G4 : M2 BASIC DESCRIPTIVE STATISTICS

Cards (24)

  • Contingency Coefficient -A measure of association or correlation for categorical variables. It is used to determine the strength of association between two categorical variables in a contingency table.
  • Contingency Coefficient Formula
    1. Assignment of Contingency Coefficient
    Contingency Coefficient Strength of association
    0.0<CC<0.1 Not Appreciable
  • 2. Assignment of Contingency Coefficient
    Contingency Coefficient Strength of association
    0.1<CC<0.2 Weak
  • 3. Assignment of Contingency Coefficient
    Contingency Coefficient Strength of association
    0.2<CC<0.3 Medium
  • 4. Assignment of Contingency Coefficient
    Contingency Coefficient Strength of association
    0.3<CC Strong
  • KENDALL'S TAU
    • It is a coefficient that represents the degree of concordance between two columns ofranked data.
  • RELATIVE RISK
    • measures the likelihood of an event occurring in one group compared to another.
  • In the context of human resources, relative risk can be applied to various scenarios, such as:
    • Assessing the risk of turnover among different employee.
  • SKEWNESS
    • refers to the asymmetry of the distribution of data. Indicates whether the data are concentrated more on one side of the mean than the other.
  • In Human Resource context : Skewness can provide valuable insights into various aspects of employee behavior and performance. Including: Distribution of salaries and wages.
  • KURTOSIS
    • Describes the amount of peakedness of a distribution
  • 3 types of kurtosis:
    1. Leptokurtic distribution
    2. Mesokurtic distribution
    3. Platykurtic distribution
  • COVARIANCE
    • Measures the relationship between two variables, indicating how they change together.
  • Positive Covariance - increase or decrease simultaneously
    Negative Covariance - one increases while other decreases
  • Four Steps in Solving Covariance
    Step 1: Find the means of X and Y
    Step 2: Calculate the differences between each data point and its respective mean for both X and Y
    Step 3: Multiply these differences for each pair of data points
    Step 4: Find the average of the products
  • In HR context: Covariance can be a valuable statistical tool for analyzing relationships between different variables and understanding their impact on various aspects of HRM.
  • PERCENTILE - a term that describes how a score compares to other scores from the same set.
  • Application in HR context: Percentile can use in Pre-employment Test - This test may measure their technical skills, experience, or how they might react in a certain work situation. Their score would then be compared to other candidates by using a percentile rank.
  • Importance of Percentile Ranks in HR:
    1. Efficient - Percentile ranks are a fast and effective way for HR to decide the best option.
    2. Comparisons - Percentile ranks make it easier for HR to compare.
    3. Provides context - Percentile ranks make it easier to interpret a score or a data point within a data set.
  • Other Applications of Percentile Ranks in HR Field:
    1. Compensation Analysis
    2. Promotions
  • OUTLIERS
    • An outlier is a single data point that goes far outside the average value of a group of statistics. It is an individual that is markedly different from the norm in some respect.
  • Contingency ranges to 0 - 1
  • Kendall's tau ranges to -1.0 - 1.0