The correct answer is: A. Inferential
An inferential model is a statistical model that is used to make inferences about a population based on a sample. Inferential models are often used in data analysis to make predictions about future events or to test hypotheses about the relationship between variables.
Descriptive models are used to describe the data that is collected. They do not make inferences about the population from which the data was collected. Descriptive models are often used to summarize data, to identify trends, or to compare groups.
Causal models are used to identify the cause and effect relationships between variables. Causal models are often used in research to determine the effects of a treatment or intervention.
All of the mentioned models are used in data analysis, but inferential models are the gold standard for data analysis. This is because inferential models allow us to make inferences about the population from which the data was collected. Descriptive and causal models are also useful, but they do not allow us to make inferences about the population.
Here are some examples of inferential models:
- Linear regression: A linear regression model is used to predict the value of a dependent variable based on the values of one or more independent variables.
- Logistic regression: A logistic regression model is used to predict the probability of a binary outcome (e.g., whether or not a person will purchase a product) based on the values of one or more independent variables.
- Poisson regression: A Poisson regression model is used to predict the number of events that occur in a given time period based on the values of one or more independent variables.
Here are some examples of descriptive models:
- Bar chart: A bar chart is a graphical representation of data that is used to compare the values of two or more variables.
- Line graph: A line graph is a graphical representation of data that is used to show the change in the value of a variable over time.
- Pie chart: A pie chart is a graphical representation of data that is used to show the relative proportions of the values of two or more variables.
Here are some examples of causal models:
- Randomized controlled trial: A randomized controlled trial is an experimental study in which participants are randomly assigned to one of two or more groups. One group receives the treatment being studied, and the other group does not. The results of the study are then used to determine whether the treatment is effective.
- Observational study: An observational study is a study in which participants are not randomly assigned to groups. Instead, the groups are formed based on the values of one or more variables. The results of an observational study can be used to identify associations between variables, but they cannot be used to determine cause and effect.