Market Segmentation and Analysis Techniques
Market Segmentation Techniques
Cluster Analysis: This is a segmentation technique, a process by which we identify groups of consumers according to particular characteristics, with the aim of searching for a differentiated offer for each. We seek:
- Uniformity Inside: Maximize the difference between groups.
- Heterogeneity Between Groups: Maximize the difference between groups.
Conclusions: To determine what group/name and p-value > 0.05, accept the null hypothesis (H0) which means no difference between
Read MoreMultiple Linear Regression Assumptions and Diagnostics
Key Assumptions of Multiple Linear Regression (MLR)
Important Information from Midterm:
- MLR1: Linearity -> The model is linear in parameters. (Linearity = residuals have a mean of zero for every level of the fitted values and predictors)
- MLR2: Random Sample -> The data is randomly sampled from the population, ensuring that the sample represents the population.
- MLR3: No Perfect Collinearity -> The independent variables are not perfectly correlated, so the model can estimate coefficients uniquely.
Epidemiology: Understanding Disease Patterns and Risk Factors
Epidemiology
Epidemiology is the study of the distribution and determinants of disease or other health-related outcomes in human populations. It is also the application of that study to control health problems.
Etiology
- Etiology refers to all the determinants of a disease.
- These determinants can be physical, psychological, or behavioral.
- Rarely is there just one determinant.
Prevalence
- Period Prevalence: The proportion of cases over a length of time.
- Point Prevalence: The proportion of cases at one specific
Statistical Variables and Data Analysis Exercises
Exercise 1: Identifying Qualitative and Quantitative Variables
Indicate which variables are qualitative and which are quantitative:
- Favorite Food (Qualitative)
- Profession you like (Qualitative)
- Number of goals scored by your favorite team last season (Quantitative)
- Number of students in your Institute (Quantitative)
- The eye color of your classmates (Qualitative)
- IQ of your classmates (Quantitative)
Exercise 2: Identifying Discrete and Continuous Variables
Indicate which variables are discrete and which are
Read MoreStatistical Inference and Regression Analysis: Key Concepts
Statistical Inference and Regression Analysis
Statistical Inference: Drawing conclusions about a population based on information from a sample.
Standard Error: Measures the variability of the sample mean estimate, calculated based on the standard deviation of the sample and the sample size.
Hypothesis Test Decisions:
- Reject the null hypothesis
- Fail to reject the null hypothesis
Multiple Linear Regression
A regression model that estimates the relationship between two or more independent variables and a
Statistical Analysis: Variables, Data, and Inference
Variables and Study Groups
- Categorical variables
- Quantitative variables
- Explanatory variable
- Response variable
Study Groups –> Population
–> sample
Sampling and Data Collection
Sample:
- Statistical Inference
- Sampling Bias
- Random Sample
- Association vs. Causation
- Confounding Variables
Collecting Data:
- Experiment
- Observational Study
- Randomized Experiment
- Control Group
- Placebo
- Blind Experiment
- Double-Blind Experiment
- Randomized Comparative Experiment
- Matched Pairs