Statistics

1. 1When using a between groups design on scale data you should use

   1. AIndependent t-test
   2. BDependent t-test
   3. CMann-Whitney
   4. DWilcoxon
2. 2When using a within groups design on scale data you should use

   1. ADependent t-test
   2. BIndependent t-test
   3. CMcNemar
   4. DChi square
3. 3When using a between groups design on ordinal data you should use

   1. AMann-Whitney
   2. BWilcoxon
   3. CPearson product-moment
   4. DMcNemar
4. 4When using a within groups design on ordinal data you should use

   1. AWilcoxon
   2. BMann-Whitney
   3. CChi square
   4. DSpearman rank-order
5. 5When using a between groups design on nominal data you should use

   1. AChi square
   2. BMcNemar
   3. CIndependent t-test
   4. DMann-Whitney
6. 6When using a within groups design on nominal data you should use

   1. AMcNemar
   2. BMann-Whitney
   3. CChi square
   4. DPaired t-test
7. 7When using a within groups design on scale data in a correlational study you should use

   1. APearson product-moment
   2. BSpearman rank-order
   3. CChi square
   4. DWilcoxon
8. 8When using a within groups design on ordinal data in a correlational study you should use

   1. ASpearman rank-order
   2. BPearson product-moment
   3. CMcNemar
   4. DIndependent t-test
9. 9Identify the parametric requirements when using a between groups design

   1. AScale data
   2. BNormal distribution
   3. CEqual variances
   4. DOrdinal data
10. 10Identify the parametric requirements when using a within groups design

    1. AScale data
    2. BNormal distribution
    3. CEqual variances
    4. DNominal data

11. 11Identify how you can check for a normal distribution and equal variances

    1. ANormal distribution: skew and kurtosis using the 2 x SE rule
    2. BEqual variances: Levene test result > 0.05
    3. CNormal distribution: Levene test result > 0.05
    4. DEqual variances: skew and kurtosis using the 2 x SE rule
12. 12How would you report both within and between group designs on scale data

    1. At ( ) = , p [ - tailed]
    2. Bu = , N1 = , N2 = , p [ - tailed]
    3. Ct = , N = , p [ - tailed]
    4. Dy = a + (b x score)
13. 13How would you report a between groups design on ordinal data (Mann-Whitney)

    1. Au = , N1 = , N2 = , p [ - tailed]
    2. Bt = , N = , p [ - tailed]
    3. Cy = a + (b x score)
    4. Dt ( ) = , p [ - tailed]
14. 14How would you report a within groups design on ordinal data (Wilcoxon)

    1. At = , N = , p [ - tailed]
    2. Bt ( ) = , p [ - tailed]
    3. CX2 = , df = , p [ - tailed]
    4. Dy = a + (b x score)
15. 15How would you report a between groups design on nominal data (Chi square)

    1. AX2 = , df = , p [ - tailed]
    2. By = a + (b x score)
    3. Ct ( ) = , p [ - tailed]
    4. Dt = , N = , p [ - tailed]
16. 16How would you report a within groups design on nominal data (McNemar)

    1. AX2 = , N = , p [ - tailed]
    2. BX2 = , df = , p [ - tailed]
    3. Ct = , N = , p [ - tailed]
    4. Dt ( ) = , p [ - tailed]
17. 17How would you report a within groups design on both scale (Pearson product-moment) and ordinal (Spearman rank-order) data in a correlational study

    1. Ay = a + (b x score)
    2. BX2 = , df = , p [ - tailed]
    3. Ct ( ) = , p [ - tailed]
    4. Du = , N1 = , N2 = , p [ - tailed]
18. 18Mode (central tendency) can be used for

    1. AScale
    2. BOrdinal
    3. CNominal
    4. DStandard deviation
19. 19Median (central tendency) can be used for

    1. AScale
    2. BOrdinal
    3. CNominal
    4. DVariance
20. 20Mean (central tendency) can be used for

    1. AScale
    2. BOrdinal
    3. CNominal
    4. DRange
21. 21The difference between the highest and lowest scores in a distribution

    1. ARange
    2. BVariance
    3. CStandard deviation
    4. DInterquartile range
22. 22The standard deviation of a distribution squared

    1. AVariance
    2. BRange
    3. CPercentile
    4. DZ-score
23. 23A measure representing the average difference between the scores and the mean of a distribution

    1. AStandard deviation
    2. BStandard error
    3. CRange
    4. DInterquartile range
24. 24The range of the central 50% of all scores or observations within a dataset

    1. AInterquartile range
    2. BRange
    3. CVariance
    4. DStandard deviation
25. 25Range, Interquartile range, Standard deviation and Variance are all examples of

    1. AMeasures of dispersion
    2. BMeasures of central tendency
    3. CStandard scores
    4. DParametric tests
26. 26A measure indicating a scores position in relation to other scores, via the proportion of scores below that particular value

    1. APercentile
    2. BZ-score
    3. CT-score
    4. DInterquartile range
27. 27A value indicating the distance of any score from the mean score of a dataset, as measured by the number of standard deviations that particular score is from the mean

    1. AZ-score
    2. BT-score
    3. CStandard error
    4. DStandard deviation
28. 28Removes negatives from z-scores

    1. AT-score
    2. BRange
    3. CVariance
    4. DPercentile
29. 29Identify the Z-score equation

    1. A(given score - mean of sample scores) / standard deviation of scores
    2. Bt = , N = , p [ - tailed]
    3. C(given sample mean - mean of sample means) / standard error of sample means
    4. D(given sample mean - population mean) / standard error of sample means
30. 30The smaller the standard error, the more representative of the population

    1. AVerdadero
    2. BFalso
31. 31The smaller the standard deviation, the more representative of the population

    1. AVerdadero
    2. BFalso
32. 32The smaller the standard error, the more representative of the sample

    1. AVerdadero
    2. BFalso
33. 33The smaller the standard deviation, the more representative of the sample

    1. AVerdadero
    2. BFalso

Descripción

Degree (RDA1) Psychology Year 1 - Semester 2 Test sobre Statistics, creado por Róisín Farmer el 03/05/2016.

Autor

Róisín Farmer

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English

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psychology year 1 - semester 2rda1degree

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