Forecasting Data Notes – Class 11 Data Science (844)
Forecasting Data Notes for Class 11 Data Science are based on the latest CBSE syllabus. Learn forecasting, observational studies, and their advantages and disadvantages with easy explanations, examples, and exam-focused notes.
Forecasting
- Forecasting is a statistical process used to predict future events or outcomes.
- It uses present data and historical data to make predictions as accurately as possible.
Observational Study
- An observational study is a study in which the subjects are only observed, and the results are recorded.
- In an observational study, the researcher does not interfere or influence the outcome.
- For example, a researcher compares the health of people who have followed an organic diet with those who have not.
- The collected data is analyzed to draw conclusions about the effect of an organic diet on overall health.
Why Use an Observational Study Instead of a Trial Assessment?
- An observational study is used when it is not possible or practical to perform a trial assessment.
- It is preferred when assigning subjects to random treatments is unethical.
- For example, deliberately exposing people to polluted air to study its health effects is unethical.
- A trial assessment may require a large amount of money, making it difficult to conduct.
- In some situations, it is not feasible to randomly assign subjects to different groups, so an observational study is preferred.
Advantages of Observational Study
- It is a simple and widely used method of collecting data.
- With proper training, a person can make accurate observations.
- Since observations are made in a natural setting, they can provide deep and useful insights.
- It can reveal information that may not be obtained through surveys.
Disadvantages of Observational Study
- The insights gained may not always justify the time spent on the study.
- Some events may not occur while the observer is present.
- The observer may miss important details during observation.
- The study may lead to unfair conclusions if it is not analyzed by an expert.
