Final answer:
When working with raw data from source systems, it is important to assume the data is accurate and valid, but also consider potential uncertainty and bias. Careful analysis and interpretation of the data using statistical tools is necessary.
Step-by-step explanation:
When working with raw data from source systems, one should always assume that the data is accurate and valid. However, it is important to be aware of the potential for uncertainty or bias in the data.
For example, if the data is collected through surveys or interviews, there may be a certain degree of subjectivity or bias introduced by the respondents. Similarly, if data is extracted from graphs or charts, there may be a margin of error that needs to be taken into account.
Therefore, it is important to carefully analyze and interpret the data, using statistical tools and critical thinking skills to ensure reliable conclusions.
When dealing with raw data from source systems, you should always assume that there is some level of uncertainty or inaccuracy inherent in the data. Data extraction uncertainties must be estimated and considered when analyzing such data.
Raw data often require thorough analysis and interpretation to become meaningful evidence to support a hypothesis or conclusion. It is important to apply critical skills to evaluate the reliability and bias of the sources of your data.
Additionally, one should recognize that numbers taken from graphs, measurements, or any type of gathered data may not be exact and can vary from the expected values. It is vital to assess whether the data are within the estimated uncertainties to ensure the validity of your conclusions.