Mastering Statistical Methods and Data Analysis

Sampling Methods

  • Simple Random Sampling: Every subject has an equal probability of being selected. This provides a good representation but may be subject to non-response bias.
  • Systematic Sampling: This involves applying a selection interval k from a random starting point. While every subject has an equal probability of being selected, it is simple but may not provide a good representation if there is a pattern in the way subjects are lined up.
  • Stratified Sampling: The sampling frame is divided into
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Sampling, Correlation, and Multivariate Methods for Research

Sampling: Population, Sample, Census

Population, sample, census: The population of interest is the entire group researchers want to generalize to. A sample is the smaller group that is actually observed or measured. A census collects data from every single member of the population. Population = who you care about. Sample = who you study. Census = everyone in the population.

Representative vs. Biased Samples

Representative vs. biased samples: A representative sample (unbiased) gives every member of

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Data Types and Statistical Analysis Concepts Explained

Q1. Data Types: Categorical vs. Numerical

[8–9 Marks]

Answer:
Data comprises raw facts and figures collected for analysis and decision-making. Based on nature, data is mainly classified into Categorical data and Numerical data.

1) Categorical Data (Qualitative)

Categorical data represents qualities or categories and cannot be measured numerically.

Types:

  • Nominal: No natural order

    Example: Gender (Male/Female), Blood Group
  • Ordinal: Ordered categories

    Example: Grades (A, B, C), Satisfaction level

Example:

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Statistics Essentials: Mean, Regression, Events & Sampling

Measures of Central Tendency

Explain measures of central tendency.

  1. Mean: The average value, calculated by summing all values and dividing by the number of observations.
  2. Median: The middle value when data is arranged in order; useful for skewed distributions.
  3. Mode: The most frequently occurring value in the dataset.

Regression and Regression Equations

Describe regression and types of regression equations

Regression models the relationship between a dependent variable (y) and one or more independent variables

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Essential Statistics Concepts and Formulas

Fundamental Statistical Definitions

1. Define Mean: Mean is the average. It is calculated as the Sum of all values ÷ Number of values.

2. Find Mean of First Ten Natural Numbers: The first 10 natural numbers are 1 to 10. The sum is 55. Mean = 55 ÷ 10 = 5.5.

3. Define Median: The Median is the middle value when data is arranged in ascending or descending order.

4. Find Median of First Ten Even Numbers: The first 10 even numbers are 2, 4, 6, 8, 10, 12, 14, 16, 18, 20. For an even count (10 values), the

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Advanced Statistical Analysis and Econometrics in SPSS

Skewness and Kurtosis: Distribution Shapes

What They Measure

  • Skewness measures the asymmetry of a distribution around its mean.
    • Positive (right) skew: Long right tail—most observations are on the left (e.g., income).
    • Negative (left) skew: Long left tail—most observations are on the right.
    • Skewness = 0: Symmetric distribution (ideally normal).
  • Kurtosis measures tailedness and peakness—how heavy the tails are relative to a normal distribution.
    • Mesokurtic: Kurtosis ≈ 3 (normal distribution).
    • Leptokurtic:
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