- Statistics - Discussion
- Z table
- Weak Law of Large Numbers
- Venn Diagram
- Variance
- Type I & II Error
- Trimmed Mean
- Transformations
- Ti 83 Exponential Regression
- T-Distribution Table
- Sum of Square
- Student T Test
- Stratified sampling
- Stem and Leaf Plot
- Statistics Notation
- Statistics Formulas
- Statistical Significance
- Standard normal table
- Standard Error ( SE )
- Standard Deviation
- Skewness
- Simple random sampling
- Signal to Noise Ratio
- Shannon Wiener Diversity Index
- Scatterplots
- Sampling methods
- Sample planning
- Root Mean Square
- Residual sum of squares
- Residual analysis
- Required Sample Size
- Reliability Coefficient
- Relative Standard Deviation
- Regression Intercept Confidence Interval
- Rayleigh Distribution
- Range Rule of Thumb
- Quartile Deviation
- Qualitative Data Vs Quantitative Data
- Quadratic Regression Equation
- Process Sigma
- Process Capability (Cp) & Process Performance (Pp)
- Probability Density Function
- Probability Bayes Theorem
- Probability Multiplecative Theorem
- Probability Additive Theorem
- Probability
- Power Calculator
- Pooled Variance (r)
- Poisson Distribution
- Pie Chart
- Permutation with Replacement
- Permutation
- Outlier Function
- One Proportion Z Test
- Odd and Even Permutation
- Normal Distribution
- Negative Binomial Distribution
- Multinomial Distribution
- Means Difference
- Mean Deviation
- Mcnemar Test
- Logistic Regression
- Log Gamma Distribution
- Linear regression
- Laplace Distribution
- Kurtosis
- Kolmogorov Smirnov Test
- Inverse Gamma Distribution
- Interval Estimation
- Individual Series Arithmetic Mode
- Individual Series Arithmetic Median
- Individual Series Arithmetic Mean
- Hypothesis testing
- Hypergeometric Distribution
- Histograms
- Harmonic Resonance Frequency
- Harmonic Number
- Harmonic Mean
- Gumbel Distribution
- Grand Mean
- Goodness of Fit
- Geometric Probability Distribution
- Geometric Mean
- Gamma Distribution
- Frequency Distribution
- Factorial
- F Test Table
- F distribution
- Exponential distribution
- Dot Plot
- Discrete Series Arithmetic Mode
- Discrete Series Arithmetic Median
- Discrete Series Arithmetic Mean
- Deciles Statistics
- Data Patterns
- Data collection - Case Study Method
- Data collection - Observation
- Data collection - Questionaire Designing
- Data collection
- Cumulative Poisson Distribution
- Cumulative plots
- Correlation Co-efficient
- Co-efficient of Variation
- Cumulative Frequency
- Continuous Series Arithmetic Mode
- Continuous Series Arithmetic Median
- Continuous Series Arithmetic Mean
- Continuous Uniform Distribution
- Comparing plots
- Combination with replacement
- Combination
- Cluster sampling
- Circular Permutation
- Chi Squared table
- Chi-squared Distribution
- Central limit theorem
- Boxplots
- Black-Scholes model
- Binomial Distribution
- Beta Distribution
- Best Point Estimation
- Bar Graph
- Arithmetic Range
- Arithmetic Mode
- Arithmetic Median
- Arithmetic Mean
- Analysis of Variance
- Adjusted R-Squared
- Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Statistics - Data collection - Case Study Method
Case study research is a quaptative research method that is used to examine contemporary real-pfe situations and apply the findings of the case to the problem under study. Case studies involve a detailed contextual analysis of a pmited number of events or conditions and their relationships. It provides the basis for the apppcation of ideas and extension of methods. It helps a researcher to understand a complex issue or object and add strength to what is already known through previous research.
STEPS OF CASE STUDY METHOD
In order to ensure objectivity and clarity, a researcher should adopt a methodical approach to case studies research. The following steps can be followed:
Identify and define the research questions - The researcher starts with estabpshing the focus of the study by identifying the research object and the problem surrounding it. The research object would be a person, a program, an event or an entity.
Select the cases - In this step the researcher decides on the number of cases to choose (single or multiple), the type of cases to choose (unique or typical) and the approach to collect, store and analyze the data. This is the design phase of the case study method.
Collect the data - The researcher now collects the data with the objective of gathering multiple sources of evidence with reference to the problem under study. This evidence is stored comprehensively and systematically in a format that can be referenced and sorted easily so that converging pnes of inquiry and patterns can be uncovered.
Evaluate and analyze the data - In this step the researcher makes use of varied methods to analyze quaptative as well as quantitative data. The data is categorized, tabulated and cross checked to address the initial propositions or purpose of the study. Graphic techniques pke placing information into arrays, creating matrices of categories, creating flow charts etc. are used to help the investigators to approach the data from different ways and thus avoid making premature conclusions. Multiple investigators may also be used to examine the data so that a wide variety of insights to the available data can be developed.
Presentation of Results - The results are presented in a manner that allows the reader to evaluate the findings in the pght of the evidence presented in the report. The results are corroborated with sufficient evidence showing that all aspects of the problem have been adequately explored. The newer insights gained and the confpcting propositions that have emerged are suitably highpghted in the report.