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 GroupOrdinal: Ordered categories
Example: Grades (A, B, C), Satisfaction level
Example:
Read MoreStatistics Essentials: Mean, Regression, Events & Sampling
Measures of Central Tendency
Explain measures of central tendency.
- Mean: The average value, calculated by summing all values and dividing by the number of observations.
- Median: The middle value when data is arranged in order; useful for skewed distributions.
- 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
Read MoreEssential 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
Read MoreAdvanced 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:
Quantitative Versus Qualitative Research Methods Comparison
Elements of Investigation: Quantitative vs. Qualitative
1. Environment (MARCO)
- Quantitative: Can be developed in a natural environment or a closed laboratory.
- Qualitative: In contact with the object being studied, in a natural setting.
2. Design Structure
- Quantitative: Requires a fixed design established a priori (in advance).
- Qualitative: Has an emergent design; it is not fixed in advance.
3. Goals and Flexibility
- Quantitative: Techniques are pre-set, aiming for technical flexibility.
- Qualitative: The reality
Statistical Test Interpretation and SPSS Decision Rules
Statistical Significance: The Main Rule
The decision rule for hypothesis testing is based on the p-value:
- p < 0.05: Significant → Reject H0 (Null Hypothesis)
- p ≥ 0.05: Not significant → Fail to reject H0
Choosing the Appropriate Test:
- 1 group vs known value → One-Sample T-Test
- 2 groups (different people) → Independent Samples T-Test
- 2 groups (same people before/after) → Paired Samples T-Test
- 3+ groups → ANOVA (+ Tukey Post-Hoc if significant)
- Numeric ↔ Numeric relationship → Correlation
- Predict