Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

MRCB Exams > SPSSFinal Exam > Flashcards

SPSSFinal Exam Flashcards

1
Q

Bivariate - cat, cat - graph?

A

clustered, stacked bar graph or pie chart

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Bivariate - cat. scale - Graph?

A

Boxplot

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Bivariate - scale scale - graph

A

Scatter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Bivariate - cat. cat. - Table

A

Crosstabs

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Bivariate - cat. scale - Table

A

Descriptive

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Bivariate - scale scale - Table

A

Correlations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Bivariate - cat. cat. - Stat?

A

Pearson Chi-square test

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Bivariate - cat. scale - Stat?

A

T-test -> compare 2 means
ANOVA -> more than 2

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Bivariate - scale scale - Stat?

A

T-test for corr=0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

when agglomerative hierarchical cluster?

A
  • we want to know about the agglomeration process (similarities and diff. between groups).
  • Limited cases.
  • Homogeneous set of data - all scale or categorical.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

How hierarchical cluster?

A

> Analyze > Classify > Hierarchical Cluster > var. in ‘Variable’ > ind. var. in ‘Case label variable > Statistics: Proximity Matrix, Agglomeration schedule if you want a specific # Clusters: Cluster Membership > Plots: Dendogram, Icicle=None > Method: Centroid Clustering, Squared Euclidian Distance if var. are diff in size - Transform > Standardize
To explore groups > Save clustership > Analyze > Compare Means > Means > clust. var. in ‘Dependent List’ > ind. var. in ‘Independent List’
To know stat. sig. > ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

How bar graphs?

A

> Graphs > Legacy Dialogs > Bar > clustered or stacked > categorical v. in ‘Category axis’ > v. diff. section in ‘Def. stacks by’ > numerical v. in ‘Columns’

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

how pie chart?

A

> Graphs > Legacy Dialogs > Pie > summ. for groups > Define

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

How boxplot?

A

> Graphs > Legacy Dialogs > Boxplot > scale v. in ‘Variable’ >

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

How scatter?

A

> Graphs > Legacy Dialogs > Scatter/Dot > indep. v. in ‘Row’ > dep. v. in ‘Column’

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

How crosstabs?

A

> Analyze > Descriptive analytics > Crosstabs > x var. as ‘Row’ & y var. as ‘Column’ > Cells, Percentages ‘Row’

17
Q

How descriptive?

A

> Analyze > Descriptive analytics > Explore > scale/dep./split var. as ‘Dependent list’ & nominal var. as ‘Factor list’

18
Q

How correlations?

A

> Analyze > Correlate > Bivariate > two var. in Variables

19
Q

How pearson chi-square

A

Null Hypothesis = Independency between x and y
> Analyze > Descriptive analytics > Crosstabs > x var. as ‘Row’ & y var. as ‘Column’ > Statistics > Chi-square
> p-value/sig. is the risk taken if rejecting Null is True.
→ sig. <= 5% reject Null / sig. >= 5% accept Null
Statistical relationship → reject Null

20
Q

How t-test?

A

Null Hypothesis = No relationship between x and y
> Analyze > Compare means > Independent-Samples t-test or Paired Sample t-test (if obs. can belong to two samples) > scale var. as ‘Test variables’ & cat. var. as ‘Grouping variable’ > Define groups > define the two groups of cat. var.
> t-value → statistic value > df → degrees of freedom > Sig. (2-tailed) → if <0.05 indicates significant difference.

21
Q

how anova?

A

Null Hypothesis = No relationship between x and y
> Analyze > Compare means > One-way ANOVA > scale var. as ‘Dependent List’ & cat. var. as ‘Factor’
> F-value → statistic value > df → degrees of freedom > Sig. → if <0.05 indicates significant difference.

22
Q

How t-test corr=0?

A

> Analyze > Correlate > Bivariate > scale var. in dialog box > check Pearson & Two-tailed
Sig. (2-tailed) → if <0.05 indicates significant difference from 0

23
Q

When two-step cluster?

A

Used when…
Not interested in agglomeration process but only in the final groups obtained.
Large number of cases/indiv.

24
Q

how two-step cluster?

A

> Analyze > Classify > Two-Step Cluster W > var. in ‘Categorical variables’ & ‘Continuous variables’ > Distance Measure : Euclidian
Analyze: Cluster quality, click on the column(s), change order of importance
Improving cluster > Change settings > Option > Specify fixed > Save cluster membership val.

25
Q

How regression?

A

> Analyze > Regression > Linear > var. of interest in ‘Dependent’ & explanatory. cand. var. in ‘Independent(s)’

26
Q

Regression what is R?

A

> R → multiple corr. coef. betw. obs. and pred. val. of dep. var.

27
Q

Regression - what is R squared?

A

> R-squared → ↑ = better fit

28
Q

Regression - what is standard error estimate?

A

> Stand. Err. Estim. → avg. dist. obs. from reg. line

29
Q

Regression - what is F?

A

> F → overall fit?

30
Q

Regression - what is sig.

A

> Sig. or p-value → if p<5%, stat. significant = ind. var. predict dep. var

31
Q

Regression - what is Beta?

A

> Beta → Strength & direction of rel. betw. ind. & dep. var.

MRCB Exams (2 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions