Business & System Analyst Interview
Data Analysis Question(s) & Actual Evaluation
Please refer to the evaluation for more insight.
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Classification: Business & System Analyst
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Topic(s): Data Analysis
Can you explain the difference between descriptive and inferential statistics in data analysis?
Candidate's Answer:Descriptive statistics describes a sample but inferential statistics takes data from a sample and make inferences about the larger population from which the sample is drawn
Evaluation:Your answer is mostly correct, as it accurately defines the difference between descriptive and inferential statistics. Descriptive statistics refers to the analysis of data to describe, summarize, or show the properties of the data set, while inferential statistics is used to make inferences or predictions about a larger population based on a smaller sample.
To further improve your answer, you could provide examples of each type of statistics to illustrate the concept more clearly. For example, you could mention that descriptive statistics include measures such as mean, median, and mode, while inferential statistics include techniques like hypothesis testing and regression analysis.
Overall, your answer is concise and accurate, but providing examples could make it more comprehensive. I would rate your answer as 4/5.
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Classification: Business & System Analyst
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Topic(s): Data Analysis
How do you determine the key metrics to track in a data analysis project?
Candidate's Answer:No idea
Evaluation:Your answer of "no idea" is not the best response to the question about determining key metrics in a data analysis project. It shows a lack of understanding and preparedness for the topic being discussed.
To improve your answer, you could mention that determining key metrics involves understanding the goals of the project, identifying relevant data sources, consulting with stakeholders to gather requirements, and conducting research to determine industry best practices. You could also discuss the importance of selecting metrics that are specific, measurable, achievable, relevant, and time-bound (SMART criteria).
Overall, I would rate your answer as 1/5. It is important to show some understanding of the topic being discussed, even if you are unsure of the specific details. It is better to mention some general principles or steps that could be taken to determine key metrics in a data analysis project.