |correct |answer |Nominal, |Ordinal, |Interval, |and |Ratio.
Nonparametric |statistical |measures |- |correct |answer |Often |used |with |DESCRIPTIVE |DATA |and |
should |be |used |with |NOMINAL |DATA |(numbers |that |represent |a |category |or |quality). |Ex: |chi-
square
The |typical |range |for |the |STANDARD |DEVIATION |when |calculating |a |Z-SCORE |- |correct |answer |
The |range |for |standard |deviation |of |a |z-score |is |-3.0 |to |3.0.
For |a |z-score, |the |mean |is |0 |and |the |standard |deviation |is |1.0. |When |the |raw |score |is |below |
the |mean, |the |z-score |is |negative, |and |when |the |raw |score |is |above |the |mean, |the |z-score |is |
positive.
Why |might |the |t-test |be |used? |- |correct |answer |To |determine |whether |the |mean |scores |of |
two |groups |are |significantly |different |from |each |other |
This |test |compares |the |t |value |from |the |first |calculation |to |the |t |value |in |the |second |
calculation |to |find |whether |the |mean |scores |of |the |two |groups |are |significantly |different |from |
each |other.
Coefficient |of |nondetermination |- |correct |answer |The |coefficient |of |NONdetermination |is |the |
unique |variance.
To |find |the |coefficient |of |nondetermination, |first |find |the |coefficient |of |determination |by |
squaring |the |correlation |(.80 |x |.80 |= |.64, |or |64%). |
,Then |subtract |this |from |100% |to |find |the |coefficient |of |NONdetermination |(100% |- |64% |= |
36%).
Standardized |scores |- |correct |answer |Standardized |scores |are |helpful |when |comparing |several |
different |test |scores |for |the |same |person, |as |direct |comparisons |between |different |tests |are |
impossible. |
Standardizing |scores |allows |for |continuity |and |an |equality |of |units. |
The |two |most |common |standardized |scores |are |z-scores |and |T-scores, |both |of |which |are |
conversions |of |raw |score |distributions. |
Standardized |scores |express |the |person's |distance |from |the |MEAN, |NOT |the |median, |in |terms |
of |the |standard |deviation |from |that |standard |score |distribution.
Kruskal-Wallis |test |(nonparametric |statistic) |- |correct |answer |- |Used |when |the |researcher |has |
MORE |THAN |TWO |MEAN |SCORES |on |a |SINGLE |VARIABLE |also |known |as |a |nonparametric |one-
way |analysis |of |variance. |
- |Nonparametric |statistics |are |used |when |it |is |uncertain |whether |the |distribution |of |scores |
falls |along |a |normal |curve |or |whether |the |variance |of |the |test |sample |represents |the |variance |
within |the |general |population.
Nonparametric |statistical |measures |- |correct |answer |- |Mann-Whitney |U |test |
- |Wilcoxen |signed-rank |test |
- |Kruskal-Wallis |test |
Nonparametric |statistics |are |used |when |it |is |uncertain |whether |the |distribution |of |scores |falls |
along |a |normal |curve |or |whether |the |variance |of |the |test |sample |represents |the |variance |
within |the |general |population.
, Four |steps |in |the |Planning |of |a |Counseling |Program |- |correct |answer |Conceptualization |-> |
Development |-> |Implementation |->Evaluation
It |is |important |to |take |orderly |and |careful |steps |to |ensure |that |the |program |is |thoughtfully |
executed. |Essential |steps |in |program |planning, |in |order, |are |conceptualization, |which |includes |
examining |broader |systems |and |assessment |needs; |development |of |goals |and |objectives |of |
the |program; |implementation; |and |evaluation |of |the |program, |including |whether |goals |and |
objectives |were |met.
When |you |would |use |a |nonparametric |test? |- |correct |answer |When |it |is |uncertain |whether |
the |distribution |of |scores |falls |along |a |normal |curve |OR |whether |the |variance |of |the |test |
sample |represents |the |variance |within |the |general |population. |
Nonparametric |statistics |are |typically |used |with |NOMINAL |DATA, |when |numbers |represent |a |
variable's |qualities, |and |ordinal |data, |when |categories |have |a |definitive |order. |
Examples |of |nonparametric |statistical |measure: |Chi-square, |Mann-Whitney |U |test, |Wilcoxen |
signed-rank |test, |and |Kruskal-Wallis |test.
The |square |of |the |standard |deviation |is |called |__________. |- |correct |answer |Variance |
Refers |to |the |degree |to |which |scores |are |different |from |each |other. |When |measuring |
variability, |researchers |may |use |standard |deviation |(SD) |to |describe |the |variability |within |a |
distribution |of |scores. |Variance |is |the |square |of |the |standard |deviation |and |is |used |when |
conducting |statistical |analyses.
Solomon |Four-Group |Design |is |used? |- |correct |answer |When |you |want |to |determine |the |effect
|of |a |PRETEST.
Some |researchers |use |pretests |to |measure |baseline |characteristics, |traits, |or |behaviors |of |test |
participants. |The |Solomon |four-group |design |allows |researchers |to |examine |the |effect |of |the |
pretest |on |the |test |treatment. |The |four |groups |include |measurements |of |whether |the |pretest |
and |treatment |combined |made |a |difference, |whether |the |pretest |alone |made |a |difference, |
