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SHRM CP > Analytical Aptitude > Flashcards

Analytical Aptitude Flashcards

1
Q

Aspects of analytical aptitude

A
  • data advocacy
  • data gathering
  • data analysis
  • evidence-based decision making
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2
Q

applying results of data analysis to make decisions

A

Evidence-Based Decision Making

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3
Q

6 Steps in Evidence-Based Decision Making

A
  1. Ask - translate problem into a question
  2. Acquire - gather info from varied sources
  3. Appraise - determine whether evidence is relevant, accurate, reliable, unbiased
  4. Aggregate - combine/organize data for analysis
  5. Apply - see/draw logical conclusions, develop solutions
  6. Assess - monitor and measure solution
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4
Q

How to become an HR data advocate

A
  • develop a questioning mind
  • build fluency in scientific literature of HR
  • gather data on a continuous basis
  • use evidence when communicating with stakeholders
  • institutionalize the competency in the HR function
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5
Q

Objective measurements verified using statistical analysis

A

Quantitative Data

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6
Q

Subjective evaluation of actions, feelings, and behaviors

A

Qualitative Data

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7
Q

Biggest challenge when using interviews as a data source

A

Avoiding biases

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8
Q

Most important consideration when using a focus group

A

The participants are representative of the larger group - randomly selected

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9
Q

Begins discussion with core ideas, connecting and grouping similar ideas

A

Mind Mapping

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10
Q

Group categorizes data until relationships are drawn

A

Affinity Diagramming

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11
Q

Rounds of suggesting ideas, eliminating irrelevant or redundant, group agrees on importance of remaining items

A

Nominal Group Technique

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12
Q

Collect anonymous info from group, then group identifies strengths and weaknesses of ideas anonymously

A

Delphi Technique

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13
Q

Most important when using observation as a data source

A

the observer must be unseen

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14
Q

Most important when using artifacts as a data source

A

researcher must understand the principles of the culture

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15
Q

The ability of a data gathering tool to provide results that are consistent

A

Reliability of data

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16
Q

The ability of data gathering tool to measure what it is intended to

A

Validity of data

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17
Q

Used when data cannot be obtained from entire population

A

Statistical Sampling

18
Q

What may result in data errors

A

Biases in sampling, selection, response, performance, and measurement

19
Q

Process where incomplete sets, anomalies, errors, and gaps in data are identified and addressed

A

Data Cleansing

20
Q

Measures of central tendency

A

mean, median, and mode

21
Q

Median

A

middle value in a range of values

22
Q

Mode

A

most frequently occurring value in a data set

23
Q

Unweighted Mean

A

average - sum of all values divided by the number of values

24
Q

Weighted Mean

A

When some data have more significance or effect - multiply individual values by a weighted factor

25
Q

Used to sort data into groups according to some factor

A

Frequency distributions

26
Q

Divide data into quarters

A

Quartiles

27
Q

Indicates proportion of dataset at a certain percentage

A

Percentile

28
Q

Distance of any data point from the center of a distribution when distributed in a normal pattern

A

Standard Deviation

29
Q

Low Standard Deviation bell curve

A

Tall and narrow

30
Q

High Standard Deviation bell curve

A

Short and wide

31
Q

Identifies degree of difference between planned and actual performance

A

Variance analysis

32
Q

Compares the relative size of two variable and yields a percentage

A

Ratio analysis

33
Q

Examines data from different points in time to determine if a variance is isolated or part of a longer trend

A

Trend analysis

34
Q

Determine whether a relationship exists between variables and the strength of the relationship

A

Regression analysis

35
Q

Starts with result and works backwards to identify preceding cause

A

Root cause analysis

36
Q

Test possible effects of altering details of a situation to see how the outcomes vary under different conditions

A

Scenario analysis

37
Q

Used to present high-level impression of data distribution as percentage of the whole

A

Pie Chart

38
Q

Used to sort data and support rapid comparison of categories of data as bars

A

Histogram

39
Q

Plots data on two axes, used to test for presence of developing trends

A

Trend diagram

40
Q

Distinguishes the vital few categories that contribute to most of the issue, supports more focused quality improvement activities

A

Pareto Chart

41
Q

Used to test possible causal relationships and narrow focus

A

Scatter diagram

SHRM CP (23 decks)

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